A pressure-robust embedded discontinuous Galerkin method for the Stokes problem by reconstruction operators

The embedded discontinuous Galerkin (EDG) finite element method for the Stokes problem results in a point-wise divergence-free approximate velocity on cells. However, the approximate velocity is not H(div)-conforming and it can be shown that this is the reason that the EDG method is not pressure-robust, i.e., the error in the velocity depends on the continuous pressure. In this paper we present a local reconstruction operator that maps discretely divergence-free test functions to exactly divergence-free test functions. This local reconstruction operator restores pressure-robustness by only changing the right hand side of the discretization, similar to the reconstruction operator recently introduced for the Taylor--Hood and mini elements by Lederer et al. (SIAM J. Numer. Anal., 55 (2017), pp. 1291--1314). We present an a priori error analysis of the discretization showing optimal convergence rates and pressure-robustness of the velocity error. These results are verified by numerical examples. The motivation for this research is that the resulting EDG method combines the versatility of discontinuous Galerkin methods with the computational efficiency of continuous Galerkin methods and accuracy of pressure-robust finite element methods

Modelling Livestock Component in FSSIM

Agricultural and Food Policy, Environmental Economics and Policy, Land Economics/Use, Livestock Production/Industries,

Feeling the future: prospects for a theory of implicit prospection

Mental time travel refers to the ability of an organism to project herself backward and forward in time, using episodic memory and imagination to simulate past and future experiences. The evolution of mental time travel gives humans a unique capacity for prospection: the ability to pre-experience the future. Discussions of mental time travel treat it as an instance of explicit prospection. We argue that implicit simulations of past and future experience can also be used as a way of gaining information about the future to shape preferences and guide behaviour

Localized energy for wave equations with degenerate trapping

Localized energy estimates have become a fundamental tool when studying wave equations in the presence of asymptotically at background geometry. Trapped rays necessitate a loss when compared to the estimate on Minkowski space. A loss of regularity is a common way to incorporate such. When trapping is sufficiently weak, a logarithmic loss of regularity suffices. Here, by studying a warped product manifold introduced by Christianson and Wunsch, we encounter the first explicit example of a situation where an estimate with an algebraic loss of regularity exists and this loss is sharp. Due to the global-in-time nature of the estimate for the wave equation, the situation is more complicated than for the Schr\"{o}dinger equation. An initial estimate with sub-optimal loss is first obtained, where extra care is required due to the low frequency contributions. An improved estimate is then established using energy functionals that are inspired by WKB analysis. Finally, it is shown that the loss cannot be improved by any power by saturating the estimate with a quasimode.Comment: 18 page

A large-scale real-life crowd steering experiment via arrow-like stimuli

We introduce "Moving Light": an unprecedented real-life crowd steering experiment that involved about 140.000 participants among the visitors of the Glow 2017 Light Festival (Eindhoven, NL). Moving Light targets one outstanding question of paramount societal and technological importance: "can we seamlessly and systematically influence routing decisions in pedestrian crowds?" Establishing effective crowd steering methods is extremely relevant in the context of crowd management, e.g. when it comes to keeping floor usage within safety limits (e.g. during public events with high attendance) or at designated comfort levels (e.g. in leisure areas). In the Moving Light setup, visitors walking in a corridor face a choice between two symmetric exits defined by a large central obstacle. Stimuli, such as arrows, alternate at random and perturb the symmetry of the environment to bias choices. While visitors move in the experiment, they are tracked with high space and time resolution, such that the efficiency of each stimulus at steering individual routing decisions can be accurately evaluated a posteriori. In this contribution, we first describe the measurement concept in the Moving Light experiment and then we investigate quantitatively the steering capability of arrow indications.Comment: 8 page

