Fencing is characterized by rapid and sudden changes that require speed in decision-making and motor responses. In addition, it requires high sensorimotor awareness and strong coordination between leg, arm, and eye movements. In the current study, the researchers used cognitive coordination response speed exercises and physical and skill exercises in order to develop performance in the time counterattack. The aim of the study is to identify the effect of cognitive coordination response speed exercises on the performance of the time counterattack of female foil fencers. An experimental method was used on the female fencing team players at the College of Physical Education and Sports Sciences for Women/University of Baghdad in the sports season (2025-2026). The sample consisted of (12) players. They were divided equally into an experimental group (practiced cognitive coordination response speed exercises) and a control group (practiced traditional exercises). The post-test results showed that the experimental group, which practiced cognitive coordination response speed exercises, outperformed the control group with a mean score of (9.5) compared to a lower mean score of (7) for the control group. The calculated t-value was (7.31) at a significance level of less than (0.05) regarding the experimental group. The results proved that the cognitive coordination response speed exercises were effective in developing time counterattack performance. Therefore, the study recommended conducting studies based on cognitive coordination response speed exercises due to their importance in developing time counterattack performance. The current study fulfills the third Sustainable Development Goal (good health and well-being).
A new Azo‐Schiff base ligand L was prepared by reaction of m‐hydroxy benzoic acid with (Schiff base B) of 3‐[2‐(1H–indol‐3‐yl)‐ethylimino]‐1.5‐dimethyl‐2‐phenyl‐2,3‐dihydro‐1H‐pyrazol‐4‐ylamine. This synthesized ligand was used for complexation with different metal ions like Ni(II), Co(II), Pd(II) and Pt(IV) by using a molar ratio of ligand: metal as 1:1. Resulted compounds were characterized by NMR (1H and 13C), UV–vis spectroscopy, TGA, FT‐IR, MS, elemental analysis, magnetic moment and molar conductivity studies. The activation thermodynamic parameters, such as ΔE*, ΔH*, ΔS*, ΔG*and
... Show MoreMR Younus, 1998
Small ring heterocycles containing nitrogen and sulfur have been under investigation for a long time because of their important medicinal properties. Among the wide range of heterocycles explored to develop pharmaceutically important molecules, thiadiazoles had played an important role in medicinal chemistry. A survey of literature had shown that compounds having thiadiazole nucleus possess a broad range of biological activities such as anti-inflammatory (1), antibacterial (2), and antifungal activities (3). Thiazine-4-one and their derivatives are import classes of compounds in organic and medicinal chemistry. The thiazine-4-one ring system is a core structure in various synthetic pharmaceutical agents, displaying a broad spectrum of biolo
... Show MoreIn this study, condensation polymerization was used to synthesize a number of novel liquid crystal polymers with 1,3,4-oxadiazole rings based on melamine. The new synthesized polymers were characterized by Fourier transform infrared (FTIR) and proton nuclear magnetic resonance (1HNMR) spectroscopy. Differential scanning calorimetry (DSC) and optical polarization microscopy (OPM) were used to investigate their liquid crystalline properties. The results demonstrated that throughout a wide temperature range, most of the polymers exhibited columnar (CohX) and nematic (N) liquid crystalline phases.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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