The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. These results reflect the overall impact observed following the entire course of the COVID-19 pandemic and are not specific to a particular wave. The analysis revealed that older participants experienced a more pronounced decline in productivity, with a mean decrease of 35% compared to younger participants. Female participants, on average, had a 28% decrease in productivity compared to their male counterparts. Moreover, individuals with lower socioeconomic status exhibited a substantial decline in productivity, experiencing an average decrease of 40% compared to those with higher socioeconomic status. Similarly, participants who slept for fewer hours per night had a significant decline in productivity, with an average decrease of 33% compared to those who had sufficient sleep. The machine learning analysis identified age, specialty, COVID-19 complications, socioeconomic status, and sleeping time as crucial predictors of productivity score. The study highlights the significant impact of post-COVID-19 on the productivity of medical staff and doctors in Iraq. The findings can aid healthcare organizations in devising strategies to mitigate the negative consequences of COVID-19 on medical staff and doctors' productivity.
The banking industry, as a result of the great challenges it faced, required continuous development of the principles of management, control and mechanisms used. The Basel Committee on Banking Supervision has played a leading role in legalizing many of these developments and has been able to contribute significantly to establishing a common framework for banking supervision, The central role in the various countries of the world is based on coordination between the various regulatory authorities and thinking about finding mechanisms to confront the risks faced by banks, recognizing the importance of the banking sector in the stability of domestic and international banking systems or the danger of this sector in the emergence of F
... Show MoreThe objective of the research is to measure the impact of social responsibility on the financial performance of the National Bank of Iraq for the period from 2014 to 2016 (3 years) through discussing and analyzing the level of practice of the Bank of Baghdad for social responsibility and the impact on their financial performance during the period. To measure the independent variable (CSR), the researcher used the CSR Disclosure Index and relied on the ROA as an indicator to measure the dependent variable (financial performance). The results of the research showed the main hypothesis of the research, which states that the social responsibility of the banks has no significant impact on the financial performance. In relation to the disclosu
... Show MoreABSTRACTObjective: The objective of this study is to develop a controlled release matrix tablet of candesartan cilexetil to reduce the frequency of administration,enhance bioavailability and improve patient compliance; a once daily sustained release formulation of candesartan cilexetil is desirable.Methods: The prepared tablets from F1 to F24 were evaluated with different evaluation parameters like weight variation, drug content, friability,hardness, thickness and swelling ability. In vitro release for all formulas were studied depends on the type and amount of each polymer, i.e. (16 mg,32 mg and 48 mg) respectively beside to the combination effect of polymers on the release of the drug from the tablet.Results: In vitro release show
... Show MoreIn this study the thermal conductivity of the epoxy composites were characterized as function of volume fraction, particle size of fillers and the time of immersion(30,60,90)days in water .Composites plates were prepared by incorporating (bi-directional) (0º-90º) glass fiber and silicon carbide (SiC) particles of (0.1,0.5,1)mm as particle size at (10%,20%,30%,40%) percent volume in epoxy matrix.
The composites shows slightly increase of the thermal conductivity with increasing volume fraction, particle size and increase with increasing the days of immersion in water. The maximum thermal conductivity (0.51W/m.K) was obtained before the immersion in water at 90 days for epoxy reinforcement by bi-directional glass fiber and SiC particl
The present work involves studying the effect of electrolyte composition [@1= 0.5 wt.% NH4F / 5% H2O / 5% Glycerol (GLY)/ 90% Ethylene Glycol (EG)] and [ @2= 0.5 wt. % NH4F / 5% H2O / 95% Ethylene Glycol (EG)] on the structural and photoelectrochemical properties of titania nanotubes arrays (TNTAs). TNTAs substrates were successfully carried out via anodization technique and were carried out in 40 V for one hour in different electrolytes (@1, and @2). The properties of physicochemical of TNTAs were distinguished via an X-ray Diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), an Energy Dispersive X-ray (EDX), and UV–visible diffuse reflectance. The photoelectrochemical response of TNTAs was evaluated
... Show MoreLiquid – liquid interface reaction is the method for
preparation nanoparticles (NP'S) which depend on the super
saturation of ions that provide by using the system that consist from
toluene and water, the first one is above the second to obtain
nanoparticles (NP's) CdS at the interface separated between these
two immiscible liquid. The structure properties were characterized by
XRD-diffraction and transmission electron microscopy.
The crystalline size estimate from X-ray diffraction pattern
using Scherer equation to be about 7nm,and by TEM analysis give us
that ananosize is about 5 nm which give a strong comparable with
Bohr radius. Photoluminescence analysis give two emission peak,
the first one around
In this study, the effect of design parameters such as pipe diameter, pipe wall thickness, pipe material and the effect of fluid velocity on the natural frequency of fluid-structure interaction in straight pipe conveying fully developed turbulent flow were investigate numerically,analytically and experimentally. Also the effect of support conditions, simply-simply and clamped-clamped was investigated. Experimentally, pipe vibrations were characterized by accelerometer mounted on the pipe wall. The natural frequencies of vibration were analyzed by using Fast Fourier Transformer (FFT). Five test sections of two different pipe diameters of 76.2
mm and 50.8 mm with two pipe thicknesses of 3.7 mm and 2.4 mm and two pipe materials,stainles
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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