Role of caloric content on gastric emptying in humans

[EN] 1. This study examined the effects of caloric content (caloric density and the nature of calories) on the rate of gastric emptying using the double-sampling gastric aspiration technique. Four test meals of 600 ml (glucose, 0.1 kcal ml-1; pea and whey peptide hydrolysates, both 0.2 kcal ml-1; milk protein, 0.7 kcal ml-1) were tested in six healthy subjects in random order on four separate occasions. 2. The glucose solution was emptied the fastest with a half-time of 9.4 +/- 1.2 min (P < 0.05) and the milk protein the slowest with a half-time of 26.4 +/- 10.0 min (P < 0.05); the pea peptide hydrolysate and whey peptide hydrolysate solutions had half-times of emptying of 16.3 +/- 5.4 and 17.2 +/- 6.1 min, respectively. The rates of gastric emptying for the peptide hydrolysate solutions derived from different protein sources were not different. 3. Despite the lower rate of gastric emptying for the milk protein solution, the rate of caloric delivery to the duodenum during the early phase of the gastric emptying process was higher than that for the other three solutions (46.3 +/- 6, 63.5 +/- 22, 62.5 +/- 19 and 113.8 +/- 25 cal min-1 kg-1 for the glucose, pea peptide hydrolysate, whey peptide hydrolysate and milk protein meals, respectively; P < 0.05). The caloric density of the test solutions was linearly related to the half-time of gastric emptying (r = 0.96, P < 0.05) as well as to the rate at which calories were delivered to the duodenum (r = 0.99, P < 0.001). 4. This study demonstrates that the rate of gastric emptying is a function of the caloric density of the ingested meal and that a linear relationship exists between these variables. Furthermore, the nature of the calories seems to play a minor role in determining the rate of gastric emptying in humans.

Engineering knowledge-based variance-reduction simulation and G-dominance for structural frame robust optimization

[EN] This paper proposes the incorporation of engineering knowledge through both (a) advanced state-of-the-art preference handling decision-making tools integrated in multiobjective evolutionary algorithms and (b) engineering knowledge-based variance reduction simulation as enhancing tools for the robust optimum design of structural frames taking uncertainties into consideration in the design variables.The simultaneous minimization of the constrained weight (adding structuralweight and average distribution of constraint violations) on the one hand and the standard deviation of the distribution of constraint violation on the other are handled with multiobjective optimization-based evolutionary computation in two different multiobjective algorithms. The optimum design values of the deterministic structural problem in question are proposed as a reference point (the aspiration level) in reference-point-based evolutionary multiobjective algorithms (here g-dominance is used). Results including