Background: Chronic cigarette smoking is one of the major risk factors for coronary artery disease. However, it has additional cardiac adverse effects independent of coronary atherosclerosis. Patient and Methods: After informed consent and perm- ission from the review board of the hospital, 80 healthy subjects who were classified as smokers or non-smokers were included in the study. They were examined by standard echocardiography protocol which was followed by two-dimensional speckle tracking to assess the functions of the right ventricle. Results: The tricuspid annular plane systolic excursion (TAPSE) was significantly reduced in smokers as compared to non-smokers (P < 0.05). The tricuspid flow peak late diastolic velocity (A wave) was significantly higher in smokers (P < 0.05, and hence the E/A ratio was signif- icantly lower (P < 0.05). The tissue Doppler imaging examination of right ventricular free wall showed that the peak systolic velocity of right ventricular (RV) free wall (S’), and the peak early diastolic velocity of RV free wall (E’) were significantly lower in smokers when compared to the control group (P < 0.05 for both). The global longit- udinal strain (GLS) assessed by 2D-speckle tracking echo- cardiography was also significantly reduced in smokers (P < 0.05). Conclusion: This study demonstrates that chronic cigarette smoking causes alterations in long-axis systolic and diast- olic functions of right ventricle in healthy young subjects. These changes can be detected early with 2-D speckle tracking echocardiography.
In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti
... Show MoreIndustrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil
... Show MoreIn this study, several ionanofluids (INFs) were prepared in order to study their efficiency as a cooling medium at 25 °C. The two-step technique is used to prepare ionanofluid (INF) by dispersing multi-walled carbon nanotubes (MWCNTs) in two concentrations 0.5 and 1 wt% in ionic liquid (IL). Two types of ionic liquids (ILs) were used: hydrophilic represented by 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM][BF4] and hydrophobic represented by 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF6]. The thermophysical properties of the prepared INFs including thermal conductivity (TC), density and viscosity were measured experimental
We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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