Energy change in elastic solids due to a spherical or circular cavity, considering uncertain in put data

In the paper we consider topological derivative of shape functionals for elasticity, which is used to derive the worst and also the maximum range scenarios for behavior of elastic body in case of uncertain material parameters and loading. It turns out that both problems are connected, because the criteria describing this behavior have form of functionals depending on topological derivative of elastic energy. Therefore in the first part we describe the methodology of computing the topological derivative with some new additional conditions for shape functionals depending on stress. For the sake of fulness of presentation the explicit formulas for stress distribution around cavities are provided

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For this, we generate synthetic metabolic profiles for benchmarking purposes based on a well-established model for red blood cell metabolism. A variety of data sets is generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We apply ARACNE, a mainstream transcriptional networks reverse engineering algorithm, to these data sets and observe performance comparable to that obtained in the transcriptional domain, for which the algorithm was originally designed.Comment: 14 pages, 3 figures. Presented at the DIMACS Workshop on Dialogue on Reverse Engineering Assessment and Methods (DREAM), Sep 200

RuleMonkey: software for stochastic simulation of rule-based models

<p>Abstract</p> <p>Background</p> <p>The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen language (BNGL). A set of rules implicitly defines a (bio)chemical reaction network. The reaction network implied by a set of rules is often very large, and as a result, generation of the network implied by rules tends to be computationally expensive. Moreover, the cost of many commonly used methods for simulating network dynamics is a function of network size. Together these factors have limited application of the rule-based modeling approach. Recently, several methods for simulating rule-based models have been developed that avoid the expensive step of network generation. The cost of these "network-free" simulation methods is independent of the number of reactions implied by rules. Software implementing such methods is now needed for the simulation and analysis of rule-based models of biochemical systems.</p> <p>Results</p> <p>Here, we present a software tool called RuleMonkey, which implements a network-free method for simulation of rule-based models that is similar to Gillespie's method. The method is suitable for rule-based models that can be encoded in BNGL, including models with rules that have global application conditions, such as rules for intramolecular association reactions. In addition, the method is rejection free, unlike other network-free methods that introduce null events, i.e., steps in the simulation procedure that do not change the state of the reaction system being simulated. We verify that RuleMonkey produces correct simulation results, and we compare its performance against DYNSTOC, another BNGL-compliant tool for network-free simulation of rule-based models. We also compare RuleMonkey against problem-specific codes implementing network-free simulation methods.</p> <p>Conclusions</p> <p>RuleMonkey enables the simulation of rule-based models for which the underlying reaction networks are large. It is typically faster than DYNSTOC for benchmark problems that we have examined. RuleMonkey is freely available as a stand-alone application <url>http://public.tgen.org/rulemonkey</url>. It is also available as a simulation engine within GetBonNie, a web-based environment for building, analyzing and sharing rule-based models.</p

The Evolution of the Intracluster Medium Metallicity in Sunyaev-Zel'dovich-Selected Galaxy Clusters at 0 < z < 1.5

We present the results of an X-ray spectral analysis of 153 galaxy clusters observed with the Chandra, XMM-Newton, and Suzaku space telescopes. These clusters, which span 0 < z < 1.5, were drawn from a larger, mass-selected sample of galaxy clusters discovered in the 2500 square degree South Pole Telescope Sunyaev Zel'dovich (SPT-SZ) survey. With a total combined exposure time of 9.1 Ms, these data yield the strongest constraints to date on the evolution of the metal content of the intracluster medium (ICM). We find no evidence for strong evolution in the global (r<R500) ICM metallicity (dZ/dz = -0.06 +/- 0.04 Zsun), with a mean value at z=0.6 of = 0.23 +/- 0.01 Zsun and a scatter of 0.08 +/- 0.01 Zsun. These results imply that >60% of the metals in the ICM were already in place at z=1 (at 95% confidence), consistent with the picture of an early (z>1) enrichment. We find, in agreement with previous works, a significantly higher mean value for the metallicity in the centers of cool core clusters versus non-cool core clusters. We find weak evidence for evolution in the central metallicity of cool core clusters (dZ/dz = -0.21 +/- 0.11 Zsun), which is sufficient to account for this enhanced central metallicity over the past ~10 Gyr. We find no evidence for metallicity evolution outside of the core (dZ/dz = -0.03 +/- 0.06 Zsun), and no significant difference in the core-excised metallicity between cool core and non-cool core clusters. This suggests that strong radio-mode AGN feedback does not significantly alter the distribution of metals at r>0.15R500. Given the limitations of current-generation X-ray telescopes in constraining the ICM metallicity at z>1, significant improvements on this work will likely require next-generation X-ray missions.Comment: 11 pages, 8 figures, 2 tables. Submitted to ApJ. Comments welcome

Star-Forming Brightest Cluster Galaxies at 0.25 < z < 1.25: A Transitioning Fuel Supply

We present a multi-wavelength study of 90 brightest cluster galaxies (BCGs) in a sample of galaxy clusters selected via the Sunyaev Zel'dovich effect by the South Pole Telescope, utilizing data from various ground- and space-based facilities. We infer the star formation rate (SFR) for the BCG in each cluster, based on the UV and IR continuum luminosity, as well as the [O II] emission line luminosity in cases where spectroscopy is available, finding 7 systems with SFR > 100 Msun/yr. We find that the BCG SFR exceeds 10 Msun/yr in 31 of 90 (34%) cases at 0.25 < z < 1.25, compared to ~1-5% at z ~ 0 from the literature. At z > 1, this fraction increases to 92(+6)(-31)%, implying a steady decrease in the BCG SFR over the past ~9 Gyr. At low-z, we find that the specific star formation rate in BCGs is declining more slowly with time than for field or cluster galaxies, most likely due to the replenishing fuel from the cooling ICM in relaxed, cool core clusters. At z > 0.6, the correlation between cluster central entropy and BCG star formation - which is well established at z ~ 0 - is not present. Instead, we find that the most star-forming BCGs at high-z are found in the cores of dynamically unrelaxed clusters. We investigate the rest-frame near-UV morphology of a subsample of the most star-forming BCGs using data from the Hubble Space Telescope, finding complex, highly asymmetric UV morphologies on scales as large as ~50-60 kpc. The high fraction of star-forming BCGs hosted in unrelaxed, non-cool core clusters at early times suggests that the dominant mode of fueling star formation in BCGs may have recently transitioned from galaxy-galaxy interactions to ICM cooling.Comment: 20 pages, 10 figures. Submitted for publication in ApJ. Comments welcom

Galaxy populations in the 26 most massive galaxy clusters in the South Pole Telescope SPT-SZ survey

We present a study of the optical properties of the 26 most massive galaxy clusters within the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) 2500 deg2 survey spanning the redshift range 0.10 < z < 1.13. We measure the radial profiles, the luminosity functions (LFs), and the halo occupation numbers (HONs) using optical data of typical depth m* + 2. The stacked radial profiles are consistent with a Navarro–Frenk–White profile of concentration 2.84+0.40−0.37 for the red sequence (RS) and 2.36+0.38−0.35 for the total population. Stacking the data in multiple redshift bins shows slight redshift evolution in the concentration when both the total population is used, and when only RS galaxies are used (at 2.1σ and 2.8σ, respectively). The stacked LF shows a faint end slope α=−1.06+0.04−0.03 for the total and α=−0.80+0.04−0.03 for the RS population. The redshift evolution of m* is consistent with a passively evolving composite stellar population (CSP) model. Adopting the CSP model predictions, we explore the redshift evolution of the Schechter parameters α and ϕ*. We find α for the total population to be consistent with no evolution (0.3σ), and mildly significant evidence of evolution for the red galaxies (1.1–2.1σ). The data show that the density ϕ*/E2(z) decreases with redshift, in tension with the self-similar expectation at a 2.4σ level for the total population. The measured HON–mass relation has a lower normalization than previous low redshift studies. Finally, our data support HON redshift evolution at a 2.1σ level, with clusters at higher redshift containing fewer galaxies than their low-z counterparts

Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena.Comment: 18 pages, 5 figure

Mass Calibration and Cosmological Analysis of the SPT-SZ Galaxy Cluster Sample Using Velocity Dispersion σv\sigma_v and X-ray YXY_\textrm{X} Measurements

We present a velocity dispersion-based mass calibration of the South Pole Telescope Sunyaev-Zel'dovich effect survey (SPT-SZ) galaxy cluster sample. Using a homogeneously selected sample of 100 cluster candidates from 720 deg2 of the survey along with 63 velocity dispersion ($\sigma_v$) and 16 X-ray Yx measurements of sample clusters, we simultaneously calibrate the mass-observable relation and constrain cosmological parameters. The calibrations using $\sigma_v$ and Yx are consistent at the $0.6\sigma$ level, with the $\sigma_v$ calibration preferring ~16% higher masses. We use the full cluster dataset to measure $\sigma_8(\Omega_ m/0.27)^{0.3}=0.809\pm0.036$. The SPT cluster abundance is lower than preferred by either the WMAP9 or Planck+WMAP9 polarization (WP) data, but assuming the sum of the neutrino masses is $\sum m_\nu=0.06$ eV, we find the datasets to be consistent at the 1.0$\sigma$ level for WMAP9 and 1.5$\sigma$ for Planck+WP. Allowing for larger $\sum m_\nu$ further reconciles the results. When we combine the cluster and Planck+WP datasets with BAO and SNIa, the preferred cluster masses are $1.9\sigma$ higher than the Yx calibration and $0.8\sigma$ higher than the $\sigma_v$ calibration. Given the scale of these shifts (~44% and ~23% in mass, respectively), we execute a goodness of fit test; it reveals no tension, indicating that the best-fit model provides an adequate description of the data. Using the multi-probe dataset, we measure $\Omega_ m=0.299\pm0.009$ and $\sigma_8=0.829\pm0.011$. Within a $\nu$CDM model we find $\sum m_\nu = 0.148\pm0.081$ eV. We present a consistency test of the cosmic growth rate. Allowing both the growth index $\gamma$ and the dark energy equation of state parameter $w$ to vary, we find $\gamma=0.73\pm0.28$ and $w=-1.007\pm0.065$, demonstrating that the expansion and the growth histories are consistent with a LCDM model ($\gamma=0.55; \,w=-1$).Comment: Accepted by ApJ (v2 is accepted version); 17 pages, 6 figure