Measurement of the Thermic Effect of Food in a Chinese Mixed Diet in Young People.

Objective: To determine the thermic effect of food (TEF) in a Chinese mixed diet in young people. Methods: During the study, the participants were weighed and examined for body composition every morning. The total energy expenditure (TEE) of the participants was measured by the doubly labeled water method for 7 days, and during this period, basal energy expenditure was measured by indirect calorimetry and physical activity energy expenditure was measured by an accelerometer. The value obtained by subtracting basal energy expenditure and physical activity energy expenditure from TEE was used to calculate TEF. Results: Twenty healthy young students (18-30 years; 10 male) participated in the study. The energy intake of the participants was not significantly different from the Chinese Dietary Reference Intake of energy ( P > 0.05). The percentage of energy from protein, fat and carbohydrate were all in the normal range. The intakes of fruits, milk and dietary fiber of the participants were significantly lower than those in the Chinese Dietary Guidelines ( P < 0.05). There was no significant difference in the body weight of the participants during the experiment ( P > 0.05). When adjusted for body weight, there was no significant difference in either TEE or basal energy expenditure between the male and female participants ( P > 0.05). In addition, there was no significant difference in physical activity energy expenditure and TEF between the male and female participants ( P > 0.05). The percentage of TEF in TEE was 8.73%. Conclusion: The percentage of TEF in TEE in a Chinese mixed diet in young people was significantly lower than 10% ( P < 0.001). A value of 10% is usually considered to be the TEF in mixed diets as a percentage of TEE.

An integrated multi-criteria decision making approach with linguistic hesitant fuzzy sets for E-learning website evaluation and selection.

Network teaching has been widely developed under the influence of COVID-19 pandemic to guarantee the implementation of teaching plans and protect the learning rights of students. Selecting a particular website for network teaching can directly affects end users' performance and promote network teaching quality. Normally, e-learning website selection can be considered as a complex multi-criteria decision making (MCDM) problem, and experts' evaluations over the performance of e-learning websites are often imprecise and fuzzy due to the subjective nature of human thinking. In this article, we propose a new integrated MCDM approach on the basis of linguistic hesitant fuzzy sets (LHFSs) and the TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method to evaluate and select the best e-learning website for network teaching. This introduced method deals with the linguistic assessments of experts based on the LHFSs, determines the weights of evaluation criteria with the best-worst method (BWM), and acquires the ranking of e-learning websites utilizing an extended TODIM method. The applicability and superiority of the presented linguistic hesitant fuzzy TODIM (LHF-TODIM) approach are demonstrated through a realistic e-learning website selection example. Results show that the LHF-TODIM model being proposed is more practical and effective for solving the e-learning website selection problem under vague and uncertain linguistic environment.