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Evaluating the impact of neurophysiological fatigue patterns on tactical decision-making in elite football players using wearable EEG technology
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Introduction: Elite football performance hinges on rapid tactical decision-making under physical and cognitive strain. While peripheral fatigue’s effects on motor output are well documented, the neurophysiological markers of mental fatigue and their impact on in-game decision making remain underexplored. Objective: To determine how EEG-derived central fatigue indices—frontal theta power and the theta/alpha ratio—relate to tactical decision accuracy and speed in elite football players. Methodology: Twenty male national-level footballers (age 22.4 ± 2.1 years; ≥ 5 years’ experience) completed the Yo-Yo Intermittent Recovery Test Level 1 while wearing an 8-channel dry-electrode frontal EEG headset. Frontal theta (4–7 Hz), alpha (8–12 Hz), and the theta/alpha ratio were extracted pre- and post-test. Decision-making was assessed via a validated 40-scenario video-based tactical test measuring accuracy (%) and reaction time (ms). Results: Post-fatigue, frontal theta increased by 45% and the theta/alpha ratio by 47% (both p < 0.001), while decision accuracy declined by 15% (p = 0.004) and reaction time slowed by 18% (p = 0.002). The theta/alpha ratio explained 52% of variance in decision accuracy (p < 0.001). Discussion: These findings confirm that wearable EEG markers sensitively capture central fatigue effects and directly predict tactical decision impairments, extending central fatigue theory to applied sport contexts. Conclusion: Frontal theta and the theta/alpha ratio are robust, portable biomarkers for monitoring cognitive fatigue in football, offering practical avenues for real-time performance management and optimized training or substitution strategies.

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Sun Jun 03 2012
Journal Name
Baghdad Science Journal
Evaluating the Inhibitory Activity of Apigenin Extracted from Salvia officinalis leaves on the Growth of L20B Cancer Cell Line
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The study aimed to evaluating the inhibitory activity of apigenin extracted from Salvia officinalis leaves on the growth of L20B cancer cell in vitro, and through two incubation periods; 48 and 72 hours. Accordingly, eight concentrations (1.56, 3.13, 6.25, 12.5, 25.0, 50.0, 100.0 and 200.0 micromol) of apigenin and similar concentrations of vitamin C and carbon tetrachloride (CCl4) were tested. The apigenin revealed its significant inhibitory potentials against the growth of L20B cell line, especially at the low concentrations (1.56, 3.13 and 6.25 micromol) and at 72 incubation period in comparison with vitamin C and CCl4.

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
Evaluating Arabic Language Teachers Appraisal Form in Light of the Comprehensive Quality Standards
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The current research aims to evaluate the appraisal form for Arabic language teachers in light of comprehensive quality standards by designing standards for the competencies of primary school teacher in accordance with comprehensive quality requirements. The researcher adopted the descriptive approach. The research community included the Arabic language supervisors in the Education Directorates of Diyala Provincial and Baghdad. The research sample consisted of (14) supervisors from the Diyala Provincial Department of Education and the First Rusafa Education Directorate in Baghdad Governorate by (8) supervisors and (6) Supervisors respectively specializing in Arabic language. As for the research tool, questionnaire prepared by the researc

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Publication Date
Sun May 01 2022
Journal Name
Expert Systems With Applications
Novel large scale brain network models for EEG epileptic pattern generations
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Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different

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Publication Date
Tue Apr 11 2023
Journal Name
Sensors
EEG Signal Complexity Measurements to Enhance BCI-Based Stroke Patients’ Rehabilitation
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The second leading cause of death and one of the most common causes of disability in the world is stroke. Researchers have found that brain–computer interface (BCI) techniques can result in better stroke patient rehabilitation. This study used the proposed motor imagery (MI) framework to analyze the electroencephalogram (EEG) dataset from eight subjects in order to enhance the MI-based BCI systems for stroke patients. The preprocessing portion of the framework comprises the use of conventional filters and the independent component analysis (ICA) denoising approach. Fractal dimension (FD) and Hurst exponent (Hur) were then calculated as complexity features, and Tsallis entropy (TsEn) and dispersion entropy (DispEn) were assessed as

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Publication Date
Tue Jul 19 2022
Journal Name
Res Militaris
Urban Geomorphology and Its Impact on Determining the Trends of Urban Expansion in The City of Kut and Its Future Expectations Using Geographic Information Systems
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Geomorphology is concerned with the topographic units that make up the Earth's surface. These take many forms, such as mountains and rivers, and include many dangers such as landslides, landslides and erosion. Many studies appeared in this field to analyze its effects and risks resulting from it, including urban studies, to determine the trends of optimal urban expansion and its geomorphological interactions. The results showed that the city of Kut originated and expanded near the course of the Tigris River and its branches, and it suffers from unbalanced urban expansion, due to the high rate of population growth, and overcrowding in housing units with the growth of urban land uses in it, which prompted the city to extend horizontally and v

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Publication Date
Tue Jun 30 2009
Journal Name
Al-kindy College Medical Journal
The impact of advancing age on total serum IgE in asthmatic patient
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Abstract

The current study was conducted to assess the effect of advancing age on total serum IgE level in asthmatic patients. To this purpose, 90 asthmatic patients and 30 healthy individuals ( control group ) were enrolled. Asthmatic patients were categorized into four groups. Group A consisted of asthmatic patients (9) whose age was more than 20 and up to 30 y. Group B contained asthmatics (13) of age more than 30 and up to 40 y. Group C comprised those (23) of more than 40 and up to 50 y. Group D consisted asthmatic patients (45) of age more than 50 y. Total serum IgE level significantly changed in group D patients when compared with those of

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Publication Date
Sun Jun 02 2024
Journal Name
Stallion Journal For Multidisciplinary Associated Research Studies
Measuring The Impact of Water Scarcity on Agricultural Economic Development in Iraq
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Water provision is sensitive to climate change, and agricultural production and food supply are sensitive to water availability. Water scarcity affects food security and agricultural economic development through changes in agricultural production and changes in the composition of produced goods. Recent droughts also led to a decrease in the volume of water allocated to agriculture, which led to a decrease in total agricultural production and exports, and this has subsequent impacts on food security and economic development. The research aimed to measure the impact of water scarcity on agricultural economic development for the period 1990-2022. The research included three behavioral equations with three endogenous variables: the cult

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Publication Date
Wed Jun 05 2024
Journal Name
International Journal Of Engineering Pedagogy (ijep)
The Impact of Artificial Intelligence on Computational Thinking in Education at University
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This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b

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Publication Date
Tue Apr 01 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
The Impact of Feature Importance on Spoofing Attack Detection in IoT Environment
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The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

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