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Psychological flow and mental immunity as predictors of job performance for mental health care practitioners during COVID-19
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Background Numerous studies indicated that workers in the health sector suffer from work stress, hassles, and mental health problems associated with COVID-19, which negatively affect the completion of their job tasks. These studies pointed out the need to search for mechanisms that enable workers to cope with job stress effectively. Objectives This study investigated psychological flow, mental immunity, and job performance levels among the mental health workforce in Saudi Arabia. It also tried to reveal the psychological flow (PF) and mental immunity (MI) predictability of job performance (JP). Method A correlational survey design was employed. The study sample consisted of 120 mental health care practitioners (therapists, psychologists, counselors)who lived in Saudi Arabia. Sixty-four were men, 56 were women, and their ages ranged between 27 and 48 (36.32±6.43). The researchers developed three measurements of psychological flow, mental immunity, and job performance. After testing their validity and reliability, these measures were applied to the study participants. Results The results found median levels of psychological flow, mental immunity, and job performance among mental health care practitioners. Also, the results revealed that psychological flow and mental immunity were statistically significant predictors of job performance. The psychological flow variable contributed (38.70%) and mental immunity (54.80%) to the variance in job performance of mental health care practitioners.

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Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Thu Feb 25 2021
Journal Name
Iraqi Journal Of Agricultural Sciences
OPTIMIZATION OF LEVOFLOXACIN REMOVAL FROM AQUEOUS SOLUTION USING ELECTROCOAGULATION PROCESS BY RESPONSE SURFACE METHODOLOGY
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This study was aimed to investigate the response surface methodology (RSM) to evaluate the effects of various experimental conditions on the removal of levofloxacin (LVX) from the aqueous solution by means of electrocoagulation (EC) technique with stainless steel electrodes. The EC process was achieved successfully with the efficiency of LVX removal of 90%. The results obtained from the regression analysis, showed that the data of experiential are better fitted to the polynomial model of second-order with the predicted correlation coefficient (pred. R2) of 0.723, adjusted correlation coefficient (Adj. R2) of 0.907 and correlation coefficient values (R2) of 0.952. This shows that the predicted models and experimental values are in go

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Publication Date
Mon Feb 02 2015
Journal Name
Journal Of Engineering, University Of Baghdad
'Impact Analysis of Reinforced Concrete Columns with Side Openings Subjected to Eccentric Axial Loads
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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Analysis the Surface Morphology of the Porous Media by using Atomic Force Microscope technique
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An atomic force microscope (AFM) technique is utilized to investigate the polystyrene (PS) impact upon the morphological properties of the outer as well as inner surface of poly vinyl chloride (PVC) porous fibers. Noticeable a new shape of the nodules at the outer and inner surfaces, namely "Crater nodules", has been observed. The fibers surface images have seen to be regular nodular texture at the skin of the inner and outer surfaces at low PS content. At PS content of 6 wt.%, the nodules structure was varied from Crater shape to stripe. While with increasing of PS content, the pore density reduces as a result of increasing the size of the pore at the fiber surface. Moreover, the test of 3D-AFM images shows that the roughness of both su

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Publication Date
Fri Jan 01 2021
Journal Name
Fme Transactions
FAT-based adaptive backstepping control of an electromechanical system with an unknown input coefficient
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This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used

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Publication Date
Tue Jan 01 2019
Journal Name
Opcion
Enhancing Islamic Concepts through English Children's Lit-erature: Al- Ibtila, The Test of Patience
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Publication Date
Sun Mar 01 2020
Journal Name
Al-ustath Journal For Human And Social Sciences
HE SIGNIFICANCE OF FREUD’S THEORY THE UNCANNY IN NELLA LARSON’S PASSING: A PSYCHOANALYTIC STUDY
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ABSTRACT This study closely investigates the elements of Sigmund Freud’s theory “The Uncanny” in one of Larson’s most famous novels. Although the novel touches upon racial issues, the study explores the mysterious relationship between Irene and Clare based on the main features of Freud’s “The Uncanny,” which are represented by hidden sexual desire, envy, supernatural power, and double characters. The aspect of the sexual desire is indicated in the novel by sexual undertones expressed by Irene towards Clare’s physical features. Envy in the novel is expressed by Irene who shows resentful longing aroused by Clare’s possessions and qualities due to her passing to the white community. The aspect of omnipotence of thoughts is in

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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Publication Date
Wed Dec 01 2021
Journal Name
Case Studies In Construction Materials
CFRP strengthening efficiency on enhancement punching shear resistance of RC bubbled slabs with openings
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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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