Continuum percolation for Gibbs point processes

We consider percolation properties of the Boolean model generated by a Gibbs point process and balls with deterministic radius. We show that for a large class of Gibbs point processes there exists a critical activity, such that percolation occurs a.s. above criticality. For locally stable Gibbs point processes we show a converse result, i.e. they do not percolate a.s. at low activity.

Regularity conditions in the realisability problem in applications to point processes and random closed sets

We study existence of random elements with partially specified distributions. The technique relies on the existence of a positive ex-tension for linear functionals accompanied by additional conditions that ensure the regularity of the extension needed for interpreting it as a probability measure. It is shown in which case the extens ion can be chosen to possess some invariance properties. The results are applied to the existence of point processes with given correlation measure and random closed sets with given two-point covering function or contact distribution function. It is shown that the regularity condition can be efficiently checked in many cases in order to ensure that the obtained point processes are indeed locally finite and random sets have closed realisations.

Gibbs point process approximation: Total variation bounds using Stein's method

We obtain upper bounds for the total variation distance between the distributions of two Gibbs point processes in a very general setting. Applications are provided to various well-known processes and settings from spatial statistics and statistical physics, including the comparison of two Lennard-Jones processes, hard core approximation of an area interaction process and the approximation of lattice processes by a continuous Gibbs process. Our proof of the main results is based on Stein's method. We construct an explicit coupling between two spatial birth-death processes to obtain Stein factors, and employ the Georgii-Nguyen-Zessin equation for the total bound.

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

An examination of the metabolic processes underpinning critical swimming in Atlantic cod (Gadus morhua L.) using in vivo 31P-NMR spectroscopy.

Traditionally, critical swimming speed has been defined as the speed when a fish can no longer propel itself forward, and is exhausted. To gain a better understanding of the metabolic processes at work during a U(crit) swim test, and that lead to fatigue, we developed a method using in vivo (31)P-NMR spectroscopy in combination with a Brett-type swim tunnel. Our data showed that a metabolic transition point is reached when the fish change from using steady state aerobic metabolism to non-steady state anaerobic metabolism, as indicated by a significant increase in inorganic phosphate levels from 0.3+/-0.3 to 9.5+/-3.4 mol g(-1), and a drop in intracellular pH from 7.48+/-0.03 to 6.81+/-0.05 in muscle. This coincides with the point when the fish change gait from subcarangiform swimming to kick-and-glide bursts. As the number of kicks increased, so too did the Pi concentration, and the pH(i) dropped. Both changes were maximal at U(crit). A significant drop in Gibbs free energy change of ATP hydrolysis from -55.6+/-1.4 to -49.8+/-0.7 kJ mol(-1) is argued to have been involved in fatigue. This confirms earlier findings that the traditional definition of U(crit), unlike other critical points that are typically marked by a transition from aerobic to anaerobic metabolism, is the point of complete exhaustion of both aerobic and anaerobic resources.

Non-exponential return time distributions for vorticity extremes explained by fractional Poisson processes

Serial correlation of extreme midlatitude cyclones observed at the storm track exits is explained by deviations from a Poisson process. To model these deviations, we apply fractional Poisson processes (FPPs) to extreme midlatitude cyclones, which are defined by the 850 hPa relative vorticity of the ERA interim reanalysis during boreal winter (DJF) and summer (JJA) seasons. Extremes are defined by a 99% quantile threshold in the grid-point time series. In general, FPPs are based on long-term memory and lead to non-exponential return time distributions. The return times are described by a Weibull distribution to approximate the Mittag–Leffler function in the FPPs. The Weibull shape parameter yields a dispersion parameter that agrees with results found for midlatitude cyclones. The memory of the FPP, which is determined by detrended fluctuation analysis, provides an independent estimate for the shape parameter. Thus, the analysis exhibits a concise framework of the deviation from Poisson statistics (by a dispersion parameter), non-exponential return times and memory (correlation) on the basis of a single parameter. The results have potential implications for the predictability of extreme cyclones.

Bounds for the probability generating functional of a Gibbs point process

We derive explicit lower and upper bounds for the probability generating functional of a stationary locally stable Gibbs point process, which can be applied to summary statistics such as the F function. For pairwise interaction processes we obtain further estimates for the G and K functions, the intensity, and higher-order correlation functions. The proof of the main result is based on Stein's method for Poisson point process approximation.

Spatial cognition, body representation and affective processes: the role of vestibular information beyond ocular reflexes and control of posture

A growing number of studies in humans demonstrate the involvement of vestibular information in tasks that are seemingly remote from well-known functions such as space constancy or postural control. In this review article we point out three emerging streams of research highlighting the importance of vestibular input: (1) Spatial Cognition: Modulation of vestibular signals can induce specific changes in spatial cognitive tasks like mental imagery and the processing of numbers. This has been shown in studies manipulating body orientation (changing the input from the otoliths), body rotation (changing the input from the semicircular canals), in clinical findings with vestibular patients, and in studies carried out in microgravity. There is also an effect in the reverse direction; top-down processes can affect perception of vestibular stimuli. (2) Body Representation: Numerous studies demonstrate that vestibular stimulation changes the representation of body parts, and sensitivity to tactile input or pain. Thus, the vestibular system plays an integral role in multisensory coordination of body representation. (3) Affective Processes and Disorders: Studies in psychiatric patients and patients with a vestibular disorder report a high comorbidity of vestibular dysfunctions and psychiatric symptoms. Recent studies investigated the beneficial effect of vestibular stimulation on psychiatric disorders, and how vestibular input can change mood and affect. These three emerging streams of research in vestibular science are—at least in part—associated with different neuronal core mechanisms. Spatial transformations draw on parietal areas, body representation is associated with somatosensory areas, and affective processes involve insular and cingulate cortices, all of which receive vestibular input. Even though a wide range of different vestibular cortical projection areas has been ascertained, their functionality still is scarcely understood.

Importance sampling approximations to various probabilities of ruin of spectrally negative Lévy risk processes

This article provides importance sampling algorithms for computing the probabilities of various types ruin of spectrally negative Lévy risk processes, which are ruin over the infinite time horizon, ruin within a finite time horizon and ruin past a finite time horizon. For the special case of the compound Poisson process perturbed by diffusion, algorithms for computing probabilities of ruins by creeping (i.e. induced by the diffusion term) and by jumping (i.e. by a claim amount) are provided. It is shown that these algorithms have either bounded relative error or logarithmic efficiency, as t,x→∞t,x→∞, where t>0t>0 is the time horizon and x>0x>0 is the starting point of the risk process, with y=t/xy=t/x held constant and assumed either below or above a certain constant.