Wettability-independent droplet transport by \emph{Bendotaxis}

We demonstrate \textit{bendotaxis}, a novel mechanism for droplet self-transport at small scales. A combination of bending and capillarity in a thin channel causes a pressure gradient that, in turn, results in the spontaneous movement of a liquid droplet. Surprisingly, the direction of this motion is always the same, regardless of the wettability of the channel. We use a combination of experiments at a macroscopic scale and a simple mathematical model to study this motion, focussing in particular on the time scale associated with the motion. We suggest that \emph{bendotaxis} may be a useful means of transporting droplets in technological applications, for example in developing self-cleaning surfaces, and discuss the implications of our results for such applications.Comment: 5 pages, 4 figures. Supplementary Information available on reques

A Bayesian spatio-temporal model of panel design data: airborne particle number concentration in Brisbane, Australia

This paper outlines a methodology for semi-parametric spatio-temporal modelling of data which is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data are hourly averaged particle number concentration (PNC) and were collected, as part of the Ultrafine Particles from Transport Emissions and Child Health (UPTECH) project. Two weeks of continuous measurements were taken at each of a number of government primary schools in the Brisbane Metropolitan Area. The monitoring equipment was taken to each school sequentially. The school data are augmented by data from long term monitoring stations at three locations in Brisbane, Australia. Fitting the model helps describe the spatial and temporal variability at a subset of the UPTECH schools and the long-term monitoring sites. The temporal variation is modelled hierarchically with penalised random walk terms, one common to all sites and a term accounting for the remaining temporal trend at each site. Parameter estimates and their uncertainty are computed in a computationally efficient approximate Bayesian inference environment, R-INLA. The temporal part of the model explains daily and weekly cycles in PNC at the schools, which can be used to estimate the exposure of school children to ultrafine particles (UFPs) emitted by vehicles. At each school and long-term monitoring site, peaks in PNC can be attributed to the morning and afternoon rush hour traffic and new particle formation events. The spatial component of the model describes the school to school variation in mean PNC at each school and within each school ground. It is shown how the spatial model can be expanded to identify spatial patterns at the city scale with the inclusion of more spatial locations.Comment: Draft of this paper presented at ISBA 2012 as poster, part of UPTECH projec

An open-source, stochastic, six-degrees-of-freedom rocket flight simulator, with a probabilistic trajectory analysis approach

Predicting the flight-path of an unguided rocket can help overcome unnecessary risks. Avoiding residential areas or a car-park can improve the safety of launching a rocket significantly. Furthermore, an accurate landing site prediction facilitates recovery. This paper introduces a six-degrees-of-freedom flight simulator for large unguided model rockets that can fly to altitudes of up to 13 km and then return to earth by parachute. The open-source software package assists the user with the design of rockets, and its simulation core models both the rocket flight and the parachute descent in stochastic wind conditions. Furthermore, the uncertainty in the input variables propagates through the model via a Monte Carlo wrapper, simulating a range of possible flight conditions. The resulting trajectories are captured as a Gaussian process, which assists in the statistical assessment of the flight conditions in the face of uncertainties, such as changes in wind conditions, failure to deploy the parachute, and variations in thrust. This approach also facilitates concise presentation of such uncertainties via visualisation of trajectory ensembles

Kepler-91b: a planet at the end of its life. Planet and giant host star properties via light-curve variations

The evolution of planetary systems is intimately linked to the evolution of their host star. Our understanding of the whole planetary evolution process is based on the large planet diversity observed so far. To date, only few tens of planets have been discovered orbiting stars ascending the Red Giant Branch. Although several theories have been proposed, the question of how planets die remains open due to the small number statistics. In this work we study the giant star Kepler-91 (KOI-2133) in order to determine the nature of a transiting companion. This system was detected by the Kepler Space Telescope. However, its planetary confirmation is needed. We confirm the planetary nature of the object transiting the star Kepler-91 by deriving a mass of $M_p=0.88^{+0.17}_{-0.33} ~M_{\rm Jup}$ and a planetary radius of $R_p=1.384^{+0.011}_{-0.054} ~R_{\rm Jup}$. Asteroseismic analysis produces a stellar radius of $R_{\star}=6.30\pm 0.16 ~R_{\odot}$ and a mass of $M_{\star}=1.31\pm 0.10 ~ M_{\odot}$. We find that its eccentric orbit ($e=0.066^{+0.013}_{-0.017}$) is just $1.32^{+0.07}_{-0.22} ~ R_{\star}$ away from the stellar atmosphere at the pericenter. Kepler-91b could be the previous stage of the planet engulfment, recently detected for BD+48 740. Our estimations show that Kepler-91b will be swallowed by its host star in less than 55 Myr. Among the confirmed planets around giant stars, this is the planetary-mass body closest to its host star. At pericenter passage, the star subtends an angle of $48^{\circ}$, covering around 10% of the sky as seen from the planet. The planetary atmosphere seems to be inflated probably due to the high stellar irradiation.Comment: 21 pages, 8 tables and 11 figure

