Showing 4 results for Mirsalim
Volume 1, Issue 3 (9-2016)
Abstract
Background: low back pain is a common health problem that has many consequences, including disability and absence from work. This study aimed to determine the prevalence of Low Back Pain among women referred to Quds clinic in Tehran, Iran. Material and Methods: This cross-sectional study was conducted on women referred to Quds clinic, in East of Tehran. A total of 100 patients were studied over a period of one month. Two questionnaires were used for this study. The first one contains general information such as age, height, weight, Body Mass Index (BMI), education level, smoking and physical activity. Also the participants were asked whether over the past two weeks had LBP or not and if yes their pain severity was measured through Visual Analogue Scale (VAS). The second questionnaire was Roland-Morris Disability Questionnaire (RDQ) that was only available to persons that expressed a report of pain over the past two weeks. Data were analyzed using SPSS. Results: 52 patients (52%) of the samples reported LBP. Also significant relationship between LBP and functional disability was shown (P < 0.05). More than 48% of patients who had LBP were physically low performance. Age, weight, body mass index, physical activity hours, number of pregnancy and parity and level of education were significantly associated with the severity of LBP (P < 0.05) whereas height, employment status and cigarette smoking were not significantly associated with LBP (P > 0.05). Conclusion: The results of this study showed individual suffering from LBP were more likely to suffer from disability.
Volume 8, Issue 4 (Fall 2020)
Abstract
Aims: Depression during pregnancy has a significant impact on both mother and fetus. This study aimed to determine the frequency of depression and associated factors among primigravid women.
Materials & Methods: This was a cross-sectional study involving 255 pregnant women attending a hospital in Tehran from October 2017 to February 2018. A demographic and clinical questionnaire, the Postpartum Depression Literacy Scale (PoDLiS) and the Edinburgh Postnatal Depression Scale (EPDS), given to a convenient sample of primigravid women attending the antenatal clinic, were completed. chi-square test, t-test and logistic regression analysis were used to analyze the data and SPSS version 22.0 was used for its analysis (p<0.05).
Findings: The prevalence of depression during pregnancy was 17.3% (n=255). The results of the t-test and chi-square test showed that depression was significantly associated with age (p=0.008), marriage age (p=0.018), economic status (p=0.050), family history of depression (p<0.001), marital satisfaction (p<0.001), ability to recognize postpartum depression (p=0.019) and attitudes about postpartum depression (p=0.042). Further analysis by logistic regression analysis revealed that family history of depression [AOR=7.89, 95% CI, p=0.002] and less satisfaction with husband [AOR=3.24, 95% CI, p=0.021] was significantly associated with depression.
Conclusion: The findings showed that a high percentage of women were depressed. Also, having a family history of depression and less satisfied with the husband were the strongest factors related to depression. It seems that educational interventions and counseling may need to be conducted on high-risk mothers to promote their mental health status.
Arman Hamidi, Seyed Mostafa Mirsalim, Barat Ghobadian, Amirhossein Parivar, Saeed Abdolmaleki,
Volume 15, Issue 5 (7-2015)
Abstract
Biodiesel is a renewable and sustainable alternative fuel that is derived from vegetable oils and animal fats. In this paper an experimental investigation is conducted to evaluate the use of soybean oil methyl ester (biodiesel) in the diesel fuel at blend ratios of B0, B2, B5 and B10. In this study, the performance and emissions characteristics of conventional diesel fuel and biodiesel fuel blends were compared. The tests were performed at steady-state conditions in a direct injection diesel engine with 90 kW power that was equipped with EGR and with no modification of calibration. The experimental results of brake-specific fuel consumption (BSFC), torque and exhaust temperature as well as carbon dioxide (CO2), smoke, nitrogen oxide (NOx), carbon monoxide (CO) and unburned hydrocarbon (UHC) emissions were presented and discussed. The results of engine performance parameters at different conditions (different load and engine speed) showed that a negligible loss of engine power and a significant increase in brake specific fuel consumption due to lower heating value of biodiesel. Smoke, CO and HC emissions were decreased by increasing blends of soybean oil as compared to pure diesel. However the increase in engine NOx and CO2 emissions were observed with the increase of biodiesel percentage in the blended fuel.
Meghdad Khazaee, Ahmad Banakar, Barat Ghobadian, Mostafa Mirsalim, Saeid Minaei, Seyed Mohammad Jafari, Peyman Sharghi,
Volume 16, Issue 3 (5-2016)
Abstract
In this research, an intelligent method is introduced for remaining useful life prediction of an internal combustion engine timing belt based on its vibrational signals. For this goal, an accelerated durability test for timing belt was designed and performed based on high temperature and high pre tension. Then, the durability test was began and vibration signals of timing belt were captures using a vibrational displacement meter laser device. Three feature functions, namely, Energy, Standard deviation and kurtosis were extracted from vibration signals of timing belt in healthy and faulty conditions and timing belt failure threshold was determined. The Artificial Neural Network (ANN) was used for prediction and monitoring vibrational behavior of timing belt. Finally, the ANN method based on Energy, Standard deviation and kurtosis features of vibration signals was predicted timing belt remaining useful life with accuracy of 98%, 98% and 97%, respectively. The correlation factor (R2) of vibration time series prediction by ANN and based on Energy, Standard deviation and kurtosis features of vibration signals were determined as 0.87, 0.91 and 87, respectively. Also, Root Mean Square Error (RMSE) of ANN based on Energy, Standard deviation and kurtosis features of vibration signals were calculated as 3.6%, 5.4% and 5.6%, respectively.
