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Association of Phantom Vibration and Ringing Syndrome and Job-Related Stress among Nurses in Al-Nasiriyah City
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Objectives: The study aims to: (1) assess the prevalence of phantom vibration and ringing syndrome among
nurses, (2) determine the level of job-related stress among those nurses who are working at teaching hospitals in
Al- Nasiriyah city, and (3) identify the association between job-related stress and experience of phantom
vibration and ringing syndrome.
Methodology: : A descriptive design, cross-sectional study was used for the present study was carried out
from 4th December, 2017 to the 4th April, 2018 in order to determine the association of Phantom
Vibration and Ringing Syndrome with Job - Related Stress among nurses at Teaching Hospitals in AlNasiriyah
City , on a purposive (non-probability) sample was used in this study that composed of (600) nurses
who are working in the morning and night shifts . Data were collected by using the technique of self –
administrative report was consisted of four parts: ' socio-demographic characteristics for the nurses, factors
that are related to mobile use among the nurses , phantom vibration and ringing syndrome scale and job –
related stress scale . The validity of the questionnaire was obtained through a panel of experts and the
internal consistency reliability was achieved through the application of Alpha Correlation Coefficient (r=0.76)
which was statistically acceptable.
Results: The finding of the study revealed that phantom vibration and ringing syndrome are experienced
moderately among nurses evidenced by significant level among all items of the scale, there were no
significant association between phantom vibration \ ringing syndrome and job- related stress among nurses.
Recommendations: The study recommended spreading awareness among nurses regarding the risks of mobile
use through instructional sessions and continuing education lectures and the necessary conducting of further
similar studies for exploring the factors that influence the job-related stress in order to apply the management for
such factors

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Adsorption of Levofloxacine Antibacterial from Contaminated Water by Non – Conventional Low Cost Natural Waste Materials
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An experimental study was conducted with low cost natural waste adsorbent materials, barley husks and eggshells, for the removal of Levofloxacine (LEVX) antibacterial from synthetic waste water. Batch sorption tests were conducted to study their isothermal adsorption capacity and compared with conventional activated carbon which were, activated carbon > barley husks > eggshells with removal efficiencies 74, 71 and 42 % with adsorbents doses of 5, 5 and 50 g/L of activated carbon, barley husks, and eggshells respectively. The equilibrium sorption isotherms had been analyzed by Langmuir, Freundlich, and Sips models, and their parameters were evaluated. The experimental data were correlated well with the Langmuir model which gives the

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Multichannel Optimization With Hybrid Spectral- Entropy Markers for Gender Identification Enhancement of Emotional-Based EEGs
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Publication Date
Tue Jan 19 2021
Journal Name
Archives Of Civil And Mechanical Engineering
Push-out test of steel–concrete–steel composite sections with various core materials: behavioural study
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Steel–concrete–steel (SCS) structural systems have economic and structural advantages over traditional reinforced concrete; thus, they have been widely used. The performance of concrete made from recycled rubber aggregate from scrap tires has been evaluated since the early 1990s. The use of rubberized concrete in structural construction remains necessary because of its high impact resistance, increases ductility, and produces a lightweight concrete; therefore, it adds such important properties to SCS members. In this research, the use of different concrete core materials in SCS was examined. Twelve SCS specimens were subjected to push-out monotonic loading for inspecting their mechanical performance. One specimen was constructed from co

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Publication Date
Wed Apr 01 2020
Journal Name
Saudi Pharmaceutical Journal
Pharmacist role to enhance the prescribing of hospital discharge medications for patients after heart attack
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Publication Date
Tue May 06 2025
Journal Name
Aip Conference Proceedings
Enhance the performance of the wind turbine blade based on the blade element momentum theory
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In order to improve the effectiveness, increase the life cycle, and avoid the blade structural failure of wind turbines, the blades need to be perfectly designed. Knowing the flow angle and the geometric characteristics of the blade is necessary to calculate the values of the induction factors (axial and tangential), which are the basis of the Blade Element Momentum theory (BEM). The aforementioned equations form an implicit and nonlinear system. Consequently, a straightforward iterative solution process can be used to solve this problem. A theoretical study of the aerodynamic performance of a horizontal-axis wind turbine blade was introduced using the BEM. The main objective of the current work is to examine the wind turbine blade’s perf

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Publication Date
Fri Jan 01 2021
Journal Name
Desalination And Water Treatment
Electrosorption of cadmium ions from the aqueous solution by a MnO2/carbon fiber composite electrode
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The nanostructured MnO2 /carbon fiber (CF) composite electrode was prepared using the anodic electrodeposition process. The crystal structure and morphology of MnO2 particles were determined with X-ray diffraction and field-emission scanning electron microscopy. The electrosorptive properties of the prepared electrode were investigated in the removal of cadmium ions from aqueous solution, and the effect of pH, cell voltage, and ionic strength was optimized and modeled using the response surface methodology combined with Box–Behnken design. The results confirm that the optimum conditions to remove Cd(II) ions were: pH of 6.03, a voltage of 2.77 V, and NaCl concentration of 3 g/L. The experimental results showed a good fit for the Freundli

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Publication Date
Mon Aug 01 2011
Journal Name
International Journal Of Research And Reviews In Computer Science
Detection of the photon number splitting attack by using decoy states quantum key distribution system
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The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.

Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Wed Sep 24 2014
Journal Name
International Journal Of Environmental Science And Technology
Removal of copper ions from contaminated groundwater using waste foundry sand as permeable reactive barrier
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