Optimized cross-slot flow geometry for microfluidic extension rheometry

A precision-machined cross-slot flow geometry with a shape that has been optimized by numerical simulation of the fluid kinematics is fabricated and used to measure the extensional viscosity of a dilute polymer solution. Full-field birefringence microscopy is used to monitor the evolution and growth of macromolecular anisotropy along the stagnation point streamline, and we observe the formation of a strong and uniform birefringent strand when the dimensionless flow strength exceeds a critical Weissenberg number Wicrit 0:5. Birefringence and bulk pressure drop measurements provide self consistent estimates of the planar extensional viscosity of the fluid over a wide range of deformation rates (26 s1 "_ 435 s1) and are also in close agreement with numerical simulations performed by using a finitely extensible nonlinear elastic dumbbell model

The Family Name as Socio-Cultural Feature and Genetic Metaphor: From Concepts to Methods

A recent workshop entitled The Family Name as Socio-Cultural Feature and Genetic Metaphor: From Concepts to Methods was held in Paris in December 2010, sponsored by the French National Centre for Scientific Research (CNRS) and by the journal Human Biology. This workshop was intended to foster a debate on questions related to the family names and to compare different multidisciplinary approaches involving geneticists, historians, geographers, sociologists and social anthropologists. This collective paper presents a collection of selected communications

Efficient History Matching of a High Dimensional Individual-Based HIV Transmission Model

History matching is a model (pre-)calibration method that has been applied to computer models from a wide range of scientific disciplines. In this work we apply history matching to an individual-based epidemiological model of HIV that has 96 input and 50 output parameters, a model of much larger scale than others that have been calibrated before using this or similar methods. Apart from demonstrating that history matching can analyze models of this complexity, a central contribution of this work is that the history match is carried out using linear regression, a statistical tool that is elementary and easier to implement than the Gaussian process--based emulators that have previously been used. Furthermore, we address a practical difficulty with history matching, namely, the sampling of tiny, nonimplausible spaces, by introducing a sampling algorithm adjusted to the specific needs of this method. The effectiveness and simplicity of the history matching method presented here shows that it is a useful tool for the calibration of computationally expensive, high dimensional, individual-based models

Bayesian history matching of complex infectious disease models using emulation: A tutorial and a case study on HIV in Uganda

Advances in scientific computing have allowed the development of complex models that are being routinely applied to problems in disease epidemiology, public health and decision making. The utility of these models depends in part on how well they can reproduce empirical data. However, fitting such models to real world data is greatly hindered both by large numbers of input and output parameters, and by long run times, such that many modelling studies lack a formal calibration methodology. We present a novel method that has the potential to improve the calibration of complex infectious disease models (hereafter called simulators). We present this in the form of a tutorial and a case study where we history match a dynamic, event-driven, individual-based stochastic HIV simulator, using extensive demographic, behavioural and epidemiological data available from Uganda. The tutorial describes history matching and emulation. History matching is an iterative procedure that reduces the simulator's input space by identifying and discarding areas that are unlikely to provide a good match to the empirical data. History matching relies on the computational efficiency of a Bayesian representation of the simulator, known as an emulator. Emulators mimic the simulator's behaviour, but are often several orders of magnitude faster to evaluate. In the case study, we use a 22 input simulator, fitting its 18 outputs simultaneously. After 9 iterations of history matching, a non-implausible region of the simulator input space was identified that was times smaller than the original input space. Simulator evaluations made within this region were found to have a 65% probability of fitting all 18 outputs. History matching and emulation are useful additions to the toolbox of infectious disease modellers. Further research is required to explicitly address the stochastic nature of the simulator as well as to account for correlations between outputs

The Spectral Energy Distribution of Powerful Starburst Galaxies I: Modelling the Radio Continuum

We have acquired radio continuum data between 70\,MHz and 48\,GHz for a sample of 19 southern starburst galaxies at moderate redshifts ($0.067 < z < 0.227$) with the aim of separating synchrotron and free-free emission components. Using a Bayesian framework we find the radio continuum is rarely characterised well by a single power law, instead often exhibiting low frequency turnovers below 500\,MHz, steepening at mid-to-high frequencies, and a flattening at high frequencies where free-free emission begins to dominate over the synchrotron emission. These higher order curvature components may be attributed to free-free absorption across multiple regions of star formation with varying optical depths. The decomposed synchrotron and free-free emission components in our sample of galaxies form strong correlations with the total-infrared bolometric luminosities. Finally, we find that without accounting for free-free absorption with turnovers between 90 to 500\,MHz the radio-continuum at low frequency ($\nu < 200$\,MHz) could be overestimated by upwards of a factor of twelve if a simple power law extrapolation is used from higher frequencies. The mean synchrotron spectral index of our sample is constrained to be $\alpha=-1.06$, which is steeper then the canonical value of $-0.8$ for normal galaxies. We suggest this may be caused by an intrinsically steeper cosmic ray distribution

The Spectral Energy Distribution of Powerful Starburst Galaxies I : Modelling the Radio Continuum

This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society. © 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.We have acquired radio-continuum data between 70MHz and 48 GHz for a sample of 19 southern starburst galaxies at moderate redshifts (0.067 < z < 0.227) with the aim of separating synchrotron and free-free emission components. Using a Bayesian framework, we find the radio continuum is rarely characterized well by a single power law, instead often exhibiting lowfrequency turnovers below 500 MHz, steepening at mid to high frequencies, and a flattening at high frequencies where free-free emission begins to dominate over the synchrotron emission. These higher order curvature components may be attributed to free-free absorption across multiple regions of star formation with varying optical depths. The decomposed synchrotron and free-free emission components in our sample of galaxies form strong correlations with the total-infrared bolometric luminosities. Finally, we find that without accounting for free-free absorption with turnovers between 90 and 500MHz the radio continuum at low frequency (v < 200 MHz) could be overestimated by upwards of a factor of 12 if a simple power-law extrapolation is used from higher frequencies. The mean synchrotron spectral index of our sample is constrained to be α = -1.06, which is steeper than the canonical value of -0.8 for normal galaxies. We suggest this may be caused by an intrinsically steeper cosmic ray distribution.Peer reviewe

Murchison Widefield Array and XMM-Newton observations of the Galactic supernova remnant G5.9+3.1

In this paper we discuss the radio continuum and X-ray properties of the so-far poorly studied Galactic supernova remnant (SNR) G5.9+3.1. We present the radio spectral energy distribution (SED) of the Galactic SNR G5.9+3.1 obtained with the Murchison Widefield Array (MWA). Combining these new observations with the surveys at other radio continuum frequencies, we discuss the integrated radio continuum spectrum of this particular remnant. We have also analyzed an archival XMM-Newton observation, which represents the first detection of X-ray emission from this remnant. The SNR SED is very well explained by a simple power-law relation. The synchrotron radio spectral index of G5.9+3.1, is estimated to be 0.42$\pm$0.03 and the integrated flux density at 1GHz to be around 2.7Jy. Furthermore, we propose that the identified point radio source, located centrally inside the SNR shell, is most probably a compact remnant of the supernova explosion. The shell-like X-ray morphology of G5.9+3.1 as revealed by XMM-Newton broadly matches the spatial distribution of the radio emission, where the radio-bright eastern and western rims are also readily detected in the X-ray while the radio-weak northern and southern rims are weak or absent in the X-ray. Extracted MOS1+MOS2+PN spectra from the whole SNR as well as the north, east, and west rims of the SNR are fit successfully with an optically thin thermal plasma model in collisional ionization equilibrium with a column density N_H~0.80x$10^{22}$ cm$^{-2}$ and fitted temperatures spanning the range kT~0.14-0.23keV for all of the regions. The derived electron number densities n_e for the whole SNR and the rims are also roughly comparable (ranging from ~$0.20f^{-1/2}$ cm$^{-3}$ to ~$0.40f^{-1/2}$ cm$^{-3}$, where f is the volume filling factor). We also estimate the swept-up mass of the X-ray emitting plasma associated with G5.9+3.1 to be ~$46f^{-1/2}M_{\odot}$.Comment: Accepted for publication in A&