Retrodiction as a tool for micromaser field measurements

We use retrodictive quantum theory to describe cavity field measurements by successive atomic detections in the micromaser. We calculate the state of the micromaser cavity field prior to detection of sequences of atoms in either the excited or ground state, for atoms that are initially prepared in the excited state. This provides the POM elements, which describe such sequences of measurements.Comment: 20 pages, 4(8) figure

The Kinetic Sunyaev-Zel'dovich Effect from Radiative Transfer Simulations of Patchy Reionization

We present the first calculation of the kinetic Sunyaev-Zel'dovich (kSZ) effect due to the inhomogeneous reionization of the universe based on detailed large-scale radiative transfer simulations of reionization. The resulting sky power spectra peak at l=2000-8000 with maximum values of l^2C_l~1\times10^{-12}. The peak scale is determined by the typical size of the ionized regions and roughly corresponds to the ionized bubble sizes observed in our simulations, ~5-20 Mpc. The kSZ anisotropy signal from reionization dominates the primary CMB signal above l=3000. This predicted kSZ signal at arcminute scales is sufficiently strong to be detectable by upcoming experiments, like the Atacama Cosmology Telescope and South Pole Telescope which are expected to have ~1' resolution and ~muK sensitivity. The extended and patchy nature of the reionization process results in a boost of the peak signal in power by approximately one order of magnitude compared to a uniform reionization scenario, while roughly tripling the signal compared with that based upon the assumption of gradual but spatially uniform reionization. At large scales the patchy kSZ signal depends largely on the ionizing source efficiencies and the large-scale velocity fields: sources which produce photons more efficiently yield correspondingly higher signals. The introduction of sub-grid gas clumping in the radiative transfer simulations produces significantly more power at small scales, and more non-Gaussian features, but has little effect at large scales. The patchy nature of the reionization process roughly doubles the total observed kSZ signal for l~3000-10^4 compared to non-patchy scenarios with the same total electron-scattering optical depth.Comment: 14 pages, 13 figures (some in color), submitted to Ap

Towards virtual machine energy-aware cost prediction in clouds

Pricing mechanisms employed by different service providers significantly influence the role of cloud computing within the IT industry. With the increasing cost of electricity, Cloud providers consider power consumption as one of the major cost factors to be maintained within their infrastructures. Consequently, modelling a new pricing mechanism that allow Cloud providers to determine the potential cost of resource usage and power consumption has attracted the attention of many researchers. Furthermore, predicting the future cost of Cloud services can help the service providers to offer the suitable services to the customers that meet their requirements. This paper introduces an Energy-Aware Cost Prediction Framework to estimate the total cost of Virtual Machines (VMs) by considering the resource usage and power consumption. The VMs’ workload is firstly predicted based on an Autoregressive Integrated Moving Average (ARIMA) model. The power consumption is then predicted using regression models. The comparison between the predicted and actual results obtained in a real Cloud testbed shows that this framework is capable of predicting the workload, power consumption and total cost for different VMs with good prediction accuracy, e.g. with 0.06 absolute percentage error for the predicted total cost of the VM

The equivalence of fluctuation scale dependence and autocorrelations

We define optimal per-particle fluctuation and correlation measures, relate fluctuations and correlations through an integral equation and show how to invert that equation to obtain precise autocorrelations from fluctuation scale dependence. We test the precision of the inversion with Monte Carlo data and compare autocorrelations to conditional distributions conventionally used to study high-$p_t$ jet structure.Comment: 10 pages, 9 figures, proceedings, MIT workshop on correlations and fluctuations in relativistic nuclear collision

Analyzing the House Fly's Exploratory Behavior with Autoregression Methods

This paper presents a detailed characterization of the trajectory of a single housefly with free range of a square cage. The trajectory of the fly was recorded and transformed into a time series, which was fully analyzed using an autoregressive model, which describes a stationary time series by a linear regression of prior state values with the white noise. The main discovery was that the fly switched styles of motion from a low dimensional regular pattern to a higher dimensional disordered pattern. This discovered exploratory behavior is, irrespective of the presence of food, characterized by anomalous diffusion.Comment: 20 pages, 9 figures, 1 table, full pape