22 research outputs found
Galaxy and Mass Assembly (GAMA): Variation in galaxy structure across the green valley
Using a sample of 472 local Universe (z \u3c 0.06) galaxies in the stellar mass range 10.25 \u3c logM*/M⊙ \u3c 10.75, we explore the variation in galaxy structure as a function of morphology and galaxy colour. Our sample of galaxies is subdivided into red, green, and blue colour groups and into elliptical and non-elliptical (disk-type) morphologies. Using Kilo- Degree Survey (KiDS) and Visible and Infrared Survey Telescope for Astronomy (VISTA) Kilo-Degree Infrared Galaxy Survey (VIKING) derived postage stamp images, a group of eight volunteers visually classified bars, rings, morphological lenses, tidal streams, shells, and signs of merger activity for all systems. We find a significant surplus of rings (2.3s) and lenses (2.9s) in disk-type galaxies as they transition across the green valley. Combined, this implies a joint ring/lens green valley surplus significance of 3.3s relative to equivalent disk-types within either the blue cloud or the red sequence. We recover a bar fraction of ~44 per cent which remains flat with colour, however, we find that the presence of a bar acts to modulate the incidence of rings and (to a lesser extent) lenses, with rings in barred disk-type galaxies more common by ~20-30 percentage points relative to their unbarred counterparts, regardless of colour. Additionally, green valley disk-type galaxies with a bar exhibit a significant 3.0s surplus of lenses relative to their blue/red analogues. The existence of such structures rules out violent transformative events as the primary end-of-life evolutionary mechanism, with a more passive scenario the favoured candidate for the majority of galaxies rapidly transitioning across the green valley
Duality relations between spatial birth-death processes and diffusions in Hilbert space
Spatially dependent birth-death processes can be modelled by kinetic models such as the BBGKY hierarchy. Diffusion in infinite dimensional systems can be modelled with Brownian motion in Hilbert space. In this work Doi field theoretic formalism is utilised to establish dualities between these classes of processes. This enables path integral methods to calculate expectations of duality functions. These are exemplified with models ranging from stochastic cable signalling to jump-diffusion processes
Galaxy and Mass Assembly (GAMA): Variation in Galaxy Structure Across the Green Valley
Using a sample of 472 local Universe (z < 0.06) galaxies in the stellar mass range
10.25 < log M*/MG < 10.75, we explore the variation in galaxy structure as a function of morphology and galaxy colour. Our sample of galaxies is sub-divided into red, green and blue colour groups and into elliptical and non-elliptical (disk-type) morphologies.
Using KiDS and VIKING derived postage stamp images, a group of eight volunteers visually classified bars, rings, morphological lenses, tidal streams, shells and signs of merger activity for all systems. We find a significant surplus of rings (2.3σ) and lenses (2.9σ) in disk-type galaxies as they transition across the green valley. Combined, this implies a joint ring/lens green valley surplus significance of 3.3σ relative to equivalent disk-types within either the blue cloud or the red sequence. We recover a bar fraction of ∼ 44% which remains flat with colour, however, we find that the presence of a bar acts to modulate the incidence of rings and (to a lesser extent) lenses, with rings in barred disk-type galaxies more common by ∼ 20 − 30 percentage points relative to their unbarred counterparts, regardless of colour. Additionally, green valley disk-type galaxies with a bar exhibit a significant 3.0σ surplus of lenses relative to their blue/red analogues. The existence of such structures rules out violent transformative events as the primary end-of-life evolutionary mechanism, with a more passive scenario the favoured candidate for the majority of galaxies rapidly transitioning across the green valley.
