Using NMR to Measure Fractal Dimensions

A comment is made on the recent PFG NMR measurements by Stallmach, et al. on water-saturated sands [Phys. Rev. Lett. 88, 105505 (2002)]. It is pointed out that the usual law for the time-dependent diffusion coefficient D(t) used by these authors is not valid for a fractal surface. It is shown that (1-D(t)/D0) \~ t^[(3-Ds)/2] at short times for a surface of fractal dimension Ds, where D0 is the bulk diffusion coefficient. Preliminary PFG NMR data on water saturated limestone and plastic beads are presented to illustrate this analysis.Comment: 1 page, 1 figur

Functional adaptivity for digital library services in e-infrastructures: the gCube approach

We consider the problem of e-Infrastructures that wish to reconcile the generality of their services with the bespoke requirements of diverse user communities. We motivate the requirement of functional adaptivity in the context of gCube, a service-based system that integrates Grid and Digital Library technologies to deploy, operate, and monitor Virtual Research Environments defined over infrastructural resources. We argue that adaptivity requires mapping service interfaces onto multiple implementations, truly alternative interpretations of the same functionality. We then analyse two design solutions in which the alternative implementations are, respectively, full-fledged services and local components of a single service. We associate the latter with lower development costs and increased binding flexibility, and outline a strategy to deploy them dynamically as the payload of service plugins. The result is an infrastructure in which services exhibit multiple behaviours, know how to select the most appropriate behaviour, and can seamlessly learn new behaviours

Optical Properties of Graphene Nanoflakes: Shape Matters

In recent years there has been significant debate on whether the edge type of graphene nanoflakes (GNF) or graphene quantum dots (GQD) are relevant for their electronic structure, thermal stability and optical properties. Using computer simulations, we have proven that there is a fundamental difference in the calculated absorption spectra between samples of the same shape, similar size but different edge type, namely, armchair or zigzag edges. These can be explained by the presence of electronic structures near the Fermi level which are localized on the edges. These features are also evident from the dependence of band gap on the GNF size, which shows three very distinct trends for different shapes and edge geometries.Comment: 8 pages, 9 figures. Submitted to The Journal of Chemical Physic

Nonparametric Bayesian Mixed-effect Model: a Sparse Gaussian Process Approach

Multi-task learning models using Gaussian processes (GP) have been developed and successfully applied in various applications. The main difficulty with this approach is the computational cost of inference using the union of examples from all tasks. Therefore sparse solutions, that avoid using the entire data directly and instead use a set of informative "representatives" are desirable. The paper investigates this problem for the grouped mixed-effect GP model where each individual response is given by a fixed-effect, taken from one of a set of unknown groups, plus a random individual effect function that captures variations among individuals. Such models have been widely used in previous work but no sparse solutions have been developed. The paper presents the first sparse solution for such problems, showing how the sparse approximation can be obtained by maximizing a variational lower bound on the marginal likelihood, generalizing ideas from single-task Gaussian processes to handle the mixed-effect model as well as grouping. Experiments using artificial and real data validate the approach showing that it can recover the performance of inference with the full sample, that it outperforms baseline methods, and that it outperforms state of the art sparse solutions for other multi-task GP formulations.Comment: Preliminary version appeared in ECML201

DWT-based Method for Partial Discharge Pattern Recognition

The new proposed method of pattern recognition is based on the application of Multiresolution Signal Decomposition (MSD) technique of wavelet transform. This technique has shown interesting properties in capturing the embedded horizontal, vertical and diagonal variations within an image obtained from the PD pattern in a separable form. This feature has been exploited to identify in the PD patterns MSD, relative at various family of PD sources, some detail images typical of a single discharge phenomenon. The classification of a generic PD phenomenon is feasible through a comparison between its detail images and the detail images typical of a single discharge phenomenon. Tests have been performed on specimens having single defects. The obtained results prove that the proposed improved classification methods is quite efficient and accurate. [DOI: 10.1685 / CSC06133] About DO

Effects of fault transmissivity on the potential of fault reactivation and induced seismicity : Implications for understanding induced seismicity at Pohang EGS

Funding Information: The project leading to part of the results in this article received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 691728 .Peer reviewedPublisher PD