The spotty donor star in the X-ray transient Cen X-4

We accurately determine the fundamental system parameters of the neutron star X-ray transient Cen X-4 solely using phase-resolved high-resolution UV-Visual Echelle Spectrograph spectroscopy. We first determine the radial-velocity curve of the secondary star and then model the shape of the phase-resolved absorption line profiles using an X-ray binary model. The model computes the exact rotationally broadened, phase-resolved spectrum and does not depend on assumptions about the rotation profile, limb-darkening coefficients and the effects of contamination from an accretion disc. We determine the secondary star-to-neutron star binary mass ratio to be 0.1755 ± 0.0025, which is an order of magnitude more accurate than previous estimates. We also constrain the inclination angle to be 32^{+8}_{-2} degrees. Combining these values with the results of the radial-velocity study gives a neutron star mass of 1.94^{+0.37}_{-0.85}M⊙ consistent with previous estimates. Finally, we perform the first Roche tomography reconstruction of the secondary star in an X-ray binary. The tomogram reveals surface inhomogeneities that are due to the presence of cool starspots. A large cool polar spot, similar to that seen in Doppler images of rapidly rotating isolated stars, is present on the Northern hemisphere of the K7 secondary star and we estimate that ~4 percent of the total surface area of the donor star is covered with spots.This evidence for starspots supports the idea that magnetic braking plays an important role in the evolution of low-mass X-ray binaries.

Wave loads on the foundation of a bottom-hinged modular flap structure

Large loads result in expensive foundations which are a substantial proportion of the capital cost of flap-type Wave Energy Converters (WECs). Devices such as Oyster 800, currently deployed at the European Marine Energy Centre (EMEC), comprise a single flap for the full width of the machine. Splitting a flap-type device into smaller vertical flap modules, to make a ‘modular-flap’, might reduce the total foundation loads, whilst still providing acceptable performance in terms of energy conversion.
This paper investigates the foundation loads of an undamped modular-flap device, comparing them to those for a rigid flap of an equivalent width. Physical modelling in a wave tank is used, with loads recorded using a six degree of freedom (DoF) load cell. Both fatigue and extreme loading analysis was conducted. The rotations of the flaps were also recorded, using a motion-tracking system.

Experimental Investigation of Transient Saltwater Intrusion in Heterogeneous Porous Media

A 2D sandbox style experiment was developed to compare the results of numerical modelling to physical testing for saltwater intrusion in homogeneous and heterogeneous aquifers. The sandbox consisted of a thin central viewing chamber filled with glass beads of varying diameters (780μm, 1090μm and 1325μm) under fully saturated conditions. Dyed saltwater (SW) was introduced at the side boundary and a head difference imposed across the porous media. Images of the SW wedge were recorded at intervals in order to assess the suitability of the numerical models predictions of transient SW intrusion. Numerical modelling of the experimental cases were simulated using SUTRA. Two main parameters were chosen to express the condition of the intruding SW wedge at each recorded time step; the toe penetration length (TL) and the width of the mixing zone (WMZ). The WMZ was larger under transient conditions in the heterogeneous case, while the TL was longer for the homogeneous case. The increased variability in the flow field fo the heterogeneous case resulted in increased dispersion, and thus, increased WMZ.

Evaluation of infilled frames: an updated in-plane-stiffness macro-model considering the effects of vertical loads

The influence of masonry infills on the in-plane behaviour of RC framed structures is a central topic in the seismic evaluation and retrofitting of existing buildings. Many models in the literature use an equivalent strut member in order to represent the infill but, among the parameters influencing the equivalent strut behaviour, the effect of vertical loads acting on the frames is recognized but not quantified. Nevertheless a vertical load causes a non-negligible variation in the in-plane behaviour of infilled frames by influencing the effective volume of the infill. This results in a change in the stiffness and strength of the system. This paper presents an equivalent diagonal pin-jointed strut model taking into account the stiffening effect of vertical loads on the infill in the initial state. The in-plane stiffness of a range of infilled frames was evaluated using a finite element model of the frame-infill system and the cross-section of the strut equivalent to the infill was obtained for different levels of vertical loading by imposing the equivalence between the frame containing the infill and the frame containing the diagonal strut. In this way a law for identifying the equivalent strut width depending on the geometrical and mechanical characteristics of the infilled frame was generalized to consider the influence of vertical loads for use in the practical applications. The strategy presented, limited to the initial stiffness of infilled frames, is preparatory to the definition of complete non-linear cyclic laws for the equivalent strut.

Invited Interview on Network Performance in the "Transient Gestures" issue

An issue on Networked Performance produceed by Neural for which I was invited to deliver an interview on network performance. Neural is a printed magazine established in 1993 dealing with new media art, electronic music and hacktivism. It was founded by Alessandro Ludovico and Minus Habens Records label owner Ivan Iusco in Bari (Italy).

