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

Scale-free user-network approach to telephone network traffic analysis

PACS number(s): 89.75.Hc, 89.75.Da, 89.75.FbAuthor name used in this publication: Chi K. TseAuthor name used in this publication: Francis C. M. Lau2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Electric Field Modulation of Galvanomagnetic Properties of Mesoscopic Graphite

Electric field effect devices based on mesoscopic graphite are fabricated for galvanomagnetic measurements. Strong modulation of magneto-resistance and Hall resistance as a function of gate voltage is observed as sample thickness approaches the screening length. Electric field dependent Landau level formation is detected from Shubnikov de Haas oscillations in magneto-resistance. The effective mass of electron and hole carriers has been measured from the temperature dependant behavior of these oscillations.Comment: 4 pages, 4 figures included, submitted to Phys. Rev. Let

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

Long-term changes in the north-south asymmetry of solar activity: A nonlinear dynamics characterization using visibility graphs

Solar activity is characterized by complex dynamics superimposed onto an almost periodic, approximately 11-year cycle. One of its main features is the presence of a marked, time-varying hemispheric asymmetry, the deeper reasons for which have not yet been completely uncovered. Traditionally, this asymmetry has been studied by considering amplitude and phase differences. Here, we use visibility graphs, a novel tool of nonlinear time series analysis, to obtain complementary information on hemispheric asymmetries in dynamical properties. Our analysis provides deep insights into the potential and limitations of this method, revealing a complex interplay between factors relating to statistical and dynamical properties, i.e., effects due to the probability distribution and the regularity of observed fluctuations. We demonstrate that temporal changes in the hemispheric predominance of the graph properties lag those directly associated with the total hemispheric sunspot areas. Our findings open a new dynamical perspective on studying the north-south sunspot asymmetry, which is to be further explored in future work

Long-term changes in the north–south asymmetry of solar activity : a nonlinear dynamics characterization using visibility graphs

Peer reviewedPublisher PD

Cosmological Luminosity Evolution of QSO/AGN Population

We apply the observed optical/X-ray spectral states of the Galactic black hole candidates (GBHCs) to the cosmological QSO luminosity evolution under the assumptions that QSOs and GBHCs are powered by similar accretion processes and that their emission mechanisms are also similar. The QSO luminosity function (LF) evolution in various energy bands is strongly affected by the spectral evolution which is tightly correlated with the luminosity evolution. We generate a random sample of QSOs born nearly synchronously by allowing the QSOs to have redshifts in a narrow range around an initial high redshift, black hole masses according to a power-law, and mass accretion rates near Eddington rates. The QSOs evolve as a single long-lived population on the cosmological time scale. The pure luminosity evolution results in distinct luminosity evolution features due to the strong spectral evolution. Most notably, different energy bands (optical/UV, soft X-ray, and hard X-ray) show different evolutionary trends and the hard X-ray LF in particular shows an apparent reversal of the luminosity evolution (from decreasing to increasing luminosity) at low redshifts, which is not seen in the conventional pure luminosity evolution scenario without spectral evolution. The resulting mass function of black holes (BHs), which is qualitatively consistent with the observed QSO LF evolution, shows that QSO remnants are likely to be found as BHs with masses in the range 10**8-5x10**10 solar masses. The long-lived single population of QSOs are expected to leave their remnants as supermassive BHs residing in rare, giant elliptical galaxies.Comment: 9 pages, 2 figures, ApJ

HLA gene expression is altered in whole blood and placenta from women who later developed preeclampsia

Preeclampsia is a multi-system disease that significantly contributes to maternal and fetal morbidity and mortality. In this study, we used a non-biased microarray approach to identify dysregulated genes in maternal whole blood samples which may be associated with the development of preeclampsia. Whole blood samples were obtained at 28 weeks of gestation from 5 women who later developed preeclampsia (cases) and 10 matched women with normotensive pregnancies (controls). Placenta samples were obtained from an independent cohort of 19 women with preeclampsia matched with 19 women with normotensive pregnancies. We studied gene expression profiles using Illumina microarray in blood and validated changes in gene expression in whole blood and placenta tissue by qPCR. We found a transcriptional profile differentiating cases from controls; 236 genes were significantly dysregulated in blood from women who developed preeclampsia. Functional annotation of microarray results indicated that most of the genes found to be dysregulated were involved in inflammatory pathways. Whilst general trends were preserved, only HLA-A was validated in whole blood samples from cases using qPCR (2.30 ± 0.9 fold change) whereas in placental tissue HLA-DRB1 expression was found to be significantly increased in samples from women with preeclampsia (5.88 ± 2.24 fold change). We have identified that HLA-A is up-regulated in the circulation of women who went on to develop preeclampsia. In placenta of women with preeclampsia we identified that HLA-DRB1 is up-regulated. Our data provide further evidence for involvement of the HLA gene family in the pathogenesis of preeclampsia

Recurrence-based time series analysis by means of complex network methods

Complex networks are an important paradigm of modern complex systems sciences which allows quantitatively assessing the structural properties of systems composed of different interacting entities. During the last years, intensive efforts have been spent on applying network-based concepts also for the analysis of dynamically relevant higher-order statistical properties of time series. Notably, many corresponding approaches are closely related with the concept of recurrence in phase space. In this paper, we review recent methodological advances in time series analysis based on complex networks, with a special emphasis on methods founded on recurrence plots. The potentials and limitations of the individual methods are discussed and illustrated for paradigmatic examples of dynamical systems as well as for real-world time series. Complex network measures are shown to provide information about structural features of dynamical systems that are complementary to those characterized by other methods of time series analysis and, hence, substantially enrich the knowledge gathered from other existing (linear as well as nonlinear) approaches.Comment: To be published in International Journal of Bifurcation and Chaos (2011

Testing for correlation structures in short-term variabilities with long-term trends of multivariate time series

2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe