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Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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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.

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Publication Date
Thu Jan 01 2026
Journal Name
Aip Conference Proceedings
Bayesian methodology for spatial quantile autoregressive model estimation
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Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data

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Publication Date
Wed Mar 26 2025
Journal Name
قضايا سياسية
The role of strategic planning in American decision-making
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The purpose of this research is to study the organic planning in the United Industry Alliance, focusing on an applied model. It takes the concept of good planning, and its importance in the overall picture, well into political, economic, and military policy. It also analyzes how the United States has used this year to address the challenges that nationalism targets. The research draws on typical examples to illustrate the differences between researcher and decision effectiveness. It also discusses the factors that lead to the success or failure of dynamic planning, and draws lessons from it in other countries. Finally, the researcher begins to help in planning the goal as a basic tool in enhancing effectiveness.

Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using Mehar method to change fuzzy cost of fuzzy linear model with practical application
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  Many production companies suffers from big losses because of  high production cost and low profits for several reasons, including raw materials high prices and no taxes impose on imported goods also consumer protection law deactivation and national product and customs law, so most of consumers buy imported goods because it is characterized by modern specifications and low prices.

  The production company also suffers from uncertainty in the cost, volume of production, sales, and availability of raw materials and workers number because they vary according to the seasons of the year.

  I had adopted in this research fuzzy linear program model with fuzzy figures

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
CONSTRUCTION DELAY ANALYSIS USING DAILY WINDOWS TECHNIQUE
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Delays occur commonly in construction projects. Assessing the impact of delay is sometimes a contentious
issue. Several delay analysis methods are available but no one method can be universally used over another in
all situations. The selection of the proper analysis method depends upon a variety of factors including
information available, time of analysis, capabilities of the methodology, and time, funds and effort allocated to the analysis. This paper presents computerized schedule analysis programmed that use daily windows analysis method as it recognized one of the most credible methods, and it is one of the few techniques much more likely to be accepted by courts than any other method. A simple case study has been implement

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
QTAIM study of the bonding in triosmium trihydride cluster [Os3(µ-H)3(µ3-ɳ2-CC7H3(2-CH3)NS)(CO)8]
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    The Atoms in Molecules (AIM) analysis for triosmium cluster, which contains trihydridede, carbon, carbonyl and 2-methylbenzothiazolide ligands, [Os3(µ-H)3(µ3-ɳ2-CC7H3(2-CH3)NS)(CO)8] is reported. Bonding features in this cluster has been analyzed based on QTAIM ("Quantum Theory of Atoms in Molecules") in this work. The topological indices derived from electron density of relevant interactions in triosmium compound have been studied. The major interesting point of the AIM analyses is that the core of part (Os3H3) reveals the absence of any critical points and bond paths connecting any pairs of O

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Publication Date
Fri Jan 16 2026
Journal Name
F1000research
Update Quasi-Newton Algorithm for Training ANN
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The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio

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Publication Date
Mon Apr 28 2025
Journal Name
Chemical Papers
New chemiluminometric method for the determination of azithromycin in a continuous flow injection analysis system
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A novel analytical method is developed for the determination of azithromycin. The method utilizes continuous flow injection analysis to enhance the chemiluminescence system of luminol, H2O2, and Cr(III). The method demonstrated a linear dynamic range of 0.001–100 mmol L-1 with a high correlation coefficient (r) of 0.9978, and 0.001–150 mmol L-1 with a correlation coefficient (r) of 0.9769 for the chemiluminescence emission versus azithromycin concentration. The limit of detection (L.O.D.) of the method was found to be 18.725 ng.50 µL−1 based on the stepwise dilution method for the lowest concentration within the linear dynamic range of the calibration graph. The relative standard deviation (R.S.D. %) for n = 6 was less than 1.2%

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Publication Date
Sun Mar 01 2026
Journal Name
Surra Man Ra'a
Gazeta.ru Dialogues: Analyzing Social News through a Linguistic Prism
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This study employs a critical discourse analysis approach to investigate the linguistic and discursive mechanisms employed by the prominent Russian online news platform Gazeta.ru in its coverage of social news. Drawing on an interdisciplinary framework integrating critical discourse analysis (CDA), media discourse analysis, and sociolinguistic perspectives, the research examines how language is used to construct and disseminate societal narratives. The analysis focuses on a dataset of Gazeta.ru articles published in March 2024, encompassing topics such as health, travel, and consumer affairs. Through a multi-level analytical approach, the study explores macro-level discursive strategies and microlevel linguistic choices, unveiling the intri

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Three-Dimensional Explicit Finite Element Simulation of Piled-Raft Foundation
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This paper aims to validate a proposed finite element model to be adopted in predicting displacement and soil stresses of a piled-raft foundation. The proposed model adopts the solid element to simulate the raft, piles, and soil mass. An explicit integration scheme has been used to simulate nonlinear static aspects of the piled-raft foundation and to avoid the computational difficulties associated with the implicit finite element analysis.

The validation process is based on comparing the results of the proposed finite element model with those of a scaled-down experimental work achieved by other researchers. Centrifuge apparatus has been used in the experimental work to generate the required stresses to simulate t

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Publication Date
Sun Jun 20 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MULTIVARIATE ANALYSIS OF THE STEM ANATOMICAL CHARACTERS OF TERMINALIA L. (COMBRETACEAE) IN EGYPT
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A comparative investigation of the anatomical characters through a microscopical examination of the prepared transverse sections of the stem was carried out. Six plates with 32 photomicrographs were provided to convincingly show the considerable variations of anatomical characters within the nine examined species. The matrix of 18 anatomical characters which included nine quantitative and nine qualitative was applied for the clustering analysis (CA) followed by the principal component analysis (PCA) using the Multivariate Analysis of Ecological Data, PC-ORD.
The results exhibited significant variations among the species resulting in the construction of an artificial key; this key accurately represents a sufficient tool to display the

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