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 microstructures of rapidly solidified laser clad layers of laser cladding of Inconel 617 with different nickel-aluminum premixed clad powders are discussed. The effect of different cladding speeds on the microstructures of rapidly solidified laser clad layers is discussed too. The detailed microstructural results showed that different growth mechanisms are produced during rapid solidification. These are planar, cellular, cellular/dendritic and dendritic.
The research is Concerned the Relationship between Self Management which is a modern administrative term and its dimensions "Self Control, Trust, and Conscientiousness" with the Hardiness and its dimensions "Challenge, Commitment, and Control". And the impact of the first variable on the second in The Hospital of Alshaheed Gaze Alharery.
The Questionnaire used and distributed on sample (60) Persons, contain from (40) Doctor, and (20) Employees from the total society (103).
The statistical methods have been used for testing the hypothesis is the mean, standard deviation correlation coefficient.
The resea
... Show MoreSocial interaction is the platform that enables people to connect and practice language. Active listening stimulates them to understand the language they are speaking. The problem of the study highlights that less attention to listening among speaking, reading, and writing skills causes the weakness of collaborative learning. This paper contributes to characterizing the effectiveness of collaborative learning in developing learner’s listening skills. It aims to underscore the role of target language learners as members of the learning groups and of the teacher in the collaborative learning process. 130 Iraqi EFL teachers from different colleges at the University of Baghdad participated in this study. The scores in the statistical data wer
... Show MoreCorrect grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
... Show MoreBackground: asthma has an influence on craniofacial development. Recently evidences show that there is an association between oral health problems and chronic lung disease. The present study was designed to estimate the changes in arch dimension measurements among asthmatic children aged 12 years old who were collected from AL- Zahra Center Advisory for Allergy and Asthma and compare them with the non-asthmatic children of the same age and gender. Material and Methods: Fifty children (25 asthmatic and 25 non- asthmatic children) were included for the odontometric measurement. For both upper and lower study models, photographs were taken using special photographic apparatus for each child, and the statistical analysis were done by using SPSS
... Show MoreTwo grades of paving asphalt with penetration of 46 and 65 are studied for determining changes in their physical and chemical properties caused by ageing.
The ageing process has been conducted on two petroleum paving asphalt cement using thin film oven test at 150, 163 and 175 C, and ageing time 5, 10,15, 20, 25 and 30 hours. The effect of ageing time and temperature on penetration, kinematic viscosity, softening point, solubility in trichloroethylene, heat loss and changes in chemical composition are investigated. The results of thin film oven test process indicte that the asphaltenes concentration of all aged asphalt increases with increasing ageing time, while the opposite was observed for polar-aromatic and naphthene-aromatic. The
The stability and releasing profile of 2:1 core: wall ratio ibuprofen microcapsules prepared by aqueous coacervation (gelatin and acacia polymers coat) and an organic coacervation methods (ethyl cellulose and sodium alginate polymers coat) in weight equivalent to 300mg drug, were studied using different storage temperatures 40°C, 50°C ,60°C and refrigerator temperature 4°C in an opened and closed container for three months (releasing profile) and four months (stability study).It was found that, these ibuprofen microcapsules were stable with expiration dates of 4.1 and 3.1 years for aqueous and an organic method respectively.Aqueous prepared ibuprofen microcapsules were found more stable than those microcapsules prepared by or
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