The Forgiving Graph:A distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick "repairs," which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions,without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been - in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most - log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degreewould have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network. © Springer-Verlag 2012.

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data

Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

Spatial statistics to estimate peat thickness using airborne radiometric data

Soil carbon stores are a major component of the annual returns required by EU governments to the Intergovernmental Panel on Climate Change. Peat has a high proportion of soil carbon due to the relatively high carbon density of peat and organic-rich soils. For this reason it has become increasingly important to measure and model soil carbon stores and changes in peat stocks to facilitate the management of carbon changes over time. The approach investigated in this research evaluates the use of airborne geophysical (radiometric) data to estimate peat thickness using the attenuation of bedrock geology radioactivity by superficial peat cover. Remotely sensed radiometric data are validated with ground peat depth measurements combined with non-invasive geophysical surveys. Two field-based case studies exemplify and validate the results. Variography and kriging are used to predict peat thickness from point measurements of peat depth and airborne radiometric data and provide an estimate of uncertainty in the predictions. Cokriging, by assessing the degree of spatial correlation between recent remote sensed geophysical monitoring and previous peat depth models, is used to examine changes in peat stocks over time. The significance of the coregionalisation is that the spatial cross correlation between the remote and ground based data can be used to update the model of peat depth. The result is that by integrating remotely sensed data with ground geophysics, the need is reduced for extensive ground-based monitoring and invasive peat depth measurements. The overall goal is to provide robust estimates of peat thickness to improve estimates of carbon stocks. The implications from the research have a broader significance that promotes a reduction in the need for damaging onsite peat thickness measurement and an increase in the use of remote sensed data for carbon stock estimations.

The role of private care in the interval between diagnosis and treatment of breast cancer in Northern Ireland: an analysis of Registry data

Objective: To examine the differences in the interval between diagnosis and initiation of treatment among women with breast cancer in Northern Ireland.

Design: A cross-sectional observational study.
Setting: All breast cancer care patients in the Northern Ireland Cancer Registry in 2006.
Participants: All women diagnosed and treated for breast cancer in Northern Ireland in 2006.
Main outcome measure: The number of days between diagnosis and initiation of treatment for breast cancer.

Results: The mean (median) interval between diagnosis and initiation of treatment among public patients was 19 (15) compared with 14 (12) among those whose care involved private providers. The differences between individual public providers were as marked as those between the public and private sector - the mean (median) ranging between 14 (12) and 25 (22) days. Multivariate models revealed that the differences were evident when a range of patient characteristics were controlled for including cancer stage.

Conclusions: A relatively small number of women received care privately in Northern Ireland but experienced shorter intervals between diagnosis and initiation of treatment than those who received care wholly in the public system. The variation among public providers was as great as that between the public and private providers. The impact of such differences on survival and in light of waiting time targets introduced in Northern Ireland warrants investigation.

Task-switching deficits and repetitive behaviour in genetic neurodevelopmental disorders: Data from children with Prader-Willi syndrome chromosome 15 q11-q13 deletion and boys with Fragile X syndrome

Prader-Willi syndrome (PWS) and Fragile X syndrome (FraX) are associated with distinctive cognitive and behavioural profiles. We examined whether repetitive behaviours in the two syndromes were associated with deficits in specific executive functions. PWS, FraX, and typically developing (TD) children were assessed for executive functioning using the Test of Everyday Attention for Children and an adapted Simon spatial interference task. Relative to the TD children, children with PWS and FraX showed greater costs of attention switching on the Simon task, but after controlling for intellectual ability, these switching deficits were only significant in the PWS group. Children with PWS and FraX also showed significantly increased preference for routine and differing profiles of other specific types of repetitive behaviours. A measure of switch cost from the Simon task was positively correlated to scores on preference for routine questionnaire items and was strongly associated with scores on other items relating to a preference for predictability. It is proposed that a deficit in attention switching is a component of the endophenotypes of both PWS and FraX and is associated with specific behaviours. This proposal is discussed in the context of neurocognitive pathways between genes and behaviour.

Qualitative data analysis:A practical example

The aim of this paper is to equip readers with an understanding of the principles of qualitative data analysis and offer a practical example of how analysis might be undertaken in an interview-based study.

