2,585 research outputs found

    Minimizing the effect of sinusoidal trends in detrended fluctuation analysis

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    The detrended fluctuation analysis (DFA) [Peng et al., 1994] and its extensions (MF-DFA) [Kantelhardt et al., 2002] have been used extensively to determine possible long-range correlations in self-affine signals. While the DFA has been claimed to be a superior technique, recent reports have indicated its susceptibility to trends in the data. In this report, a smoothing filter is proposed to minimize the effect of sinusoidal trends and distortion in the log-log plots obtained by DFA and MF-DFA techniques

    Time Delay Interferometry for LISA with one arm dysfunctional

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    In order to attain the requisite sensitivity for LISA - a joint space mission of the ESA and NASA- the laser frequency noise must be suppressed below the secondary noises such as the optical path noise, acceleration noise etc. By combining six appropriately time-delayed data streams containing fractional Doppler shifts - a technique called time delay interferometry (TDI) - the laser frequency noise may be adequately suppressed. We consider the general model of LISA where the armlengths vary with time, so that second generation TDI are relevant. However, we must envisage the possibility, that not all the optical links of LISA will be operating at all times, and therefore, we here consider the case of LISA operating with two arms only. As shown earlier in the literature, obtaining even approximate solutions of TDI to the general problem is very difficult. Since here only four optical links are relevant, the algebraic problem simplifies considerably. We are then able to exhibit a large number of solutions (from mathematical point of view an infinite number) and further present an algorithm to generate these solutions

    Potential barrier lowering and electrical transport at the LaAlO3_{3}/SrTiO3_{3} heterointerface

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    Using a combination of vertical transport measurements across and lateral transport measurements along the LaAlO3_{3}/SrTiO3_{3} heterointerface, we demonstrate that significant potential barrier lowering and band bending are the cause of interfacial metallicity. Barrier lowering and enhanced band bending extends over 2.5 nm into LaAlO3_{3} as well as SrTiO3_{3}. We explain origins of high-temperature carrier saturation, lower carrier concentration, and higher mobility in the sample with the thinnest LaAlO3_{3} film on a SrTiO3_{3} substrate. Lateral transport results suggest that parasitic interface scattering centers limit the low-temperature lateral electron mobility of the metallic channel.Comment: 10 pages, 3 figures, and 1 tabl

    Exact Phase Diagram of a model with Aggregation and Chipping

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    We revisit a simple lattice model of aggregation in which masses diffuse and coalesce upon contact with rate 1 and every nonzero mass chips off a single unit of mass to a randomly chosen neighbour with rate ww. The dynamics conserves the average mass density ρ\rho and in the stationary state the system undergoes a nonequilibrium phase transition in the (ρw)(\rho-w) plane across a critical line ρc(w)\rho_c(w). In this paper, we show analytically that in arbitrary spatial dimensions, ρc(w)=w+11\rho_c(w) = \sqrt{w+1}-1 exactly and hence, remarkably, independent of dimension. We also provide direct and indirect numerical evidence that strongly suggest that the mean field asymptotic answer for the single site mass distribution function and the associated critical exponents are super-universal, i.e., independent of dimension.Comment: 11 pages, RevTex, 3 figure

    Stochastic model of transcription factor-regulated gene expression

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    We consider a stochastic model of transcription factor (TF)-regulated gene expression. The model describes two genes: Gene A and Gene B which synthesize the TFs and the target gene proteins respectively. We show through analytic calculations that the TF fluctuations have a significant effect on the distribution of the target gene protein levels when the mean TF level falls in the highest sensitive region of the dose-response curve. We further study the effect of reducing the copy number of Gene A from two to one. The enhanced TF fluctuations yield results different from those in the deterministic case. The probability that the target gene protein level exceeds a threshold value is calculated with a knowledge of the probability density functions associated with the TF and target gene protein levels. Numerical simulation results for a more detailed stochastic model are shown to be in agreement with those obtained through analytic calculations. The relevance of these results in the context of the genetic disorder haploinsufficiency is pointed out. Some experimental observations on the haploinsufficiency of the tumour suppressor gene, Nkx3.1, are explained with the help of the stochastic model of TF-regulated gene expression.Comment: 17 pages, 11 figures. Accepted for publication in Physical Biolog

    Breakdown of Kolmogorov scaling in models of cluster aggregation with deposition

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    The steady state of the model of cluster aggregation with deposition is characterized by a constant flux of mass directed from small masses towards large masses. It can therefore be studied using phenomenological theories of turbulence, such as Kolmogorov's 1941 theory. On the other hand, the large scale behavior of the aggregation model in dimensions lower than or equal to two is governed by a perturbative fixed point of the renormalization group flow, which enables an analytic study of the scaling properties of correlation functions in the steady state. In this paper, we show that the correlation functions have multifractal scaling, which violates linear Kolmogorov scaling. The analytical results are verified by Monte Carlo simulations.Comment: 5 pages 4 figure

    Oral Apolipoprotein A-I Mimetic D-4F Lowers HDL-Inflammatory Index in High-Risk Patients: A First-in-Human Multiple-Dose, Randomized Controlled Trial.

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    A single dose of the apolipoprotein (apo)A-I mimetic peptide D-4F rendered high-density lipoprotein (HDL) less inflammatory, motivating the first multiple-dose study. We aimed to assess safety/tolerability, pharmacokinetics, and pharmacodynamics of daily, orally administered D-4F. High-risk coronary heart disease (CHD) subjects added double-blinded placebo or D-4F to statin for 13 days, randomly assigned 1:3 to ascending cohorts of 100, 300, then 500 mg (n = 62; 46 men/16 women). D-4F was safe and well-tolerated. Mean ± SD plasma D-4F area under the curve (AUC, 0-8h) was 6.9 ± 5.7 ng/mL*h (100 mg), 22.7 ± 19.6 ng/mL*h (300 mg), and 104.0 ± 60.9 ng/mL*h (500 mg) among men, higher among women. Whereas placebo dropped HDL inflammatory index (HII) 28% 8 h postdose (range, 1.25-0.86), 300-500 mg D-4F effectively halved HII: 1.35-0.57 and 1.22-0.63, respectively (P \u3c 0.03 vs. placebo). Oral D-4F peptide dose predicted HII suppression, whereas plasma D-4F exposure was dissociated, suggesting plasma penetration is unnecessary. In conclusion, oral D-4F dosing rendered HDL less inflammatory, affirming oral D-4F as a potential therapy to improve HDL function

    Exact Tagged Particle Correlations in the Random Average Process

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    We study analytically the correlations between the positions of tagged particles in the random average process, an interacting particle system in one dimension. We show that in the steady state the mean squared auto-fluctuation of a tracer particle grows subdiffusively as sigma2(t) t1/2sigma^2(t) ~ t^{1/2} for large time t in the absence of external bias, but grows diffusively sigma2(t) tsigma^2(t) ~ t in the presence of a nonzero bias. The prefactors of the subdiffusive and diffusive growths as well as the universal scaling function describing the crossover between them are computed exactly. We also compute sigmar2(t)sigma_r^2(t), the mean squared fluctuation in the position difference of two tagged particles separated by a fixed tag shift r in the steady state and show that the external bias has a dramatic effect in the time dependence of sigmar2(t)sigma_r^2(t). For fixed r, sigmar2(t)sigma_r^2(t) increases monotonically with t in absence of bias but has a non-monotonic dependence on t in presence of bias. Similarities and differences with the simple exclusion process are also discussed.Comment: 10 pages, 2 figures, revte
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