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Backgrounds: A novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now spread to all countries of the world, including Iran. Although anti-SARS-CoV-2 antibodies may be identified in patients using immunological methods with sufficient sensitivity and specificity, the conclusive diagnosis of the disease is made using the molecular RT-PCR method. A population-based seroepidemiological survey was conducted to quantify the proportion of the exposed population with SARS-CoV-2 antibodies and evaluate whether the antibodies are a marker of total or partial immunity compared to the population that remains susceptible to the virus.
Material & Methods: This cross-sectional study was conducted to investigate the seroprevalence of COVID-19 in Valiasr, Sajad, and Ghaem hospitals in Tehran, the capital of Iran, from April to the end of October 2020. Clotted and heparinized blood specimens (2mL) were collected from the patients. The serum and plasma were separated and stored at −80 °C until use. Anti-SARS-CoV-2 IgG and IgM antibodies were examined in the serum samples of 1375 in-patients admitted to the hospitals using ELISA kits. The obtained data were analyzed using SPSS software Ver.22.0 by employing statistical tests such as Chi-square and Fisher’s exact tests. A p-value <.05 was considered as significant.
Findings: In total, 1375 participants were enrolled in this study, and SARS‐CoV‐2 antibodies were detected in 291 patients using IgM‐IgG antibody assay. Among the seropositive patients studied, 187 were male (64.3%), and 104 were female (35.7%) (p<.05). The mean age of the patients was 49±8.4 years; the majority of whom (27%) were in the age group of 31-40 years. Also, the lowest frequency of infected cases was related to the age group of 1-10 years (p <.05). The seroprevalence of SARS‐CoV‐2 IgM or IgG antibodies was determined to be 21.2%. Diabetes mellitus was the most common underlying disease among SARS‐CoV‐2 patients [p=.05; Odd Ratio=1.61(0.90-2.91)].
Conclusion: The use of conventional serological assays, such as the enzyme-linked immunoassay (ELISA), for detecting specific IgM and IgG antibodies in SARS‐CoV‐2 patients has a high-throughput advantage while minimizing false-negative results obtained using the RT-PCR method. In this study, the seroprevalence of SARS-CoV-2 antibodies was determined to be 21%. Control of diabetes, among other influential factors, plays an important role in the management and control of COVID-19.

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Lipid solutes in blood such as Low-Density Lipoproteins (LDLs) are the major cause of most cardiovascular diseases. Increase of fatty materials in the blood flow endanger personal healthiness and enhance possibility of cardio and cerebrovascular infarctions. In order to provide nutritional blood for different tissues, heart sends pulsatile flow with high pressure to the circulatory system such that LDL particles spread over the entire body. Contraction and expansion of the heart create pulsatile flow that affect blood hemodynamics and LDL mass transfer in vessels. In this paper, effects of the pulsatile flow on LDL mass transport in a multilayered artery with atherosclerotic plaques are investigated numerically. In order to apply pulsatile flow in the artery, a set of specific-person flow and pressure pulses, which are resulted from the ultrasound method, are employed directly. Results indicate that pulsatile flow increases LDL concentration both on the luminal surface and across arterial layers and produces interesting periodic concentration patterns in these regions. Moreover, pulsatile effect intensifies remarkable reversal flow right at post-stenotic regions of plaques locations, where the flow is recirculated naturally, and lowers LDL accumulation.

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Rupture of abdominal aortic aneurysm is a result of the relatively complex hemodynamic forces that are exerted along the arterial walls. In the present study, numerical simulations of blood flow in a patient-specific model are performed employing the fluid-structure interaction method. The aneurysm model is reconstructed from CT angiographic scans from a patient diagnosed with abdominal aortic aneurysm, which also contains an intraluminal thrombus. Both isotropic and anisotropic material models are considered for arterial wall. In particular, the effects of arterial wall heterogeneity with respect to its material model are examined. Results indicate that unlike the computational solid stress method, which exerts the peak systolic pressure to the inner surface of the arterial wall, FSI method predicts the time of peak wall stress between the times of peak systolic velocity and pressure. Results also indicate that the isotropic material model with uniform wall thickness as compare to the anisotropic material model with variable wall thickness significantly underestimate wall stresses. The peak wall stress in all models are located somewhere on the posterior wall near the maximum diameter of AAA and the extent of the region of higher wall stresses are larger in models with variable wall thickness as compared to the uniform wall thickness. This fact along with the higher values of wall stress for variable wall thickness models, increase the rupture risk of the variable wall thickness model as compared to the models with uniform wall thickness.

