Comparison of macroalgal dominants in the two Olentangy River experimental wetland basins

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Algal and Lemna populations continue to fluctuate seasonally and basin-to-basin in the Olentangy River wetlands

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Summer mat macroalgae largely replaced by duckweed, Lemna minor, in 1999 in two Olentangy River experimental wetlands

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Time's Barbed Arrow: Irreversibility, Crypticity, and Stored Information

We show why the amount of information communicated between the past and future--the excess entropy--is not in general the amount of information stored in the present--the statistical complexity. This is a puzzle, and a long-standing one, since the latter is what is required for optimal prediction, but the former describes observed behavior. We layout a classification scheme for dynamical systems and stochastic processes that determines when these two quantities are the same or different. We do this by developing closed-form expressions for the excess entropy in terms of optimal causal predictors and retrodictors--the epsilon-machines of computational mechanics. A process's causal irreversibility and crypticity are key determining properties.Comment: 4 pages, 2 figure

Complex Network Approach for Recurrence Analysis of Time Series

We propose a novel approach for analysing time series using complex network theory. We identify the recurrence matrix calculated from time series with the adjacency matrix of a complex network, and apply measures for the characterisation of complex networks to this recurrence matrix. By using the logistic map, we illustrate the potentials of these complex network measures for detecting dynamical transitions. Finally we apply the proposed approach to a marine palaeo-climate record and identify subtle changes of the climate regime.Comment: 23 pages, 7 figure

Chaos in the Einstein-Yang-Mills Equations

Yang-Mills color fields evolve chaotically in an anisotropically expanding universe. The chaotic behaviour differs from that found in anisotropic Mixmaster universes. The universe isotropizes at late times, approaching the mean expansion rate of a radiation-dominated universe. However, small chaotic oscillations of the shear and color stresses continue indefinitely. An invariant, coordinate-independent characterisation of the chaos is provided by means of fractal basin boundaries.Comment: 3 pages LaTeX + 3 pages of figure

Tensile Deformation of Oriented Poly(ε-caprolactone) and Its Miscible Blends with Poly(vinyl methyl ether)

The structural evolution of micromolded poly(ε-caprolactone) (PCL) and its miscible blends with noncrystallizable poly(vinyl methyl ether) (PVME) at the nanoscale was investigated as a function of deformation ratio and blend composition using in situ synchrotron smallangle X-ray scattering (SAXS) and scanning SAXS techniques. It was found that the deformation mechanism of the oriented samples shows a general scheme for the process of tensile deformation: crystal block slips within the lamellae occur at small deformations followed by a stressinduced fragmentation and recrystallization process along the drawing direction at a critical strain where the average thickness of the crystalline lamellae remains essentially constant during stretching. The value of the critical strain depends on the amount of the amorphous component incorporated in the blends, which could be traced back to the lower modulus of the entangled amorphous phase and, therefore, the reduced network stress acting on the crystallites upon addition of PVME. When stretching beyond the critical strain the slippage of the fibrils (stacks of newly formed lamellae) past each other takes place resulting in a relaxation of stretched interlamellar amorphous chains. Because of deformation-induced introduction of the amorphous PVME into the interfibrillar regions in the highly oriented blends, the interactions between fibrils becomes stronger upon further deformation and thus impeding sliding of the fibrils to some extent leading finally to less contraction of the interlamellar amorphous layers compared to the pure PCLNational Natural Science Foundation of China (21204088 and 21134006). This work is within the framework of the RCUK/EPSRC Science Bridges China project of UK−China Advanced Materials Research Institute (AMRI)

Monitoring the Depth of Anaesthesia

One of the current challenges in medicine is monitoring the patients’ depth of general anaesthesia (DGA). Accurate assessment of the depth of anaesthesia contributes to tailoring drug administration to the individual patient, thus preventing awareness or excessive anaesthetic depth and improving patients’ outcomes. In the past decade, there has been a significant increase in the number of studies on the development, comparison and validation of commercial devices that estimate the DGA by analyzing electrical activity of the brain (i.e., evoked potentials or brain waves). In this paper we review the most frequently used sensors and mathematical methods for monitoring the DGA, their validation in clinical practice and discuss the central question of whether these approaches can, compared to other conventional methods, reduce the risk of patient awareness during surgical procedures

Modeling Brain Resonance Phenomena Using a Neural Mass Model

Stimulation with rhythmic light flicker (photic driving) plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment) is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM) of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect