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OCCUPATIONAL APPLICATIONSIn the context of Industry 5.0, our study advances manufacturing factory layout planning by integrating multi-objective optimization with nature-inspired algorithms and a digital human modeling tool. This approach aims to overcome the limitations of traditional planning methods, which often rely on engineers' expertise and inputs from various functions in a company, leading to slow processes and risk of human errors. By focusing the multi-objective optimization on three primary targets, our methodology promotes objective and efficient layout planning, simultaneously considering worker well-being and system performance efficiency. Illustrated through a pedal car assembly station layout case, we demonstrate how layout planning can transition into a transparent, cross-disciplinary, and automated activity. This methodology provides multi-objective decision support, showcasing a significant step forward in manufacturing factory layout design practices.

Rationale: Integrating multi-objective optimization in manufacturing layout planning addresses simultaneous considerations of productivity, worker well-being, and space efficiency, moving beyond traditional, expert-reliant methods that often overlook critical design aspects. Leveraging nature-inspired algorithms and a digital human modeling tool, this study advances a holistic, automated design process in line with Industry 5.0. Purpose: This research demonstrates an innovative approach to manufacturing layout optimization that simultaneously considers worker well-being and system performance. Utilizing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swarm Optimization (PSO) alongside a Digital Human Modeling (DHM) tool, the study proposes layouts that equally prioritize ergonomic factors, productivity, and area utilization. Methods: Through a pedal car assembly station case, the study illustrates the transition of layout planning into a transparent, cross-disciplinary, and automated process. This method offers objective decision support, balancing diverse objectives concurrently. Results: The optimization results obtained from the NSGA-II and PSO algorithms represent feasible non-dominated solutions of layout proposals, with the NSGA-II algorithm finding a solution superior in all objectives compared to the expert engineer-designed start solution for the layout. This demonstrates the presented method's capacity to refine layout planning practices significantly. Conclusions: The study validates the effectiveness of combining multi-objective optimization with digital human modeling in manufacturing layout planning, aligning with Industry 5.0's emphasis on human-centric processes. It proves that operational efficiency and worker well-being can be simultaneously considered and presents future potential manufacturing design advancements. This approach underscores the necessity of multi-objective consideration for optimal layout achievement, marking a progressive step in meeting modern manufacturing's complex demands.

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A chemical multisensor array is used in combination with an artificial neural network to estimate the biomass concentration and specific growth rate in a recombination Escherichia coli batch cultivation. It is shown that by providing sufficient information to the artificial neural network, an accuracy comparable to that of an established dry weight method can be achieved. The obtained prediction error (1 sigma) of 0.043 g l-1 for biomass compares well with the error of the dry weight method in this low biomass concentration range (0.1-3 g l-1). The prediction for the specific growth rate is accurate during important parts of the cell growth (1 sigma = 0.025 h-1). The results show that this non-invasive method is potentially useful for estimating biomass and specific growth rate on-line in bioprocesses.

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Daily variations of pineal and plasma melatonin and plasma thyroid hormones were measured in harp seals (Phoca groenlandica), grey seals (Halichoerus grypus), and hooded seals (Cystophora cristata), ranging in age from newborn to 14 days. In newborn harp seals the mean mass of the pineal gland was 273 mg (+/- 45 SEM, n = 11), containing 49 ng (median) melatonin. In newborn, 4- and 10-day-old grey seals, the pineal mass was similar, weighing on average 337 mg (+/- 74, n = 6) and containing 90 ng melatonin. Two newborn hooded seal pups had pineals weighing 520 and 1289 mg, with 254 and 7600 ng melatonin, respectively. There were no day-night differences in the pineal contents of melatonin or in the number of pineal beta-adrenergic receptors measured in newborn harp seals, and, in newborn, 4- and 10-day-old grey seals, there were no day-night or age differences in pineal melatonin content. Plasma melatonin levels were 10 times higher in newborn seals than in two 10-day-old grey seals and one 14-day-old harp seal pup. In all seal pups, the levels exhibited a 24-hr rhythmicity, with increasing night- and decreasing daytime concentrations. Plasma levels of thyroxine (T4) and triiodothyronine (T3) were generally higher in newborn seals than in 10- and 14-day-old seals or in adult females. There was no apparent 24-hr rhythmicity, but the thyroid hormone levels generally declined throughout each sampling sequence. High pineal and thyroid activities may play a thermoregulatory role in newborn seals, but the results do not indicate a stimulatory action of melatonin in the peripheral conversion of T4 to T3. It is speculated that the large and active pineal gland, particularly in newborn seals, may be related to aspects of their diving habit.

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Apparent digestible efficiency (% DE) was studied by use of dietary Mn as an inert marker, in minke whales (Balaenoptera acutorostrata) and crabeater seals (Lobodon carcinophagus) which had been eating krill. Median % DE in minke whales (n5) eating krill of the genus Thysanoessa sp. (energy density (ED) 23.8 kJ/g) was 93 (range 87-93). Median % DE in crabeater seals (n6) eating krill of the species Euphausia superba (ED 20.8 kJ/g) was 84 (range 79-85), which is significantly lower than the % DE of krill in minke whales (P = 0.008). Since the chemical composition in E. superba and in Thysanoessa sp. is similar, it is suggested that the complex multi-stomached system of minke whales, which contains both chitinase (EC 3.2.1.14)-producing as well as several other types of bacteria, is superior to the single-stomached system of crabeater seals with regard to krill digestion. It is worth noting, however, that the % DE of krill in the crabeater seal is still very high.

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