Non-convex dynamic economic/environmental dispatch with plug-in electric vehicle loads

Electric vehicles are a key prospect for future transportation. A large penetration of electric vehicles has the potential to reduce the global fossil fuel consumption and hence the greenhouse gas emissions and air pollution. However, the additional stochastic loads imposed by plug-in electric vehicles will possibly introduce significant changes to existing load profiles. In his paper, electric vehicles loads are integrated into an 5-unit system using a non-convex dynamic dispatch model. The actual infrastructure characteristics including valve-point effects, load balance constrains and transmission loss have been included in the model. Multiple load profiles are comparatively studied and compared in terms of economic and environmental impacts in order o identify patterns to charge properly. The study as expected shows ha off-peak charging is the best scenario with respect to using less fuels and producing less emissions.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

A combined transient and computational study of the dissociation of N(2)O on platinum catalysts

The energetics of the low-temperature adsorption and decomposition of nitrous oxide, N(2)O, on flat and stepped platinum surfaces were calculated using density-functional theory (DFT). The results show that the preferred adsorption site for N(2)O is an atop site, bound upright via the terminal nitrogen. The molecule is only weakly chemisorbed to the platinum surface. The decomposition barriers on flat (I 11) surfaces and stepped (211) surfaces are similar. While the barrier for N(2)O dissociation is relatively small, the surface rapidly becomes poisoned by adsorbed oxygen. These findings are supported by experimental results of pulsed N(2)O decomposition with 5% Pt/SiO(2) and bismuth-modified Pt/C catalysts. At low temperature, decomposition occurs but self-poisoning by O((ads)) prevents further decomposition. At higher temperatures some desorption Of O(2) is observed, allowing continued catalytic activity. The study with bismuth-modified Pt/C catalysts showed that, although the activation barriers calculated for both terraces and steps were similar, the actual rate was different for the two surfaces. Steps were found experimentally to be more active than terraces and this is attributed to differences in the preexponential term. (C) 2004 Elsevier Inc. All rights reserved.

Machine learning for transient discovery in Pan-STARRS1 difference imaging

Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of similar to 32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 x 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.

PESSTO: Survey description and products from the first data release by the Public ESO Spectroscopic Survey of Transient Objects

Context. The Public European Southern Observatory Spectroscopic Survey of Transient Objects (PESSTO) began as a public spectroscopic survey in April 2012. PESSTO classifies transients from publicly available sources and wide-field surveys, and selects science targets for detailed spectroscopic and photometric follow-up. PESSTO runs for nine months of the year, January - April and August - December inclusive, and typically has allocations of 10 nights per month. 

Aims. We describe the data reduction strategy and data products that are publicly available through the ESO archive as the Spectroscopic Survey data release 1 (SSDR1). 

Methods. PESSTO uses the New Technology Telescope with the instruments EFOSC2 and SOFI to provide optical and NIR spectroscopy and imaging. We target supernovae and optical transients brighter than 20.5^m for classification. Science targets are selected for follow-up based on the PESSTO science goal of extending knowledge of the extremes of the supernova population. We use standard EFOSC2 set-ups providing spectra with resolutions of 13-18 Å between 3345-9995 Å. A subset of the brighter science targets are selected for SOFI spectroscopy with the blue and red grisms (0.935-2.53 μm and resolutions 23-33 Å) and imaging with broadband JHK<inf>s</inf> filters. 

Results. This first data release (SSDR1) contains flux calibrated spectra from the first year (April 2012-2013). A total of 221 confirmed supernovae were classified, and we released calibrated optical spectra and classifications publicly within 24 h of the data being taken (via WISeREP). The data in SSDR1 replace those released spectra. They have more reliable and quantifiable flux calibrations, correction for telluric absorption, and are made available in standard ESO Phase 3 formats. We estimate the absolute accuracy of the flux calibrations for EFOSC2 across the whole survey in SSDR1 to be typically ∼15%, although a number of spectra will have less reliable absolute flux calibration because of weather and slit losses. Acquisition images for each spectrum are available which, in principle, can allow the user to refine the absolute flux calibration. The standard NIR reduction process does not produce high accuracy absolute spectrophotometry but synthetic photometry with accompanying JHK<inf>s</inf> imaging can improve this. Whenever possible, reduced SOFI images are provided to allow this. 

Conclusions. Future data releases will focus on improving the automated flux calibration of the data products. The rapid turnaround between discovery and classification and access to reliable pipeline processed data products has allowed early science papers in the first few months of the survey.

The Ultraviolet-Bright, Slowly Declining Transient PS1-11af as a Partial Tidal Disruption Event

We present the Pan-STARRS1 discovery of the long-lived and blue transient PS1-11af, which was also detected by Galaxy Evolution Explorer with coordinated observations in the near-ultraviolet (NUV) band. PS1-11af is associated with the nucleus of an early type galaxy at redshift z = 0.4046 that exhibits no evidence for star formation or active galactic nucleus activity. Four epochs of spectroscopy reveal a pair of transient broad absorption features in the UV on otherwise featureless spectra. Despite the superficial similarity of these features to P-Cygni absorptions of supernovae (SNe), we conclude that PS1-11af is not consistent with the properties of known types of SNe. Blackbody fits to the spectral energy distribution are inconsistent with the cooling, expanding ejecta of a SN, and the velocities of the absorption features are too high to represent material in homologous expansion near a SN photosphere. However, the constant blue colors and slow evolution of the luminosity are similar to previous optically selected tidal disruption events (TDEs). The shape of the optical light curve is consistent with models for TDEs, but the minimum accreted mass necessary to power the observed luminosity is only 0.002 M, which points to a partial disruption model. A full disruption model predicts higher bolometric luminosities, which would require most of the radiation to be emitted in a separate component at high energies where we lack observations. In addition, the observed temperature is lower than that predicted by pure accretion disk models for TDEs and requires reprocessing to a constant, lower temperature. Three deep non-detections in the radio with the Very Large Array over the first two years after the event set strict limits on the production of any relativistic outflow comparable to Swift J1644+57, even if off-axis.