Extracting partition statistics from semistructured data

The effective grouping, or partitioning, of semistructured data is of fundamental importance when providing support for queries. Partitions allow items within the data set that share common structural properties to be identified efficiently. This allows queries that make use of these properties, such as branching path expressions, to be accelerated. Here, we evaluate the effectiveness of several partitioning techniques by establishing the number of partitions that each scheme can identify over a given data set. In particular, we explore the use of parameterised indexes, based upon the notion of forward and backward bisimilarity, as a means of partitioning semistructured data; demonstrating that even restricted instances of such indexes can be used to identify the majority of relevant partitions in the data

Targeted radiotherapy of neuroblastoma: future directions

No abstract available

Quantum Corrections in Quintessence Models

We investigate the impact of quantum fluctuations on a light rolling quintessence field from three different sources, namely, from a coupling to the standard model and dark matter, from its self-couplings and from its coupling to gravity. We derive bounds for time-varying masses from the change of vacuum energy, finding \Delta m_e/m_e << 10^{-11} for the electron and \Delta m_p/m_p << 10^{-15} for the proton since redshift z~2, whereas the neutrino masses could change of order one. Mass-varying dark matter is also constrained. Next, the self-interactions are investigated. For inverse power law potentials, the effective potential does not become infinitely large at small field values, but saturates at a finite maximal value. We discuss implications for cosmology. Finally, we show that one-loop corrections induce non-minimal gravitational couplings involving arbitrarily high powers of the curvature scalar R, indicating that quintessence entails modified gravity effects.Comment: 10 pages + appendix, added reference

Understanding the dynamical structure of pulsating stars. HARPS spectroscopy of the delta Scuti stars rho Pup and DX Cet

High-resolution spectroscopy is a powerful tool to study the dynamical structure of pulsating stars atmosphere. We aim at comparing the line asymmetry and velocity of the two delta Sct stars rho Pup and DX Cet with previous spectroscopic data obtained on classical Cepheids and beta Cep stars. We obtained, analysed and discuss HARPS high-resolution spectra of rho Pup and DX Cet. We derived the same physical quantities as used in previous studies, which are the first-moment radial velocities and the bi-Gaussian spectral line asymmetries. The identification of f=7.098 (1/d) as a fundamental radial mode and the very accurate Hipparcos parallax promote rho Pup as the best standard candle to test the period-luminosity relations of delta Sct stars. The action of small-amplitude nonradial modes can be seen as well-defined cycle-to-cycle variations in the radial velocity measurements of rho Pup. Using the spectral-line asymmetry method, we also found the centre-of-mass velocities of rho Pup and DX Cet, V_gamma = 47.49 +/- 0.07 km/s and V_gamma = 25.75 +/- 0.06 km/s, respectively. By comparing our results with previous HARPS observations of classical Cepheids and beta Cep stars, we confirm the linear relation between the atmospheric velocity gradient and the amplitude of the radial velocity curve, but only for amplitudes larger than 22.5 km/s. For lower values of the velocity amplitude (i.e., < 22.5 km/s), our data on rho Pup seem to indicate that the velocity gradient is null, but this result needs to be confirmed with additional data. We derived the Baade-Wesselink projection factor p = 1.36 +/- 0.02 for rho Pup and p = 1.39 +/- 0.02 for DX Cet. We successfully extended the period-projection factor relation from classical Cepheids to delta Scuti stars.Comment: Accepted for publication in A&A (in press

Understanding the dynamical structure of pulsating stars: The Baade-Wesselink projection factor of the delta Scuti stars AI Vel and beta Cas

Aims. The Baade-Wesselink method of distance determination is based on the oscillations of pulsating stars. The key parameter of this method is the projection factor used to convert the radial velocity into the pulsation velocity. Our analysis was aimed at deriving for the first time the projection factor of delta Scuti stars, using high-resolution spectra of the high-amplitude pulsator AI Vel and of the fast rotator beta Cas. Methods. The geometric component of the projection factor (i.e. p0) was calculated using a limb-darkening model of the intensity distribution for AI Vel, and a fast-rotator model for beta Cas. Then, using SOPHIE/OHP data for beta Cas and HARPS/ESO data for AI Vel, we compared the radial velocity curves of several spectral lines forming at different levels in the atmosphere and derived the velocity gradient associated to the spectral-line-forming regions in the atmosphere of the star. This velocity gradient was used to derive a dynamical projection factor p. Results. We find a flat velocity gradient for both stars and finally p = p0 = 1.44 for AI Vel and p = p0 = 1.41 for beta Cas. By comparing Cepheids and delta Scuti stars, these results bring valuable insights into the dynamical structure of pulsating star atmospheres. They suggest that the period-projection factor relation derived for Cepheids is also applicable to delta Scuti stars pulsating in a dominant radial mode

Remote Detection of Saline Intrusion in a Coastal Aquifer Using Borehole Measurements of Self-Potential

Funded by NERC CASE studentship . Grant Number: NE/I018417/1Peer reviewedPublisher PD

Quantum-Well Wavefunction Localization and the Electron-Phonon Interaction in Thin Ag Nanofilms

The electron-phonon interaction in thin Ag-nanofilms epitaxially grown on Cu(111) is investigated by temperature-dependent and angle-resolved photoemission from silver quantum-well states. Clear oscillations in the electron-phonon coupling parameter as a function of the silver film thickness are observed. Different from other thin film systems where quantum oscillations are related to the Fermi-level crossing of quantum-well states, we can identify a new mechanism behind these oscillations, based on the wavefunction localization of the quantum-well states in the film

DeepInf: Social Influence Prediction with Deep Learning

Social and information networking activities such as on Facebook, Twitter, WeChat, and Weibo have become an indispensable part of our everyday life, where we can easily access friends' behaviors and are in turn influenced by them. Consequently, an effective social influence prediction for each user is critical for a variety of applications such as online recommendation and advertising. Conventional social influence prediction approaches typically design various hand-crafted rules to extract user- and network-specific features. However, their effectiveness heavily relies on the knowledge of domain experts. As a result, it is usually difficult to generalize them into different domains. Inspired by the recent success of deep neural networks in a wide range of computing applications, we design an end-to-end framework, DeepInf, to learn users' latent feature representation for predicting social influence. In general, DeepInf takes a user's local network as the input to a graph neural network for learning her latent social representation. We design strategies to incorporate both network structures and user-specific features into convolutional neural and attention networks. Extensive experiments on Open Academic Graph, Twitter, Weibo, and Digg, representing different types of social and information networks, demonstrate that the proposed end-to-end model, DeepInf, significantly outperforms traditional feature engineering-based approaches, suggesting the effectiveness of representation learning for social applications.Comment: 10 pages, 5 figures, to appear in KDD 2018 proceeding