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The effect of the strategy to nominate ideas on divided and selective attention and perform some volleyball skills
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Introduction: Attention is a fundamental cognitive function in sports, particularly in volleyball, where players must process multiple stimuli and make rapid decisions. Effective attentional control can enhance an athlete’s ability to react to dynamic game situations. The nomination of ideas strategy. Objective: This study aims to examine the effectiveness of the nomination of ideas strategy in enhancing divided and selective attention and its subsequent impact on volleyball skill performance. Methodology: A controlled experimental design was employed, involving volleyball players divided into an experimental group and a control group. The experimental group integrated the nomination of ideas strategy into their training sessions, while the control group followed traditional training methods. Pre- and post-tests were conducted to assess selective attention, divided attention, and volleyball skill performance, ensuring a comprehensive evaluation of cognitive and motor improvements. Discussion: The findings reveal that the experimental group exhibited significant improvements in both selective and divided attention, leading to enhanced volleyball skill performance compared to the control group. This suggests that implementing cognitive strategies such as the nomination of ideas can positively influence attentional focus, enabling athletes to process information more efficiently and execute complex skills with greater precision. Conclusion: The study underscores the value of integrating cognitive training techniques into sports practice to optimize both mental and physical performance. The nomination of ideas strategy proved to be an effective tool for improving attentional control and volleyball skills. Future research should investigate its long-term effects and potential applications across different sports and athlete populations.

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Publication Date
Fri Jun 17 2022
Journal Name
International Journal Of Health Sciences
Corrosion inhibitor of carbon steel in 3.5%NaCl solution with Schiff base compounds
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In this work, synthesized N4,N4`-bis(2, 3, 4 nitro benzylidene) biphenyi-4-4`-diamine(B1-B3) , was tested as an inhibitors in controlling the corrosion of carbon steel in NaCl 3.5% solution by using open circuit potential (OCP),at four different temperatures (293, 303, 313 and 323 K). Furthermore, the surface morphology was investigated using the Atomic force microscopy (AFM). The effect of using different Schiff bases and temperature was also investigated. Schiff bases was synthesized and characterized via using. Fourier Transform Infrared Spectroscopy (FT-IR)and Atomic Force Microscope (AFM) characterized . The experimental results shown that Schiff bases can consider as an excellent corrosion inhibitors for carbon steel in NaCl 3

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Publication Date
Mon Feb 01 2010
Journal Name
Food Chemistry
Determination of aflatoxins in animal feeds by HPLC with multifunctional column clean-up
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A reversed-phase HPLC method with fluorescence detection for the determination of the aflatoxins B1, B2, G1 and G2 in 42 animal feeds, comprising corn (16), soya bean meal (8), mixed meal (13), sunflower, wheat, canola, palm kernel, copra meals (1 each) was carried out. The samples were first extracted using acetonitrile:water (9:1), and was further cleaned-up using a multifunctional column. Optimum conditions for the extraction and chromatographic separation were investigated. By adopting an isocratic chromatographic system using a mobile phase comprising acetonitrile:methanol:water (8:27:65, v/v/v), the separation of the four aflatoxins was possible within 30 min. Recoveries for aflatoxins B1, B2, G1 and G2 were 98 ± 0.7%, 95 ± 1.0%, 94

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
A Hyperbolic Potential Field Model for Designing an Einzel Lens of Low Aberrations
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An analytical model in the form of a hyperbolic function has been suggested for the axial potential distribution of an electrostatic einzel lens. With the aid of this hyperbolic model the relative optical parameters have been computed and investigated in detail as a function of the electrodes voltage ratio for various trajectories of an accelerated charged-particles beam. The electrodes voltage ratio covered a wide range where the lens may be operated at accelerating and decelerating modes. The results have shown that the proposed hyperbolic field has the advantages of producing low aberrations under various magnification conditions and operational modes. The electrodes profile and their three-dimensional diagram have been determined whi

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Publication Date
Fri Oct 22 2021
Journal Name
Iraqi Journal Of Physics
Absorption properties of novolac-alumina-graphite mixture microwave absorbers in x-band frequencies
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Absorption properties (Attenuation coefficient, the percentage of the reflection, and the percentage of absorption) in x-band have been investigated in this paper for novolac – alumina- graphite mixture. Using novolac as the host material, the samples are prepared with alumina concentrations (5%,10%,15%,20%) and graphite concentrations (5%,10%) with thickness equal to 2.2mm .Network analyzer produced by HP-8510 was used in this work to measure the attenuation coefficient. The samples (3, 5) have good attenuation of wave with bandwidth of frequencies. The maximum of attenuation is -25dB at frequency 10.28GHZ in sample (3) which has concentrations (80%novolac,10%alumina,and 5% graphite) and -24 dB at frequency 10.56GHZ in sample (5) whic

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Estimation of kidney tumor volume in CT images using medical image segmentation techniques
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Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of an Educational Program in Enhancing Nurses’ Knowledge about Occupational Health Hazards
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Objective: To determine the effectiveness of an Educational Program in Enhancing Nurse’s Knowledge about Occupational Health Hazards at Medical City Hospitals in Baghdad City.

Methodology: The present study employed a quasi-experimental design held at Medical City Hospitals in Baghdad City. A non-probability sample (convenience sample) consisted of (60) nurse. Data were collected by using a self-report questionnaire which consisted of six parts (a) socio-demographic characteristics (b) physical hazards knowledge (c) chemical hazards knowledge (d) biological hazards knowledge (e) psychological hazards knowledge and (f) mechanical hazards knowledge. Data were analyzed using the statistical packag

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Antibacterial Activity of Electrospun Silver Nitrate /Nylon 6 Polymeric Nanofiber Water Filtration Mats
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Bacterial water pollution is a genuine general wellbeing concern since it causes various maladies. Antimicrobial nanofibers can be integrated by incorporating nanobiocides, for example, silver nanoparticles into nanofibers. Nylon 6 was dissolved in formic acid at a concentration of (25 wt. %) and tough antibacterial (AgNO3/Nylon) nanofibers were produced utilizing electrospinning system. Polymer solution was tested before accomplishing electrospinning process to acquire its surface tension, electric conductivity and viscosity, where every one of those parameters increased relatively with increasing concentration of (AgNO3) additions. SEM and EDX spectra were utilized to focus on the morphology, surface elemental mem

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Publication Date
Tue Nov 01 2016
Journal Name
Renewable Energy
Biodiesel production by esterification of oleic acid over zeolite Y prepared from kaolin
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Publication Date
Wed Dec 04 2013
Journal Name
Proceedings Of Nuclei Of Seyfert Galaxies And Qsos - Central Engine & Conditions Of Star Formation — Pos(seyfert 2012)
Are Narrow Line Seyfert 1 galaxies a special class of Active Galactic Nuclei?
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No. Due to their apparently extreme optical to X-ray properties, Narrow Line Seyfert 1s (NLSy1s) have been considered a special class of active galactic nuclei (AGN). Here, we summarize observational results from different groups to conclude that none of the characteristics that are typically used to define the NLSy1s as a distinct group – from the, nowadays called, Broad Line Seyfert 1s (BLSy1s) – is unique, nor ubiquitous of these particular sources, but shared by the whole Type 1 AGN. Historically, the NLSy1s have been distinguished from the BLSy1s by the narrow width of the broad Hb emission line. The upper limit on the full width at half maximum of this line is 2000kms−1 for NLSy1s, while in BLSy1s it can be of several thousands

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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