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Emotional Trends, and Emotional Exhaustion in organizations: (Developing foundations the philosophy and thinking in organizational behavior)
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Emotional exhaustion considered one of the critical factors in the formation and composition of organizational behavior of individuals within organizations, as well as social behavior and psychological, and emotional exhaustion is one of the three components of burnout, as well as depersonalization (cynicism) and low achievement, the emergence of research relevant to this concept began at the beginning of the seventies of the twentieth century, then started to become clear features in the eighties it. This research aims to build intellectual framework for draining emotional exhaustion through highlight on most important philosophical contents, as well as review and analysis of some models associated with this concept, and then a statement its interaction with some of the other individual emotional trends, as is the case in empathy role, and conflict of roles and Theory of protection sources, and so out of intellectual dilemma which says to the omission role of emotional exhaustion in the Arab management thought of organizational behavior in business organizations, despite the clarity of such importance in many aspects such as organizational performance, and organizational citizenship, and labor turnover. Finally the search represented some implications for future research in a set of recommendations for our organizations, as well as a range of topics proposed introduction for researchers and professionals to engage in the midst of this subject in order to detect mastery, and the extent of its applicability in our organizations, and through investigation of a group of hypotheses proposed, such as emotional exhaustion relationship with individual performance, and the impact of emotional exhaustion in achieving customer satisfaction. Finally research involved submits a proposal to form a statement the intermediary role of the emotional drain of the relationship between leadership styles and organizational loyalty.

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Publication Date
Fri Aug 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Types of the Fiber Glass-Mat on Fatigue Characteristic of Composite Materials at Constant Fiber Volume Fraction: Experimental Determination
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The aim of this work is to study the influence of the type of fiber glass –mat on fatigue behavior of composite material which is manufactured from polyester and E-glass (woven roving, chopped strand mat (CSM)) as a laminate with a constant fiber volume fraction (VF) of 33%. The results showed that the laminates reinforced with E-glass (woven roving) [0/90, ±45.0/90] and [0/90, CSM, 0/90] have lower fatigue strength than the laminates reinforced with E-glass [0/90]3,[CSM]3 and [CSM, 0/90, CSM]  although they had different tensile strength; the best laminate was [0/90]3 .

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Publication Date
Thu Jun 15 2023
Journal Name
Alustath Journal For Human And Social Sciences
The Effectiveness of a Cognitive-Behavioral Treatment Program to Reduce Nervous Fatigue for Mothers of Children with Cerebral Palsy
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Cognitive-behavioral therapy is one of the most important relatively recent; treatment programs that attempt to modify behavior and control psychological disorders by modifying the individual's thinking style and awareness of himself and his environment, and cognitive reconstruction by replacing negative thoughts with positive ones. The current study aimed to know the effectiveness of a cognitive behavioral treatment program in reducing nervous fatigue among mothers of children with cerebral palsy. The sample on which the nervous fatigue scale was applied consisted of (30) mothers whose son suffers from cerebral palsy, and the results indicated that (24) mothers suffer from nervous fatigue. This sample was divided

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Compared of estimating two methods for nonparametric function to cluster data for the white blood cells to leukemia patients
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Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
The Remediation of Congo Red-Contaminated Groundwater by using a Permeable Reactive Barrier Through Modified Waterworks Sludge MgAl-LDH
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This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the analysis of contaminant transport under diverse conditions.

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
The Numerical Technique Based on Shifted Jacobi-Gauss-Lobatto Polynomials for Solving Two Dimensional Multi-Space Fractional Bioheat Equations
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This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

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Publication Date
Wed Oct 31 2018
Journal Name
International Journal Of Research In Pharmaceutical Sciences
The impact of systemic hypertension-related heart remodeling on right ventricle mechanics: A two-dimensional echocardiographic speckle tracking study
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Thu Jan 27 2022
Journal Name
Nanomaterials
Improving the Melting Duration of a PV/PCM System Integrated with Different Metal Foam Configurations for Thermal Energy Management
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The melting duration in the photovoltaic/phase-change material (PV/PCM) system is a crucial parameter for thermal energy management such that its improvement can realize better energy management in respect to thermal storage capabilities, thermal conditions, and the lifespan of PV modules. An innovative and efficient technique for improving the melting duration is the inclusion of an exterior metal foam layer in the PV/PCM system. For detailed investigations of utilizing different metal foam configurations in terms of their convective heat transfer coefficients, the present paper proposes a newly developed mathematical model for the PV/PCM–metal foam assembly that can readily be implemented with a wide range of operating condition

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Publication Date
Sun Mar 01 2020
Journal Name
Plant Archives
EVALUATION THE ACTIVITY OF SOME MEDICINAL PLANTS EXTRACTS AS PROMOTER ROOTING FOR STEM CUTTINGS OF ROSEMARY (ROSMARINUS OFFICINALIS L.)
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This study was conducted in the botanical garden, Department of biology, College of Science / Mustansiriyah University in spring season, where the starts from (15 February to 15 March, 2019). Under the natural environmental conditions in the greenhouse in order to evaluate the effectiveness of some plant extracts as a promoter for rooting the apical stem cutting of rosemary plants at different concentrations compared with the IBA growth regulator. Plant extracts are Parsley (Petroselinum crispum), Dill (Anethum graveolens) and date palm fruits (Phoenix dactylifera) were used with concentrations (0, 1.25, 2.5 g / l). The IBA concentration was (100 mg / L) with dipping time 24 hour for all treatments. The following measurements were taken aft

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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