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It is well accepted that diabetes is associated with heart diseases and hyperlipidemia as a risk factor. In traditional medicines, some herbs such as Aloe vera seem to be effective in controlling diabetes. Owing to lack of human studies, this study aims to examine the effect of Aloe vera consumption on fasting blood sugar (FBS), lipid profiles and body composition in type 2 diabetic patients.

This double-blind, placebo-controlled trial study was conducted in 2019, in Shiraz, Iran. A total of 56 diabetic subjects were randomized by block randomization to receive a daily supplement of 1,000 mg Aloe vera powder capsules (n = 28) or placebo (n = 28) for eight weeks. At baseline and after eight weeks of treatment, dietary intake and physical activity were assessed by three-day food recall and international physical activity questionnaire. Meanwhile, after an overnight fasting, FBS and lipid profiles were measured. Blood pressure and anthropometric parameters were assessed in the beginning and the end of the study. Independent t-tests were used for between-group analysis and paired t-tests for within-group analysis.

After intervention, weight, body mass index and waist circumference significantly decreased in comparison to the placebo group (p-value: < 0.001, 0.001 and 0.02). Although, FBS, total triglyceride and systolic blood pressure decreased significantly (p-value: 0.03, 0.001 and 0.01), no change has been seen in low density lipoprotein, high density lipoprotein and total cholesterol blood level and diastolic blood pressure.

The limitations of this study are the short study duration and lack of Aloe vera powder’s ingredient analysis.

This study is one of few human studies investigating the effect of Aloe vera on metabolic syndrome’s indices in diabetic patients. Because pharmacological therapy is tough, not comfort and correlated with potential adverse drug interactions, it is important to find an alternative or complementary measure to aid the diabetic patients. This study shows that Aloe vera has positive effect on body weight and blood sugar.

Proper planning for the response phase of humanitarian relief can significantly prevent many financial and human losses. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of injured people, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified injured people.

The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized injured people in the network. Besides, the total transportation activities of different types of vehicles are considered as another objective function. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize transportation activities as the second objective function while maintaining the optimality of the first objective function.

The performances of the proposed model were analyzed in different cases and its robust approach for different problems was shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.

The proposed methodology can be applied to find the best response plan for all crises.

In this paper, we have tried to use a multi-objective optimization model to guide and correct response programs to deal with the occurred crisis. This is important because it can help emergency managers to improve their plans.