11,108 research outputs found
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--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
, 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 21ĂÂ days in high phosphorus (black) and low phosphorus (grey) media. (PDF 72 kb
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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
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