The role of fingerprints in the coding of tactile information probed with a biomimetic sensor

In humans, the tactile perception of fine textures (spatial scale <200 micrometers) is mediated by skin vibrations generated as the finger scans the surface. To establish the relationship between texture characteristics and subcutaneous vibrations, a biomimetic tactile sensor has been designed whose dimensions match those of the fingertip. When the sensor surface is patterned with parallel ridges mimicking the fingerprints, the spectrum of vibrations elicited by randomly textured substrates is dominated by one frequency set by the ratio of the scanning speed to the interridge distance. For human touch, this frequency falls within the optimal range of sensitivity of Pacinian afferents, which mediate the coding of fine textures. Thus, fingerprints may perform spectral selection and amplification of tactile information that facilitate its processing by specific mechanoreceptors.Comment: 25 pages, 11 figures, article + supporting materia

Searching for Galactic White Dwarf Binaries in Mock LISA Data using an F-Statistic Template Bank

We describe an F-statistic search for continuous gravitational waves from galactic white-dwarf binaries in simulated LISA Data. Our search method employs a hierarchical template-grid based exploration of the parameter space. In the first stage, candidate sources are identified in searches using different simulated laser signal combinations (known as TDI variables). Since each source generates a primary maximum near its true "Doppler parameters" (intrinsic frequency and sky position) as well as numerous secondary maxima of the F-statistic in Doppler parameter space, a search for multiple sources needs to distinguish between true signals and secondary maxima associated with other, "louder" signals. Our method does this by applying a coincidence test to reject candidates which are not found at nearby parameter space positions in searches using each of the three TDI variables. For signals surviving the coincidence test, we perform a fully coherent search over a refined parameter grid to provide an accurate parameter estimation for the final candidates. Suitably tuned, the pipeline is able to extract 1989 true signals with only 5 false alarms. The use of the rigid adiabatic approximation allows recovery of signal parameters with errors comparable to statistical expectations, although there is still some systematic excess with respect to statistical errors expected from Gaussian noise. An experimental iterative pipeline with seven rounds of signal subtraction and re-analysis of the residuals allows us to increase the number of signals recovered to a total of 3419 with 29 false alarms.Comment: 29 pages, 11 figures; submitted to Classical and Quantum Gravit

Structure and Metal Binding Properties of ZnuA, a Periplasmic Zinc Transporter from \u3cem\u3eEscherichia coli\u3c/em\u3e

ZnuA is the periplasmic Zn2+-binding protein associated with the high-affinity ATP-binding cassette ZnuABC transporter from Escherichia coli. Although several structures of ZnuA and its homologs have been determined, details regarding metal ion stoichiometry, affinity, and specificity as well as the mechanism of metal uptake and transfer remain unclear. The crystal structures of E. coli ZnuA (Eco-ZnuA) in the apo, Zn2+-bound, and Co2+-bound forms have been determined. ZnZnuA binds at least two metal ions. The first, observed previously in other structures, is coordinated tetrahedrally by Glu59, His60, His143, and His207. Replacement of Zn2+ with Co2+ results in almost identical coordination geometry at this site. The second metal binding site involves His224 and several yet to be identified residues from the His-rich loop that is unique to Zn2+ periplasmic metal binding receptors. Electron paramagnetic resonance and X-ray absorption spectroscopic data on CoZnuA provide additional insight into possible residues involved in this second site. The second site is also detected by metal analysis and circular dichroism (CD) titrations. Eco-ZnuA binds Zn2+ (estimated K d \u3c 20 nM), Co2+, Ni2+, Cu2+, Cu+, and Cd2+, but not Mn2+. Finally, conformational changes upon metal binding observed in the crystal structures together with fluorescence and CD data indicate that only Zn2+ substantially stabilizes ZnuA and might facilitate recognition of ZnuB and subsequent metal transfer

Dynactin-dependent cortical dynein and spherical spindle shape correlate temporally with meiotic spindle rotation in Caenorhabditis elegans.

