Longevity is influenced by genetic and environmental factors. The brain's dopamine system may be particularly relevant, since it modulates traits (e.g., sensitivity to reward, incentive motivation, sustained effort) that impact behavioral responses to the environment. In particular, the dopamine D4 receptor (DRD4) has been shown to moderate the impact of environments on behavior and health. We tested the hypothesis that the DRD4 gene influences longevity and that its impact is mediated through environmental effects. Surviving participants of a 30 year-old population-based health survey (N=310, age range 90–109; the 90+ Study) were genotyped/resequenced at the DRD4 gene, and compared to a European ancestry-matched younger population (N=2902, age range 7–45). We found that the oldest-old population had a 66% increase in individuals carrying the DRD4 7R allele relative to the younger sample (p=3.5 × 10−9), and that this genotype was strongly correlated with increased levels of physical activity. Consistent with these results, DRD4 knockout mice, when compared to wild-type and heterozygous mice, displayed a 7–9.7% decrease in lifespan, reduced spontaneous locomotor activity, and no lifespan increase when reared in an enriched environment. These results support the hypothesis that DRD4 gene variants contribute to longevity in humans and in mice, and suggest that this effect is mediated by shaping behavioral responses to the environment.

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a Three-layer cross-oriented strand boards, OSB type 3 of 10 mm thick, were industrially manufactured from a mixture of wood species including 50% softwoods, 25% beech, and 25% low hardwoods, using a continuous press line. The effects of line speed and press factor on physical and mechanical properties of OSB/3 (exterior grade) were evaluated, keeping nearly constant the face-core adhesive ratio. The manufactured boards were classified into five groups depending on the pressing parameters. The experimental results showed that all mechanical properties increased, with increasing press factor and decreasing line speed. The ratios of bending strength (MOR) and the modulus of elasticity (MOE) parallel to perpendicular were 1.73 to 1.89 and 2.18 to 2.24, respectively. No significant differences in thickness swell and water absorption were observed. The lowest density was achieved at higher speed, although there was no large variation in densities between groups. Thickness swelling and internal bond after boil test exceeded the EN 300 standard requirements for OSB/3 moisture resistance, excepting a few boards. The results revealed that a correlation between speed and press factor is necessary in order to improve mechanical properties and to keep the physical performance of boards within a limited range of values.

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Abstract. Time studies represent important tools that are used in forest operations research to produce empirical models or to comparatively assess the performance of two or more operational alternatives with the general aim to predict the performance of operational behavior, choose the most adequate equipment or eliminate the useless time. There is a long tradition in collecting the needed data in a traditional fashion, but this approach has its limitations, and it is likely that in the future the use of professional software would be extended is such preoccupations as this kind of tools have been already implemented. However, little to no information is available in what concerns the performance of data analyzing tasks when using purpose-built professional time studying software in such research preoccupations, while the resources needed to conduct time studies, including here the time may be quite intensive. Our study aimed to model the relations between the variation of time needed to analyze the video-recorded time study data and the variation of some measured independent variables for a complex organization of a work cycle. The results of our study indicate that the number of work elements which were separated within a work cycle as well as the delay-free cycle time and the software functionalities that were used during data analysis, significantly affected the time expenditure needed to analyze the data (α=0.01, p<0.01). Under the conditions of this study, where the average duration of a work cycle was of about 48 seconds and the number of separated work elements was of about 14, the speed that was used to replay the video files significantly affected the mean time expenditure which averaged about 273 seconds for half of the real speed and about 192 seconds for an analyzing speed that equaled the real speed. We argue that different study designs as well as the parameters used within the software are likely to produce different results, a fact that should trigger other studies based on variations of these parameters. However, the results of this study give an initial overview on the time resources needed in processing and analyzing the data, and may help researchers in allocating their resources.