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    On robust stability of stochastic genetic regulatory networks with time delays: A delay fractioning approach

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    Copyright [2009] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.Robust stability serves as an important regulation mechanism in system biology and synthetic biology. In this paper, the robust stability analysis problem is investigated for a class of nonlinear delayed genetic regulatory networks with parameter uncertainties and stochastic perturbations. The nonlinear function describing the feedback regulation satisfies the sector condition, the time delays exist in both translation and feedback regulation processes, and the state-dependent Brownian motions are introduced to reflect the inherent intrinsic and extrinsic noise perturbations. The purpose of the addressed stability analysis problem is to establish some easy-to-verify conditions under which the dynamics of the true concentrations of the messenger ribonucleic acid (mRNA) and protein is asymptotically stable irrespective of the norm-bounded modeling errors. By utilizing a new Lyapunov functional based on the idea of “delay fractioning”, we employ the linear matrix inequality (LMI) technique to derive delay-dependent sufficient conditions ensuring the robust stability of the gene regulatory networks. Note that the obtained results are formulated in terms of LMIs that can easily be solved using standard software packages. Simulation examples are exploited to illustrate the effectiveness of the proposed design procedures

    Cosmological model of the interaction between dark matter and dark energy

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    In this paper, we test the dark matter-dark energy interacting cosmological model with a dynamic equation of state wDE(z)=w0+w1z/(1+z)w_{DE}(z)=w_{0}+w_{1}z/(1+z), using type Ia supernovae (SNe Ia), Hubble parameter data, baryonic acoustic oscillation (BAO) measurements, and the cosmic microwave background (CMB) observation. This interacting cosmological model has not been studied before. The best-fitted parameters with 1σ1 \sigma uncertainties are δ=0.022±0.006\delta=-0.022 \pm 0.006, ΩDM0=0.213±0.008\Omega_{DM}^{0}=0.213 \pm 0.008, w0=1.210±0.033w_0 =-1.210 \pm 0.033 and w1=0.872±0.072w_1=0.872 \pm 0.072 with χmin2/dof=0.990\chi^2_{min}/dof = 0.990. At the 1σ1 \sigma confidence level, we find δ<0\delta<0, which means that the energy transfer prefers from dark matter to dark energy. We also find that the SNe Ia are in tension with the combination of CMB, BAO and Hubble parameter data. The evolution of ρDM/ρDE\rho_{DM}/\rho_{DE} indicates that this interacting model is a good approach to solve the coincidence problem, because the ρDE\rho_{DE} decrease with scale factor aa. The transition redshift is ztr=0.63±0.07z_{tr}=0.63 \pm 0.07 in this model.Comment: 6 pages, 6 figures, published in A&

    The SDSS Galaxy Angular Two-Point Correlation Function

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    We present the galaxy two-point angular correlation function for galaxies selected from the seventh data release of the Sloan Digital Sky Survey. The galaxy sample was selected with rr-band apparent magnitudes between 17 and 21; and we measure the correlation function for the full sample as well as for the four magnitude ranges: 17-18, 18-19, 19-20, and 20-21. We update the flag criteria to select a clean galaxy catalog and detail specific tests that we perform to characterize systematic effects, including the effects of seeing, Galactic extinction, and the overall survey uniformity. Notably, we find that optimally we can use observed regions with seeing < 1\farcs5, and rr-band extinction < 0.13 magnitudes, smaller than previously published results. Furthermore, we confirm that the uniformity of the SDSS photometry is minimally affected by the stripe geometry. We find that, overall, the two-point angular correlation function can be described by a power law, ω(θ)=Aωθ(1γ)\omega(\theta) = A_\omega \theta^{(1-\gamma)} with γ1.72\gamma \simeq 1.72, over the range 0\fdg005--10\degr. We also find similar relationships for the four magnitude subsamples, but the amplitude within the same angular interval for the four subsamples is found to decrease with fainter magnitudes, in agreement with previous results. We find that the systematic signals are well below the galaxy angular correlation function for angles less than approximately 5\degr, which limits the modeling of galaxy angular correlations on larger scales. Finally, we present our custom, highly parallelized two-point correlation code that we used in this analysis.Comment: 22 pages, 17 figures, accepted by MNRA
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