Oocyte meiotic spindles orient with one pole juxtaposed to the cortex to facilitate extrusion of chromosomes into polar bodies. In Caenorhabditis elegans, these acentriolar spindles initially orient parallel to the cortex and then rotate to the perpendicular orientation. To understand the mechanism of spindle rotation, we characterized events that correlated temporally with rotation, including shortening of the spindle in the pole-to pole axis, which resulted in a nearly spherical spindle at rotation. By analyzing large spindles of polyploid C. elegans and a related nematode species, we found that spindle rotation initiated at a defined spherical shape rather than at a defined spindle length. In addition, dynein accumulated on the cortex just before rotation, and microtubules grew from the spindle with plus ends outward during rotation. Dynactin depletion prevented accumulation of dynein on the cortex and prevented spindle rotation independently of effects on spindle shape. These results support a cortical pulling model in which spindle shape might facilitate rotation because a sphere can rotate without deforming the adjacent elastic cytoplasm. We also present evidence that activation of spindle rotation is promoted by dephosphorylation of the basic domain of p150 dynactin

The Southern Zagros Collisional Orogen: New Insights From Transdimensional Trees Inversion of Seismic Noise

Imaging and resolving the lateral continuity of 3-D crustal structures enhances our ability to interpret seismicity, and to understand how orogens are created. We apply a Bayesian, hierarchical inversion approach based on a transdimensional trees-structured wavelet parameterisation to recover phase-velocity maps at 2-40 second periods. We then invert phase-velocity dispersion to constrain a 3-D shear-velocity model of the crust beneath south-central Iran. Together with accurate earthquake centroid depths and focal mechanisms, the pattern of 3-D velocity variations supports recent suggestions that most large earthquakes in the Zagros occur within the lower sedimentary cover, or close to the sediment-basement interface. Furthermore, we fi nd evidence for Arabian basement underthrusting beneath central Iran, although only in one location does it appear to generate earthquakes. Our new 3-D tomographic model clarifi es and throws new light on the crustal structure of the SE Zagros and its relation to seismicity and active faulting.NERC Horizon 2020 Petroleum Institute Research Centr

LISA Data Analysis using MCMC methods

The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50,000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analyses and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we super-cool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions.Comment: 14 pages, 7 figure

Can Modus Vivendi Save Liberalism from Moralism? A Critical Assessment of John Gray’s Political Realism

This chapter assesses John Gray’s modus vivendi-based justification for liberalism. I argue that his approach is preferable to the more orthodox deontological or teleological justificatory strategies, at least because of the way it can deal with the problem of diversity. But then I show how that is not good news for liberalism, for grounding liberal political authority in a modus vivendi undermines liberalism’s aspiration to occupy a privileged normative position vis-à-vis other kinds of regimes. So modus vivendi can save liberalism from moralism, but at cost many liberals will not be prepared to pay

Studying stellar binary systems with the Laser Interferometer Space Antenna using Delayed Rejection Markov chain Monte Carlo methods

Bayesian analysis of LISA data sets based on Markov chain Monte Carlo methods has been shown to be a challenging problem, in part due to the complicated structure of the likelihood function consisting of several isolated local maxima that dramatically reduces the efficiency of the sampling techniques. Here we introduce a new fully Markovian algorithm, a Delayed Rejection Metropolis-Hastings Markov chain Monte Carlo method, to efficiently explore these kind of structures and we demonstrate its performance on selected LISA data sets containing a known number of stellar-mass binary signals embedded in Gaussian stationary noise.Comment: 12 pages, 4 figures, accepted in CQG (GWDAW-13 proceedings

Extracting galactic binary signals from the first round of Mock LISA Data Challenges

We report on the performance of an end-to-end Bayesian analysis pipeline for detecting and characterizing galactic binary signals in simulated LISA data. Our principal analysis tool is the Blocked-Annealed Metropolis Hasting (BAM) algorithm, which has been optimized to search for tens of thousands of overlapping signals across the LISA band. The BAM algorithm employs Bayesian model selection to determine the number of resolvable sources, and provides posterior distribution functions for all the model parameters. The BAM algorithm performed almost flawlessly on all the Round 1 Mock LISA Data Challenge data sets, including those with many highly overlapping sources. The only misses were later traced to a coding error that affected high frequency sources. In addition to the BAM algorithm we also successfully tested a Genetic Algorithm (GA), but only on data sets with isolated signals as the GA has yet to be optimized to handle large numbers of overlapping signals.Comment: 13 pages, 4 figures, submitted to Proceedings of GWDAW-11 (Berlin, Dec. '06