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We investigate the ergodic properties of a random walker performing (anomalous) diffusion on a random fractal geometry. Extensive Monte Carlo simulations of the motion of tracer particles on an ensemble of realisations of percolation clusters are performed for a wide range of percolation densities. Single trajectories of the tracer motion are analysed to quantify the time averaged mean squared displacement (MSD) and to compare this with the ensemble averaged MSD of the particle motion. Other complementary physical observables associated with ergodicity are studied, as well. It turns out that the time averaged MSD of individual realisations exhibits non-vanishing fluctuations even in the limit of very long observation times as the percolation density approaches the critical value. This apparent non-ergodic behaviour concurs with the ergodic behaviour on the ensemble averaged level. We demonstrate how the non-vanishing fluctuations in single particle trajectories are analytically expressed in terms of the fractal dimension and the cluster size distribution of the random geometry, thus being of
purely geometrical origin. Moreover, we reveal that the convergence scaling law to ergodicity, which is known to be inversely proportional to the observation time T for ergodic diffusion processes, follows a power-law BTh with h o 1 due to the fractal structure of the accessible space. These results provide useful measures for differentiating the subdiffusion on random fractals from an otherwise closely related process, namely, fractional Brownian motion. Implications of our results on the analysis of single particle tracking experiments are provided.
The interruption of learning processes by breaks filled with diverse activities is common in everyday life. We investigated the effects of active computer gaming and passive relaxation (rest and music) breaks on working memory performance. Young adults were exposed to breaks involving (i) eyes-open resting, (ii) listening to music and (iii) playing the video game “Angry Birds” before performing the n-back working memory task. Based on linear mixed-effects modeling, we found that playing the “Angry Birds” video game during a short learning break led to a decline in task performance over the course of the task as compared to eyes-open resting and listening to music, although overall task performance was not impaired. This effect was associated with high levels of daily mind wandering and low self-reported ability to concentrate. These findings indicate that video games can negatively affect working memory performance over time when played in between learning tasks. We suggest further investigation of these effects because of their relevance to everyday activity.
The Norway lobster, Nephrops norvegicus, is a burrowing decapod with a rhythmic burrow emergence (24 h) governed by the circadian system. It is an important resource for European fisheries and its behavior deeply affects its availability. The current knowledge of Nephrops circadian biology is phenomenological as it is currently the case for almost all crustaceans. In attempt to elucidate the putative molecular mechanisms underlying circadian gene regulation in Nephrops, we used a transcriptomics approach on cDNA extracted from the eyestalk, a structure playing a crucial role in controlling behavior of decapods. We studied 14 male lobsters under 12–12 light-darkness blue light cycle. We used the Hiseq 2000 Illumina platform to sequence two eyestalk libraries (under light and darkness conditions) obtaining about 90 millions 100-bp paired-end reads. Trinity was used for the de novo reconstruction of transcriptomes; the size at which half of all assembled bases reside in contigs (N50) was equal to 1796 (light) and 2055 (darkness). We found a list of candidate clock genes and focused our attention on canonical ones: timeless, period, clock and bmal1. The cloning of assembled fragments validated Trinity outputs. The putative Nephrops clock genes showed high levels of identity (blastx on NCBI) with known crustacean clock gene homologs such as Eurydice pulchra (period: 47%, timeless: 59%, bmal1: 79%) and Macrobrachium rosenbergii (clock: 100%). We also found a vertebrate-like cryptochrome 2. RT-qPCR showed that only timeless had a robust diel pattern of expression. Our data are in accordance with the current knowledge of the crustacean circadian clock, reinforcing the idea that the molecular clockwork of this group shows some differences with the established model in Drosophila melanogaster.
Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961–1990) and a future (2071–2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature.We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate
projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.