Structure-function clustering in multiplex brain networks

A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally-connected neural populations: elucidating the subtle interactions between evoked ‘functional connectivity’ and the underlying ‘structural connectivity’ has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime

Automatic ROI detection and classification of the Achilles tendon ultrasound images

Ultrasound (US) imaging plays an important role in medical imaging technologies. It is widely used because of its ease of use and low cost compared to other imaging techniques. Specifically, ultrasound imaging is used in the detection of the Achilles Tendon (AT) pathologies as it detects important details. For example, US imaging is used for AT rupture that affects about 1 in 5,000 people worldwide. Decision support systems are important in medical imaging, as they assist radiologist in detecting probable diagnoses and lesions. The work presented in this paper concerns the development of a software application to detect changes in the AT ultrasound images and subsequently classify them into normal or abnormal. We propose an approach that fully automates the detection for the Region of Interest (ROI) in ultrasound AT images. The original image is divided into six blocks with 1 cm size in each direction. The blocks lie inside the vulnerable area considered as our ROI. The proposed system achieved an accuracy of 97.21%

Googling the brain: discovering hierarchical and asymmetric network structures, with applications in neuroscience

Hierarchical organisation is a common feature of many directed networks arising in nature and technology. For example, a well-defined message-passing framework based on managerial status typically exists in a business organisation. However, in many real-world networks such patterns of hierarchy are unlikely to be quite so transparent. Due to the nature in which empirical data is collated the nodes will often be ordered so as to obscure any underlying structure. In addition, the possibility of even a small number of links violating any overall “chain of command” makes the determination of such structures extremely challenging. Here we address the issue of how to reorder a directed network in order to reveal this type of hierarchy. In doing so we also look at the task of quantifying the level of hierarchy, given a particular node ordering. We look at a variety of approaches. Using ideas from the graph Laplacian literature, we show that a relevant discrete optimization problem leads to a natural hierarchical node ranking. We also show that this ranking arises via a maximum likelihood problem associated with a new range-dependent hierarchical random graph model. This random graph insight allows us to compute a likelihood ratio that quantifies the overall tendency for a given network to be hierarchical. We also develop a generalization of this node ordering algorithm based on the combinatorics of directed walks. In passing, we note that Google’s PageRank algorithm tackles a closely related problem, and may also be motivated from a combinatoric, walk-counting viewpoint. We illustrate the performance of the resulting algorithms on synthetic network data, and on a real-world network from neuroscience where results may be validated biologically

Pre-conceptual Design Assessment of DEMO Remote Maintenance

EDFA, as part of the Power Plant Physics and Technology programme, has been working on the pre-conceptual design of a Demonstration Power Plant (DEMO). As part of this programme, a review of the remote maintenance strategy considered maintenance solutions compatible with expected environmental conditions, whilst showing potential for meeting the plant availability targets. A key finding was that, for practical purposes, the expected radiation levels prohibit the use of complex remote handling operations to replace the first wall. In 2012/13, these remote maintenance activities were further extended, providing an insight into the requirements, constraints and challenges. In particular, the assessment of blanket and divertor maintenance, in light of the expected radiation conditions and availability, has elaborated the need for a very different approach from that of ITER. This activity has produced some very informative virtual reality simulations of the blanket segments and pipe removal that are exceptionally valuable in communicating the complexity and scale of the required operations. Through these simulations, estimates of the maintenance task durations have been possible demonstrating that a full replacement of the blankets within 6 months could be achieved. The design of the first wall, including the need to use sacrificial limiters must still be investigated. In support of the maintenance operations, a first indication of the requirements of an Active Maintenance Facility (AMF) has been elaborated.Comment: 6 pages, 5 figure

THISTLE:trial of hands-on Interprofessional simulation training for local emergencies: a research protocol for a stepped-wedge clustered randomised controlled trial

Peer reviewedPublisher PD

Non-Backtracking Alternating Walks

The combinatorics of walks on a graph is a key topic in network science. Here we study a special class of walks on directed graphs. We combine two features that have previously been considered in isolation. We consider alternating walks, which form the basis of algorithms for hub/authority detection and for discovering directed bipartite substructure. Within this class, we restrict to non-backtracking walks, since this constraint has been seen to offer advantages in related contexts. We derive a recursive formula for counting the total number of non-backtracking alternating walks of a given length, leading to an expression for any associated power series expansion. We discuss computational issues for the widely used cases of resolvent and exponential series, showing that non-backtracking can be incorporated at very little extra cost. We also derive an appropriate asymptotic limit which gives a parameter-free, spectral analogue. We perform tests on an artificial data set in order to quantify the advantages of the new methodology. We also show that the removal of backtracking allows us to identify larger bipartite subgraphs within an anatomical connectivity network from neuroscience

"Author! Author!" : Shakespeare and biography

Original article can be found at: http://www.informaworld.com/smpp/title~content=t714579626~db=all Copyright Informa / Taylor & Francis Group. DOI: 10.1080/17450910902764454Since 1996, not a year has passed without the publication of at least one Shakespeare biography. Yet for many years the place of the author in the practice of understanding literary works has been problematized, and even on occasions eliminated. Criticism reads the “works”, and may or may not refer to an author whose “life” contributed to their meaning. Biography seeks the author in the works, the personality that precedes the works and gives them their characteristic shape and meaning. But the form of literary biography addresses the unusual kind of “life” that puts itself into “works”, and this is particularly challenging where the “works” predominate massively over the salient facts of the “life”. This essay surveys the current terrain of Shakespeare biography, and considers the key questions raised by the medium: can we know anything of Shakespeare's “personality” from the facts of his life and the survival of his works? What is the status of the kind of speculation that inevitably plays a part in biographical reconstruction? Are biographers in the end telling us as much about themselves as they tell us about Shakespeare?Peer reviewe