ABSTRACT
The ambiguous information in multi-criteria decision-making (MCDM) and the vagueness of decision-makers for qualitative judgments necessitate accurate tools to overcome uncertainties and generate reliable solutions. As one of the latest and most powerful MCDM methods for obtaining criteria weight, the best-worst method (BWM) has been developed. Compared to other MCDM methods, such as the analytic hierarchy process, the BWM requires fewer pairwise comparisons and produces more consistent results. Consequently, the main objective of this study is to develop an extension of BWM using spherical fuzzy sets (SFS) to address MCDM problems under uncertain conditions. Hesitancy, non-membership, and membership degrees are three-dimensional functions included in the SFS. The presence of three defined degrees allows decision-makers to express their judgments more accurately. An optimization model based on nonlinear constraints is used to determine optimal spherical fuzzy weight coefficients (SF-BWM). Additionally, a consistency ratio is proposed for the SF-BWM to assess the reliability of the proposed method in comparison to other versions of BWM. SF-BWM is examined using two numerical decision-making problems. The results show that the proposed method based on the SF-BWM provided the criteria weights with the same priority as the BWM and fuzzy BWM. However, there are differences in the criteria weight values based on the SF-BWM that indicate the accuracy and reliability of the obtained results. The main advantage of using SF-BWM is providing a better consistency ratio. Based on the comparative analysis, the consistency ratio obtained for SF-BWM is threefold better than the BWM and fuzzy BWM methods, which leads to more accurate results than BWM and fuzzy BWM.
ABSTRACT
Diabetes Mellitus (DM) can damage the function of metabolic tissues, including the liver. Liver macrophages are the first responders to tissue damage or exercise. We sought to determine whether eight weeks of interval training (HIIT & MIIT) protect against diabetes-induced modulation of hepatic CD86 and CD206 expression associated with the amelioration of insulin resistance and inflammation in rats. Thirty rats were divided into six groups, including a control group, MIIT, HIIT, DM, DM + MIIT, and DM + HIIT (n = 5 in each group). Diabetes was induced using a combination of a high-fat diet (HFD) and STZ. Wistar rats in the exercise groups were subjected to moderate and high-intensity interval training for eight weeks. After sample collection, liver tissue was removed and weighed. Serum levels of TNFα, IL-6, TGFß, and IL-10 were measured by ELISA. Protein expression of the immune markers CD86 and CD206 in liver tissue was determined by immunohistochemical staining. Induction of diabetes increased glycemic indices, insulin resistance, and liver injury enzymes, especially in DM and DM + HIIT groups (p < 0.05). Moreover, diabetic groups showed an increase in liver CD86 protein expression, an increase in TNFα, IL-6, and TGFß serum levels, and a decrease in liver CD206 and serum IL-10 (p < 0.05). Doing exercise while being diabetic, especially MIIT, significantly reversed the aforementioned factors and reduced insulin resistance (p < 0.05), except IL-10). We concluded that performing exercise training specially MIIT by decreasing CD86 and increasing CD206 in the liver, followed by decreasing pro-inflammatory factors (TNFα, IL-6) caused the regulation of liver enzymes and insulin resistance in diabetic rats. Therefore, it seems that exercise training by regulating macrophage markers CD86 and CD206 can reduce damage to the insulin-signaling pathway by reducing pro-inflammatory cytokines.
