Both traditional and fuzzy regression analyses have demonstrated the significant characteristics of the least-squares methodology as a method for parameter estimation.} The presence of outliers in the sample and/or minor variations in the dataset might impact the behaviour and characteristics of the least-squares estimators (LSE)‎. ‎In contrast‎, ‎robust approaches provide estimators of the parameters that are resilient to the aforementioned unfavourable effects‎. ‎This study aims to expand upon the Theil-Sen estimator in fuzzy regression analysis‎, ‎with the objective of obtaining consistent findings even when outliers are present‎. ‎\rd{ We demonstrate the effectiveness of the suggested technique through simulation experiments and real-world examples‎, ‎comparing it to commonly used fuzzy regression models‎. ‎The applicative examples are based on hydrology and atmospheric environment datasets‎. ‎We also show the sensitivity analysis of the estimated parameters using a Monte-Carlo simulation study‎, ‎demonstrating the effectiveness of the suggested estimators in comparison to other established approaches in the field of fuzzy regression analysis‎. ‎The results showed that the Theil-Sen estimator (TSE) is very effective in cases where there are outliers‎, ‎and the calculation error is smaller compared to other methods.

Although hepatotropic viruses such as hepatitis B virus (HBV) and hepatitis C virus (HCV) are well-identified viral agents for the development of hepatitis, infection with some other viruses may lead to varying degrees of liver injury. Moreover, the hepatic pathogenicity of a few viral agents still remains to be determined. In recent years, viral agents such as TTV and SEN virus with possible hepatic pathogenicity have been introduced. SEN virus has been reported with different rates of prevalence in high-risk groups such as dialysis patients, and low-risk groups such as blood donors. Identification of the SEN virus as a possible etiological agent of parenteral transmission hepatitis led to a major concern about the possibility of its role in liver diseases in hemodialysis patients as well as in renal transplant recipients. This manuscript provides an updated integrative review on SEN virus from virological aspect as well as epidemiologic and diagnostic medicine. Moreover, its role in liver diseases considering the co-infection with other hepatotropic viruses has also been reviewed.

Background: SEN virus is a blood-borne, single-stranded, nonenveloped DNA virus. Two of its strains (D and H), appear to be associated with non-A-to-E hepatitis more frequently than the others, although it is not clear whether this observation has any significance. The prevalence of SEN virus in otherwise healthy individuals, including blood donors, differs markedly by geographic region. In this study, an investigation to evaluate the prevalence of SEN virus strains among blood donors in Tehran was carried out.Methods: Sera of 260 blood donors who were negative for hepatitis B surface antigen (HBsAg) and third-generation hepatitis C virus antibody (anti-HCV) were tested for SEN virus-D and -H DNA. DNA was extracted from plasma of 260 blood donors and amplified by semi- nested polymerase chain reaction.Results: SEN virus-D viremia was detected in four (1.5%) of the 260 blood donors (95% confidence interval (CI), 0.0 – 3%). SEN virus-H viremia was detected in 47 (18.08 %) of the 260 blood donors (95% CI, 13.4 – 22.8%). Both SEN virus-D and SEN virus-H viremia were detected in nine (3.4%) of the 260 blood donors (95% CI, 1.2 – 5.7%). SEN virus-D or SEN virus-H viremia was identified in 60 (23.08%) of the 260 blood donors (95% CI, 18.08 – 28.08%).Conclusion: Out of the 260 blood donors, 60 (23%) were infected by SEN virus-D/H. The prevalence of SEN virus-H is more than SEN virus-D. Our results also showed that the high prevalence of SEN virus in healthy blood donors with no history of blood transfusion may attribute to the transmission modes other than parenteral transmission.