Estimating the distribution of dynamic invariants: illustrated with an application to human photo-plethysmographic time series

Dynamic invariants are often estimated from experimental time series with the aim of differentiating between different physical states in the underlying system. The most popular schemes for estimating dynamic invariants are capable of estimating confidence intervals, however, such confidence intervals do not reflect variability in the underlying dynamics. We propose a surrogate based method to estimate the expected distribution of values under the null hypothesis that the underlying deterministic dynamics are stationary. We demonstrate the application of this method by considering four recordings of human pulse waveforms in differing physiological states and show that correlation dimension and entropy are insufficient to differentiate between these states. In contrast, algorithmic complexity can clearly differentiate between all four rhythms

Detecting periodicity in experimental data using linear modeling techniques

Fourier spectral estimates and, to a lesser extent, the autocorrelation function are the primary tools to detect periodicities in experimental data in the physical and biological sciences. We propose a new method which is more reliable than traditional techniques, and is able to make clear identification of periodic behavior when traditional techniques do not. This technique is based on an information theoretic reduction of linear (autoregressive) models so that only the essential features of an autoregressive model are retained. These models we call reduced autoregressive models (RARM). The essential features of reduced autoregressive models include any periodicity present in the data. We provide theoretical and numerical evidence from both experimental and artificial data, to demonstrate that this technique will reliably detect periodicities if and only if they are present in the data. There are strong information theoretic arguments to support the statement that RARM detects periodicities if they are present. Surrogate data techniques are used to ensure the converse. Furthermore, our calculations demonstrate that RARM is more robust, more accurate, and more sensitive, than traditional spectral techniques.Comment: 10 pages (revtex) and 6 figures. To appear in Phys Rev E. Modified styl

Multi-Player Diffusion Games on Graph Classes

We study competitive diffusion games on graphs introduced by Alon et al. [1] to model the spread of influence in social networks. Extending results of Roshanbin [8] for two players, we investigate the existence of pure Nash equilibria for at least three players on different classes of graphs including paths, cycles, grid graphs and hypercubes; as a main contribution, we answer an open question proving that there is no Nash equilibrium for three players on (m x n) grids with min(m, n) >= 5. Further, extending results of Etesami and Basar [3] for two players, we prove the existence of pure Nash equilibria for four players on every d-dimensional hypercube.Comment: Extended version of the TAMC 2015 conference version now discussing hypercube results (added details for the proof of Proposition 1

rPICARD: A CASA-based Calibration Pipeline for VLBI Data

Currently, HOPS and AIPS are the primary choices for the time-consuming process of (millimeter) Very Long Baseline Interferometry (VLBI) data calibration. However, for a full end-to-end pipeline, they either lack the ability to perform easily scriptable incremental calibration or do not provide full control over the workflow with the ability to manipulate and edit calibration solutions directly. The Common Astronomy Software Application (CASA) offers all these abilities, together with a secure development future and an intuitive Python interface, which is very attractive for young radio astronomers. Inspired by the recent addition of a global fringe-fitter, the capability to convert FITS-IDI files to measurement sets, and amplitude calibration routines based on ANTAB metadata, we have developed the the CASA-based Radboud PIpeline for the Calibration of high Angular Resolution Data (rPICARD). The pipeline will be able to handle data from multiple arrays: EHT, GMVA, VLBA and the EVN in the first release. Polarization and phase-referencing calibration are supported and a spectral line mode will be added in the future. The large bandwidths of future radio observatories ask for a scalable reduction software. Within CASA, a message passing interface (MPI) implementation is used for parallelization, reducing the total time needed for processing. The most significant gain is obtained for the time-consuming fringe-fitting task where each scan be processed in parallel.Comment: 6 pages, 1 figure, EVN 2018 symposium proceeding

Gravitational Waves Probe the Coalescence Rate of Massive Black Hole Binaries

We calculate the expected nHz--$\mu$Hz gravitational wave (GW) spectrum from coalescing Massive Black Hole (MBH) binaries resulting from mergers of their host galaxies. We consider detection of this spectrum by precision pulsar timing and a future Pulsar Timing Array. The spectrum depends on the merger rate of massive galaxies, the demographics of MBHs at low and high redshift, and the dynamics of MBH binaries. We apply recent theoretical and observational work on all of these fronts. The spectrum has a characteristic strain $h_c(f)~10^{-15} (f/yr^{-1})^{-2/3}$, just below the detection limit from recent analysis of precision pulsar timing measurements. However, the amplitude of the spectrum is still very uncertain owing to approximations in the theoretical formulation of the model, to our lack of knowledge of the merger rate and MBH population at high redshift, and to the dynamical problem of removing enough angular momentum from the MBH binary to reach a GW-dominated regime.Comment: 31 Pages, 8 Figures, small changes to match the published versio

Long-term balancing selection at the Phosphorus Starvation Tolerance 1 (PSTOL1) locus in wild, domesticated and weedy rice (Oryza)

Dry Shoot Weights of PSTOL1 genotypes grown in low and high phosphorus conditions. Plants were measured after 21 days in high phosphorus (black) and low phosphorus (grey) media. (PDF 72 kb

Subregional Hippocampal Thickness Abnormalities in Older Adults with a History of Heavy Cannabis Use.

Background and Aims: Legalization of cannabis (CB) for both medicinal and, in some states, recreational use, has given rise to increasing usage rates across the country. Of particular concern are indications that frequent CB use may be selectively harmful to the developing adolescent brain compared with adult-onset usage. However, the long-term effects of heavy, adolescent CB use on brain structure and cognitive performance in late-life remain unknown. A critical brain region is the hippocampus (HC), where there is a striking intersection between high concentrations of cannabinoid 1 (CB1) receptors and age-related pathology. Design: We investigated whether older adults (average age=66.6+7.2 years old) with a history of early life CB use show morphological differences in hippocampal subregions compared with older, nonusers. Methods: We performed high-resolution magnetic resonance imaging combined with computational techniques to assess cortical thickness of the medial temporal lobe, neuropsychological testing, and extensive drug use histories on 50 subjects (24 formerly heavy cannabis users [CB+ group] abstinent for an average of 28.7 years, 26 nonusers [CB- group]). We investigated group differences in hippocampal subregions, controlling for age, sex, and intelligence (as measured by the Wechsler Test of Adult Reading), years of education, and cigarette use. Results: The CB+ subjects exhibited thinner cortices in subfields cornu ammonis 1 [CA1; F(1,42)=9.96, p=0.0003], and CA2, 3, and the dentate gyrus [CA23DG; F(1,42)=23.17, p<0.0001], and in the entire HC averaged over all subregions [F(1,42)=8.49, p=0.006]. Conclusions: Negative effects of chronic adolescent CB use on hippocampal structure are maintained well into late life. Because hippocampal cortical loss underlies and exacerbates age-related cognitive decline, these findings have profound implications for aging adults with a history of early life usage. Clinical Trial Registration: ClinicalTrials.gov # NCT01874886