Based on the streamer growth model, the streamer discharge propagation was simulated in aid of finite element technique. That was done within two non- mixed dielectric liquids (Normal-Hexane and Acetone) located between two electrodes in pin - plane configuration. The output results show that, the path of the streamer was affected by the interface between the two liquids; the streamer path crosses this interface under some conditions such as the permittivity of the liquids and the distance between this interface and the tip of the pin. Under other conditions, the streamer path grows along the interface. The results were assisted by the development of the potential and the electric field distributions with the growth of the streamer propagation within the configuration
A theoretical and protection study was conducted of the corrosion behavior of carbon steel surface with different concentrations of the derivative (Quinolin-2-one), namly (1-Amino-4,7-dimethyl-6-nitro-1H-quinolin-2-one (ADNQ2O)). Theoretically, Density Functional Theory (DFT) of B3LYP/ 6-311++G (2d, 2p) level was used to calculate the optimized geometry, physical properties and chemical inhibition parameters, with the local reactivity to predict both the reactive centers and to locate the possible sites of nucleophilic and electrophilic attacks, in vacuum, and in two solvents (DMSO and H2O), all at the equilibrium geometry. Experimentally, the inhibition efficiencies (%IE) in the saline solution (of 3.5%) NaCl were studied using potentiomet
... Show MorePlatinum nanoparticles (PtNPs) exhibit promising biomedical properties, but concerns about biocompatibility and synthesis-related toxicity remain. This study aimed to develop eco-friendly PtNPs using aqueous broccoli extract as a natural reducing and stabilizing agent, and to assess their multifunctional biomedical potential. PtNPs were synthesized through sonochemical reduction of K₂PtCl₆ in broccoli extract, followed by purification and comprehensive physicochemical characterization. UV–Vis confirmed nanoparticle formation at 253 nm, while XRD and FTIR analyses verified the crystalline FCC structure and phytochemical capping. TEM revealed mainly spherical PtNPs with an average core size of 14.83 ± 7.67 nm. Conversely, DLS showe
... Show MoreSocial determinants of health (SDH) profoundly influence diabetes outcomes; nevertheless, their impact on the Iraqi diabetic population remains under researched. The objectives of this study were To investigate the relationship between particular social determinants of health (SDH) variables namely food and housing insecurity, social support, income, and education and clinical outcomes, including HbA1c levels, medication adherence, and patient satisfaction among Iraqi diabetic patients. A cross-sectional study involving 212 diabetic patients in Iraq was conducted. Participants attending a healthcare facility in Iraq filled out validated questionnaires regarding social determinants of health, medication adherence, and satisfaction. HbA1c rea
... Show MoreThe aim of this study was to assess the effectiveness of listening to music or Quran in reducing cancer patients’ anxiety before chemotherapy administration. Reducing anxiety in people with cancer, prior to chemotherapy administration, is a crucial goal in nursing care.
An experimental comparative study was conducted.
A simple randomization sampling method was applied. Two hundred thirty‐eight people with cancer who underwent chemotherapy were participated. They are assigned as Quran, music and control groups.
Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte
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