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A comprehensive review of drivers influencing flu vaccine acceptance in the Middle East over the last six years: using Health Belief Model
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Abstract<sec> <title>Objectives

The objectives of this study were to review the literature covering the perceptions about influenza vaccines in the Middle East and to determine factors influencing the acceptance of vaccination using Health Belief Model (HBM).

Methods

A comprehensive literature search was performed utilizing PubMed and Google Scholar databases. Three keywords were used: Influenza vaccine, perceptions and Middle East. Empirical studies that dealt with people/healthcare worker (HCW) perceptions of influenza vaccine in the Middle East and written in English were included. The search covered articles published between January 2015 and November 2020.

Key Findings

A total of 34 cross-sectional studies covering a total of 35 518 participants from 22 countries were included in this review. The overall influenza vaccination rates were generally low (&lt;50%) among general population, particularly among pregnant women and children. HCWs had relatively higher vaccination rates compared with general population. Old age, health comorbidities or working in high-risk environments were noted as major motivators to receive the vaccine. Concerns about adverse reactions and the lack of vaccine efficacy were the most predominant reported barriers to receiving the vaccines. Lastly, cues to actions included receiving advice from HCWs, influence of institutional requirement, awareness/educational pamphlets and influence from the media.

Summary

The HBM can be helpful in identifying and analysing motivators and barriers to vaccination. Additionally, by looking at the root causation, this model can help plan campaigns to increase vaccination rates in the region. Finally, we recommend empowering HCWs to proactively advocate for vaccination as part of preventive care.

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Publication Date
Fri Sep 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Real Time Wireless Monitoring and Controlling of 3-D Single Point Incremental Tool
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Maintenance of machine tools can be improved significantly by analyzing the operating of manufacturing process with the real-time monitoring system for 3-D single point deformation measurements. Therefore, the process of manufacturing could be optimized with less cost. Recently, wireless technology and internet of things (IOT) applied on intelligent machine has witnessed a significant advance with augmented virtuality, the analysis and the process certainly would contribute to enhance the intelligence of that machine. This paper presents a group of the wireless sensors and 3D animation technologies for data monitoring and analyzing. Three degree of freedom robotic hand structure has been selected as a prototype to be form the process of the

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Publication Date
Sun Sep 06 2015
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Baghdad Science Journal
Preparation and Characterization of Some Metal Complexes with Heterocyclic Azo Ligand (4-SuBAI)
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The preparation and characterization of the Cu (II), Co(II), Ni(II), Zn(II), Cd(II), and Hg(II) metal complexes of heterocyclic azo ligand 2-[(4`-sulphamide phenyl) azo] -4,5-diphenyl imidazole (4-SuBAI) have been studied by elemental analysis, FT-IR and UV-Vis Spectroscopic, magnetic moment and molar conductance methods. The analytical data showed that all chelate complexes were prepared with (metal-ligand) ratio of (1:2). The general formula of these complexes was [ML2X2]. nH2O [were L=2-[(4`-sulphamide phenyl) azo]-4,5-diphenyl imidazole and X=Cl, and the octahedral geometry were suggested for these complexes .

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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research &amp; Development
Effect of Gold Nanoparticles and Laser on Platelet, Lymphocytes, and White Blood Cells
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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparative study of between P chart and Multinomial Fuzzy quality control chart ( FM).
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Quality is one of the important criteria to determine the success of product. So quality control is required for all stages of production to ensure a good final product with lowest possible losses. Control charts are the most important means used to monitor the quality and its accuracy is measured by quickly detecting unusual changes in the quality to maintain the product and reduce the costs and losses that may result from the defective items. There are different types of quality control charts and new types appeases involving the concept of fuzziness named multinomial fuzzy quality control chart (FM) , dividing the product to accepted and not may not be accurate therefore adding fuzziness concept to quality charts confirm and a

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Frequency Domain Analysis for Geometric Nonlinear Seismic Response of Tall Reinforced Concrete Buildings
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This paper aims to study the second-order geometric nonlinearity effects of P-Delta on the dynamic response of tall reinforced concrete buildings due to a wide range of earthquake ground motion forces, including minor earthquake up to moderate and strong earthquakes. The frequency domain dynamic analysis procedure was used for response assessment. Reinforced concrete building models with different heights up to 50 stories were analyzed. The finite element software ETABS (version 16.0.3) was used to analyze reinforced concrete building models.

The study reveals that the percentage increase in buildings' sway and drift due to P-Delta effects are nearly constant for specific building height irrespective of the seism

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Sat Jan 01 2022
Journal Name
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Adsorption of Phosphorous and Zinc, and their interaction and processing power on Bentonite
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Wed Jan 01 2020
Journal Name
Biochemical Cellular Archives
Synthesis, characterizationand antibacterialactivity of PVA cyclic acetal (Cu) metal complex / chitosan polymer blend
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Sun Jun 01 2014
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Efficacy of Bacillus thuringiensis (Berliner) isolates on fig moth, Ephestia cautella (Walker) Larvae
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Publication Date
Mon Apr 01 2019
Journal Name
2019 International Conference On Automation, Computational And Technology Management (icactm)
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
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Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

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Publication Date
Mon Feb 01 2016
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