Key words: galaxies: elliptical and lenticular, cD – galaxies: spiral – galaxies: evo- lution – galaxies: star formation – galaxies: statistics – galaxies: structur
Temperature Control of Fimbriation Circuit Switch in Uropathogenic Escherichia coli: Quantitative Analysis via Automated Model Abstraction
Uropathogenic Escherichia coli (UPEC) represent the predominant cause of urinary tract infections (UTIs). A key UPEC molecular virulence mechanism is type 1 fimbriae, whose expression is controlled by the orientation of an invertible chromosomal DNA element—the fim switch. Temperature has been shown to act as a major regulator of fim switching behavior and is overall an important indicator as well as functional feature of many urologic diseases, including UPEC host-pathogen interaction dynamics. Given this panoptic physiological role of temperature during UTI progression and notable empirical challenges to its direct in vivo studies, in silico modeling of corresponding biochemical and biophysical mechanisms essential to UPEC pathogenicity may significantly aid our understanding of the underlying disease processes. However, rigorous computational analysis of biological systems, such as fim switch temperature control circuit, has hereto presented a notoriously demanding problem due to both the substantial complexity of the gene regulatory networks involved as well as their often characteristically discrete and stochastic dynamics. To address these issues, we have developed an approach that enables automated multiscale abstraction of biological system descriptions based on reaction kinetics. Implemented as a computational tool, this method has allowed us to efficiently analyze the modular organization and behavior of the E. coli fimbriation switch circuit at different temperature settings, thus facilitating new insights into this mode of UPEC molecular virulence regulation. In particular, our results suggest that, with respect to its role in shutting down fimbriae expression, the primary function of FimB recombinase may be to effect a controlled down-regulation (rather than increase) of the ON-to-OFF fim switching rate via temperature-dependent suppression of competing dynamics mediated by recombinase FimE. Our computational analysis further implies that this down-regulation mechanism could be particularly significant inside the host environment, thus potentially contributing further understanding toward the development of novel therapeutic approaches to UPEC-caused UTIs
Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures
Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo
Massive Parallel NEMS Flow Restriction Fabricated Using Self-Aligned 3D-Crystallographic Nanolithography
We introduce a massive parallel NEMS flow restriction nano-slit array fabricated in a wafer scale process using self-aligned 3D-nanolithography on sharp convex corners created by anisotropic etching of the silicon crystal. The device consists of an array of 50.000 slits, all having a length of ∼360 nm and a width of ∼6 nm. A relatively low resistance (short pore throat) configuration ensures high throughput on the order of 25μ g/s at 4 bar differential pressure. A dedicated hierarchical mechanical design consisting of on-membrane supports within a larger support structure enables operation pressures over 6 bar
Delayed acceptance particle MCMC for exact inference in stochastic kinetic models
Recently-proposed particle MCMC methods provide a flexible way of performing
Bayesian inference for parameters governing stochastic kinetic models defined
as Markov (jump) processes (MJPs). Each iteration of the scheme requires an
estimate of the marginal likelihood calculated from the output of a sequential
Monte Carlo scheme (also known as a particle filter). Consequently, the method
can be extremely computationally intensive. We therefore aim to avoid most
instances of the expensive likelihood calculation through use of a fast
approximation. We consider two approximations: the chemical Langevin equation
diffusion approximation (CLE) and the linear noise approximation (LNA). Either
an estimate of the marginal likelihood under the CLE, or the tractable marginal
likelihood under the LNA can be used to calculate a first step acceptance
probability. Only if a proposal is accepted under the approximation do we then
run a sequential Monte Carlo scheme to compute an estimate of the marginal
likelihood under the true MJP and construct a second stage acceptance
probability that permits exact (simulation based) inference for the MJP. We
therefore avoid expensive calculations for proposals that are likely to be
rejected. We illustrate the method by considering inference for parameters
governing a Lotka-Volterra system, a model of gene expression and a simple
epidemic process.Comment: Statistics and Computing (to appear
Efficient particle MCMC for exact inference in stochastic biochemical network models through approximation of expensive likelihoods
Recently-proposed particle MCMC methods provide a flexible way of performing Bayesian inference for parameters governing stochastic kinetic models defined as Markov (jump) processes (MJPs). Each iteration of the scheme requires an estimate of the marginal likelihood calculated from the output of a sequential Monte Carlo scheme (also known as a particle filter). Consequently, the method can be extremely computationally intensive. We therefore aim to avoid most instances of the expensive likelihood calculation through use of a fast approximation. We consider two approximations: the chemical Langevin equation diffusion approximation (CLE) and the linear noise approximation (LNA). Either an estimate of the marginal likelihood under the CLE, or the tractable marginal likelihood under the LNA can be used to calculate a first step acceptance probability. Only if a proposal is accepted under the approximation do we then run a sequential Monte Carlo scheme to compute an estimate of the marginal likelihood under the true MJP and construct a second stage acceptance probability that permits exact (simulation based) inference for the MJP. We therefore avoid expensive calculations for proposals that are likely to be rejected. We illustrate the method by considering inference for parameters governing a Lotka–Volterra system, a model of gene expression and a simple epidemic process