Red noise in steady-state multiphase flow

Understanding the interaction between competing fluids in the pore space of rocks is key for predicting subsurface flow and trapping, such as with CO2 in a saline aquifer. These processes occur over a large span of timescales (from seconds to thousands of years), and length scales (from microns to kilometres). Understanding the link between these temporal and spatial scales will enable us to interpolate between observations made at different resolutions. In this work we explore the temporal scales present during macroscopically steady-state multiphase flow in a porous rock using differential pressure measurements. We observe a cascade of timescales in the pressure differential i.e. a continuous range of frequencies, with lower frequencies having greater amplitudes. We demonstrate a scaling of the spectral density with frequency of S ∼ 1/f^2, or red noise, to describe the dynamics. This scaling is independent of the flow rate of the fluids or the fraction of the flow taken by water. This red, or Brownian, noise indicates a stochastic process where pressure fluctuations are seen throughout the pore space, resulting in intermittent filling of pores over a wide range of time-scales, from seconds to minutes in these experiments. This observation will aid future modelling of subsurface flow as it suggests self-organised critically of the system with no characteristic time or length scale.

Polarimetric Properties of Blazars Caught by the WEBT

Active galactic nuclei come in many varieties. A minority of them are radio-loud, and exhibit two opposite prominent plasma jets extending from the proximity of the supermassive black hole up to megaparsec distances. When one of the relativistic jets is oriented closely to the line of sight, its emission is Doppler beamed and these objects show extreme variability properties at all wavelengths. These are called “blazars”. The unpredictable blazar variability, occurring on a continuous range of time-scales, from minutes to years, is most effectively investigated in a multi-wavelength context. Ground-based and space observations together contribute to give us a comprehensive picture of the blazar emission properties from the radio to the γ-ray band. Moreover, in recent years, a lot of effort has been devoted to the observation and analysis of the blazar polarimetric radio and optical behaviour, showing strong variability of both the polarisation degree and angle. The Whole Earth Blazar Telescope (WEBT) Collaboration, involving many tens of astronomers all around the globe, has been monitoring several blazars since 1997. The results of the corresponding data analysis have contributed to the understanding of the blazar phenomenon, particularly stressing the viability of a geometrical interpretation of the blazar variability. We review here the most significant polarimetric results achieved in the WEBT studies.

Predicting population genetic change in an experimental stochastic environment

Most natural environments exhibit a substantial component of random variation. Such environmental noise is expected to cause random fluctuations in natural selection, affecting the predictability of evolution. But despite a long-standing theoretical interest for understanding the population genetic consequences of stochastic environments, there has been a dearth of empirical validation and estimation of the underlying parameters of this theory. Indeed, tracking the genetics of a large number of replicate lines under a controlled level of environmental stochasticity is particularly challenging. Here, we tackled this problem by resorting to an automated experimental evolution approach. We used a liquid-handling robot to expose over a hundred lines of the micro-alga Dunaliella salina to randomly fluctuating salinity over a continuous range, with controlled mean, variance, and autocorrelation. We then tracked the frequency of one of two competing strains through amplicon sequencing of a nuclear and choloroplastic barcode sequences. We show that the magnitude of environmental fluctuations (variance), but also their predictability (autocorrelation), have large impacts on the average selection coefficient. Furthermore, the stochastic variance in population genetic change is substantially higher in a fluctuating environment. Reaction norms of selection coefficients and growth rates of single strains against the environment captured the mean response accurately, but failed to explain the high variance induced by environmental stochasticity. Overall, our results provide exceptional insights on the prospects for understanding and predicting genetic evolution in randomly fluctuating environments.

