zahra fathollahi
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Despite other modes of transportation, trains move just along one dimension. However, trains inevitably change their track or move to the opposite track in railway stations and ports using switch systems. Switches are vital for better operation and seamless movement of trains. Furthermore, they are crucial for the safety of movement in tracks due to high derailment potentials at switches; therefore, all parts of switches need to be continuously monitored. An increasing number of accidents in railway systems is highly dependent on switch performance. According to the Islamic Republic of Iran Railways, 90 percent of railway accidents in Tehran stations occur on switches, from which 25 percent happen due to switch defects. Therefore, condition evaluation of switches is of significant importance. Research studies have not been sufficiently conducted on automated condition evaluation of switches. This paper aims to develop a robust automated approach to evaluate switch conditions to be able to measure switch defects. Having taken some pictures from various switches with fixed angles and distance from rails, an image processing technique is applied to determine defects. The first step of image processing is to preprocess the images to increase their quality. The second step is to indicate the type and severity of defects using different algorithms. A Graphical User Interface (GUI) is developed to develop a user-friendly tool to be able to load images, preprocess the images, measure defects, and report the health condition of switches. Finally, the outcomes are validated by applying ground truth, which ends up with high accuracy of approximation of 87 percent.Keywords: Fatality Severity, Risk Map, Classification, Decision Tree algorithms
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Background
Coronary artery bypass surgery is a common method for coronary artery disease (CAD) treatment, which in turn activates pro-inflammatory biomarkers such as Interleukin-6 (IL-6) and high sensitivity C-reaction protein (hs-CRP).
ObjectivesThe present study aimed to investigate the effects of 8 weeks Yoga and cardiac rehabilitation training on IL-6 and hs-CRP after coronary artery bypass surgery.
MethodsThe subjects of this randomized control trial study consist of 20 male patients (40 - 75 years old) who experienced coronary artery bypass surgery. They were randomly assigned in cardiac rehabilitation training group (CRT, n = 10) and combined training group (Yoga-cardiac rehabilitation) (YCRT, n = 10). Plasma levels of IL-6 and hs-CRP were assessed at baseline and end of the study. The CRT group performed cardiac rehabilitation program with 60% - 85% of maximum heart rate for 1 hour three days a week. The YCRT group performed one session in between cardiac rehabilitation and Yoga training for 1 hour three days in a week. All subjects completed training sessions at the cardiac rehabilitation center of Shahid Rajaie Cardiovascular, Medical and Research Center in Tehran for 8 weeks. SPSS software was used for analysis. Covariance analysis was used to compare groups (P ≤ 0.05).
ResultsDespite a small decline in IL-6 (10.90 to 8.77 in CRT group, 9.87 to 9.40 in YCRT group (and hs-CRP (2.58 to 2.00 in CRT group, 3.67 to 3.13 in YCRT group), there weren’t any significant differences in IL-6 (P = 0.160) and hs-CRP (P = 0.234) levels between two groups.
ConclusionsIt could be proposed to add Yoga training to cardiac rehabilitation program after coronary artery bypass surgery.
Keywords: Interlukin-6, Yoga, Coronary Artery Bypass Surgery, Cardiac Rehabilitation Training, C-Reaction Protein
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