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The aim of this study was to determine the kinetics, effective moisture diffusivity, activation energy, specific energy consumption, and also predict the moisture content of white mulberry during the drying process with microwave-hot air dryer using mathematical models, Artificial Neural Networks (ANN) and Neuro-Fuzzy Inference System (ANFIS). Drying process was accomplished in three temperature levels (40, 55, and 70°C), three inlet air velocity levels (0.5, 1 and 1.5 m/s) and three microwave power levels (270, 450 and 630 W). To estimate the moisture ratio of white mulberry, 10 mathematical models, ANN and ANFIS were used to fit the experimental data of thin-layer drying. The results showed, the maximum and minimum effective moisture diffusivity during drying was calculated 3.56×10-9 and 3.86×10-10 m2/s, respectively. Also, the minimum and maximum effective moisture diffusivity during drying was achieved 48.54 and 1380.88 Mj/kg, respectively. Among the mathematical models under study, the Page model was the best model for describing the behavior of the thin layer of white mulberry drying. The mean square error (MSE) values for the mathematical models, ANN, and ANFIS were 0.00059, 0.0052 and 0.0044, respectively. Therefore, the ANFIS model with the highest Correlation Coefficient (R2=0.99995), the least percentage of mean relative error (ε=1.84) and mean square error (MSE=0.0044) were used to evaluate the moisture ratio in comparison with other methods implemented in this research Selected as the best model

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Attention to sexual harassment at workplace is a new phenomenon which has been the focus of researchers since the 1970s. There are many models and theories to explain sexual causes, most of which have socio-cultural, biological and personality roots,as well as organizational and cognitive origins. Recently, a multi-factor model has combined all factors to investigate this phenomenon. In this article, we have conducted in-depth interviews with 31 sexual harassment victims (with age groups ranging from 23 to 47). Applying the Snowball Method, the study found what the members of the focus group described their experiences and it analyzed the sexual harassment based on patterns and theories. In response to causes of sexual harassment, the findings of this study show that biological, social, cultural, organizational, and cognitive factors are effective but not sufficient in themselves and a multifactorial pattern can be used to explain the influential variables of this phenomenon.
 

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Sexual harassment at workplace is a phenomenon that has many implications for women. Also, organizations and other employees are not immune to the devastating consequences of sexual harassment against women. Victimized women respond to harassment differently, such as silence, tolerance, bullying and aggression, leaving the workplace and even positive responding to sexual demands. In this article, in-depth interviews with victims will address the reactions and effects of harassment. We have also used the same tool to analyze the consequences of sexual harassment in organizations. The main questions of the study were the type of victim response to the harasser, the impact of the harassment on the victim, and the organization or other staff. The findings are obtained from interpretation and classification of in-depth and semi-structured interviews with 25 women in 23-47 age groups. They were selected from those with bachelor and doctoral degrees and working in government and private sectors. In order to obtain data, 5 open-ended and semi-structured interviews were conducted with 5 managers and administrative and financial assistants of public and private companies. The results of qualitative content analysis of interviews with victims, focused group, and the organizational management panel showed that women's responses differed by education, age, public or workplace privacy, from fear and silence to aggressive responses and complaints. And even retreats toward harassers were different. From individual perspective, harassment causes depression, morbid fears, prolonged anxiety, pessimism and suspicion, physical illness, labeling and social isolation. From an organizational point of view, there is virtually no protection mechanism for victims, which results in the abandonment of work, unwanted displacements, harassing dismissals, and even harassment and reduced organizational productivity.