Optimality and evolution of transcriptionally regulated gene expression

<p>Abstract</p> <p>Background</p> <p>How transcriptionally regulated gene expression evolves under natural selection is an open question. The cost and benefit of gene expression are the driving factors. While the former can be determined by gratuitous induction, the latter is difficult to measure directly.</p> <p>Results</p> <p>We addressed this problem by decoupling the regulatory and metabolic function of the <it>Escherichia coli lac </it>system, using an inducer that cannot be metabolized and a carbon source that does not induce. Growth rate measurements directly identified the induced expression level that maximizes the metabolism benefits minus the protein production costs, without relying on models. Using these results, we established a controlled mismatch between sensing and metabolism, resulting in sub-optimal transcriptional regulation with the potential to improve by evolution. Next, we tested the evolutionary response by serial transfer. Constant environments showed cells evolving to the predicted expression optimum. Phenotypes with decreased expression emerged several hundred generations later than phenotypes with increased expression, indicating a higher genetic accessibility of the latter. Environments alternating between low and high expression demands resulted in overall rather than differential changes in expression, which is explained by the concave shape of the cross-environmental tradeoff curve that limits the selective advantage of altering the regulatory response.</p> <p>Conclusions</p> <p>This work indicates that the decoupling of regulatory and metabolic functions allows one to directly measure the costs and benefits that underlie the natural selection of gene regulation. Regulated gene expression is shown to evolve within several hundreds of generations to optima that are predicted by these costs and benefits. The results provide a step towards a quantitative understanding of the adaptive origins of regulatory systems.</p

Modelling frequency and attestations for OntoLex-Lemon

The OntoLex vocabulary enjoys increasing popularity as a means of publishing lexical resources with RDF and as Linked Data. The recent publication of a new OntoLex module for lexicography, lexicog, reflects its increasing importance for digital lexicography. However, not all aspects of digital lexicography have been covered to the same extent. In particular, supplementary information drawn from corpora such as frequency information, links to attestations, and collocation data were considered to be beyond the scope of lexicog. Therefore, the OntoLex community has put forward the proposal for a novel module for frequency, attestation and corpus information (FrAC), that not only covers the requirements of digital lexicography, but also accommodates essential data structures for lexical information in natural language processing. This paper introduces the current state of the OntoLex-FrAC vocabulary, describes its structure, some selected use cases, elementary concepts and fundamental definitions, with a focus on frequency and attestations

When at rest: "Event-free” active inference may give rise to implicit self-models of coping potential

Kalisch and colleagues highlight coping potential (CP) as a principle resilience mechanism during event engagement. We complement this discussion by exploring generative implicit CP self-models, arguably emerging during "resting-state,” subsequent and prior to events. Resting-state affords a propitious environment for Bayesian learning, wherein appraisals/reappraisals may update active inferential CP self-models, which then mediate appraisal style organization and resilience factor valuatio

Burning velocity measurement of lean methane-air flames in a new nanosecond DBD microplasma burner platform

This paper presents the initial characterization of a new burner design to study the effect of non-thermal plasma discharge on combustion characteristics at atmospheric pressure. The burner allows stabilizing an inverted cone flame in a mixture flowing through a perforated plate designed as a microplasma reactor. The design principle of the microplasma reactor is based on the dielectric barrier discharge scheme which helps to generate a stable nonthermal plasma discharge driven by nanosecond high-voltage pulses in the burner holes. The consumed power and pulse energy have been calculated from simultaneously measurements of current and voltage of the electrical pulses. Time-resolved measurements of direct emission spectra for nitrogen second positive system N2(C-B) have been done to determine the rotational and vibrational temperatures of the plasma discharge. By fitting the spectra with SPECAIR simulation data, it was found that the rotational and vibrational temperatures are 480 K and 3700 K, respectively, for the discharge in methane-air mixture with an equivalence ratio of 0.5 at atmospheric pressure. The influence of a high-voltage (5 kV) pulsed nanosecond discharge on the laminar burning velocity of methane-air flame has been investigated over a range of equivalence ratios (0.55–0.75). The laminar burning velocity was calculated by the conical flame area method which has been validated by other published data. CH* chemiluminescence image analysis has been applied to accurately determine the flame area. The results show an increase of the burning velocity of about 100% in very lean (Φ= 0.55) flames as a result of the plasma discharge effect