The crystalline waters of the Bodoquena Plateau revealed Hypostomus froehlichi (Siluriformes: Loricariidae), a new armored catfish from the rio Paraguay basin in Brazil

The menaced and poorly-known waters of the Bodoquena Plateau revealed a new resident, the stunning Hypostomus froehlichi sp. n., a large-sized armored catfish, which is finally described after more than twenty years since its discovery. The Bodoquena Plateau is drained by the rio Paraguay basin, and is located in the state of Mato Grosso do Sul, Brazil. The new species differs from its congeners on the Bodoquena crystalline waters by having teeth with morphological and numerical variation in adult specimens. There is a continuous range of specimens having about 20 thick and worn teeth to specimens having about 50 thin teeth with intact crowns and lanceolate main cusps. Additional diagnostic characters are: dentaries angled more than 90 degrees, dark blotches, one plate bordering supraoccipital, moderate keel along dorsal series of plates, usually two rows of blotches per interradial membrane on dorsal, pectoral and ventral fins, and by attaining comparatively large size. Hypostomus froehlichi seems to be endemic to the area of the Bodoquena Plateau, in rivers draining to the rio Miranda. The description of the new species reveals a potential conservation flagship species as it is one of the most seen and documented fish by visitors and divers in the clear waters from the touristic, though menaced, Bonito region in Brazil.

A method for continuous-range sequence analysis with Jensen-Shannon divergence

Mutual Information (MI) is a useful Information Theory tool for the recognition of mutual dependence between data sets. Several methods have been developed fore estimation of MI when both data sets are of the discrete type or when both are of the continuous type. However, MI estimation between a discrete range data set and a continuous range data set has not received so much attention. We therefore present here a method for the estimation of MI for this case, based on the kernel density approximation. This calculationmay be of interest in diverse contexts. Since MI is closely related to the Jensen Shannon divergence, the method developed here is of particular interest in the problems of sequence segmentation and set comparisons.

Use of a genetic algorithm to optimize a NumericalWeather Prediction system

An important step in an Ensemble Kalman Filter (EnKF) algorithm is the integration of an ensemble of short-range forecasts with a Numerical Weather Prediction (NWP) model. A multi-physics approach is used in the Canadian global EnKF system. This paper explores whether the many integrations with different versions of the model physics can be used to obtain more accurate and more reliable probability distributions for the model parameters. Some model parameters have a continuous range of possible values. Other parameters are categorical and act as switches between different parametrizations. In an evolutionary algorithm, the member configurations that contribute most to the quality of the ensemble are duplicated, while adding a small perturbation, at the expense of configurations that perform poorly. The evolutionary algorithm is being used in the migration of the EnKF to a new version of the Canadian NWP model with upgraded physics. The quality of configurations is measured with both a deterministic and an ensemble score, using the observations assimilated in the EnKF system. When using the ensemble score in the evaluation, the algorithm is shown to be able to converge to non-Gaussian distributions. However, for several model parameters, there is not enough information to arrive at improved distributions. The optimized system features slight reductions in biases for radiance measurements that are sensitive to humidity. Modest improvements are also seen in medium-range ensemble forecasts.

Time Hurries on but Does not Fly in Older Age — No Effect of Depressive Symptoms

Research on the commonly known phenomenon of perceived accelerated time passage with increasing age has provided inconsistent results. This could be due to a mediating time-slowing effect of depressive symptoms as the prevalence of depression does also alter with age. Based on a large sample of 380 subjects covering a continuous range of age between 20 and 70 years, we tested whether the assumed age-related effect on time perception is being mediated by symptoms of depression. Cross-sectional differences indicate a weak, but significant nonlinear acceleration of the perceived passage of time especially during mid-adulthood, whereas no further alteration was observed above the age of 60. In contrast to our hypothesis, symptoms of depression did clearly not mediate the effects of age on perceived time passage. Moreover, neither time passage ratings nor age were significantly related to the severity of depressive symptoms. Our results are partly compatible with (and extend) several previous reports, indicating that subjective time passage changes over the life span in a nonlinear fashion; they do not provide evidence for a mediating time-slowing effect of depressive symptoms in nonclinical samples.