Integrating geophysical data and upscaling techniques to support regional groundwater flow modelling: A practical example of the Lagan Valley, Northern Ireland

When studying heterogeneous aquifer systems, especially at regional scale, a degree of generalization is anticipated. This can be due to sparse sampling regimes, complex depositional environments or lack of accessibility to measure the subsurface. This can lead to an inaccurate conceptualization which can be detrimental when applied to groundwater flow models. It is important that numerical models are based on observed and accurate geological information and do not rely on the distribution of artificial aquifer properties. This can still be problematic as data will be modelled at a different scale to which it was collected. It is proposed here that integrating geophysics and upscaling techniques can assist in a more realistic and deterministic groundwater flow model. In this study, the sedimentary aquifer of the Lagan Valley in Northern Ireland is chosen due to intruding sub-vertical dolerite dykes. These dykes are of a lower permeability than the sandstone aquifer. The use of airborne magnetics allows the delineation of heterogeneities, confirmed by field analysis. Permeability measured at the field scale is then upscaled to different levels using a correlation with the geophysical data, creating equivalent parameters that can be directly imported into numerical groundwater flow models. These parameters include directional equivalent permeabilities and anisotropy. Several stages of upscaling are modelled in finite element. Initial modelling is providing promising results, especially at the intermediate scale, suggesting an accurate distribution of aquifer properties. This deterministic based methodology is being expanded to include stochastic methods of obtaining heterogeneity location based on airborne geophysical data. This is through the Direct Sample method of Multiple-Point Statistics (MPS). This method uses the magnetics as a training image to computationally determine a probabilistic occurrence of heterogeneity. There is also a need to apply the method to alternate geological contexts where the heterogeneity is of a higher permeability than the host rock.

Job strain and the risk of severe asthma exacerbations: A meta-analysis of individual-participant data from 100 000 European men and women

Background: Many patients and healthcare professionals believe that work-related psychosocial stress, such as job strain, can make asthma worse, but this is not corroborated by empirical evidence. We investigated the associations between job strain and the incidence of severe asthma exacerbations in working-age European men and women. Methods: We analysed individual-level data, collected between 1985 and 2010, from 102 175 working-age men and women in 11 prospective European studies. Job strain (a combination of high demands and low control at work) was self-reported at baseline. Incident severe asthma exacerbations were ascertained from national hospitalization and death registries. Associations between job strain and asthma exacerbations were modelled using Cox regression and the study-specific findings combined using random-effects meta-analyses. Results: During a median follow-up of 10 years, 1 109 individuals experienced a severe asthma exacerbation (430 with asthma as the primary diagnostic code). In the age- and sex-adjusted analyses, job strain was associated with an increased risk of severe asthma exacerbations defined using the primary diagnostic code (hazard ratio, HR: 1.27, 95% confidence interval, CI: 1.00, 1.61). This association attenuated towards the null after adjustment for potential confounders (HR: 1.22, 95% CI: 0.96, 1.55). No association was observed in the analyses with asthma defined using any diagnostic code (HR: 1.01, 95% CI: 0.86, 1.19). Conclusions: Our findings suggest that job strain is probably not an important risk factor for severe asthma exacerbations leading to hospitalization or death.

Neolithic settlement at the woodland’s edge: palynological data and timber architecture in Orkney, Scotland

It has often been assumed that the islands of Orkney were essentially treeless throughout much of the Holocene, with any ‘scrub’ woodland having been destroyed by Neolithic farming communities by around 3500 cal. BC. This apparently open, hyper-oceanic environment would presumably have provided quite marginal conditions for human settlement, yet Neolithic communities flourished and the islands contain some of the most spectacular remains of this period in north-west Europe. The study of new Orcadian pollen sequences, in conjunction with the synthesis of existing data, indicates that the timing of woodland decline was not synchronous across the archipelago, beginning in the Mesolithic, and that in some areas woodland persisted into the Bronze Age. There is also evidence to suggest that woodland communities in Orkney were more diverse, and therefore that a wider range of resources was available to Neolithic people, than has previously been assumed. Recent archaeological investigations have revealed evidence for timber buildings at early Neolithic settlement sites, suggesting that the predominance of stone architecture in Neolithic Orkney may not have been due to a lack of timber as has been supposed. Rather than simply reflecting adaptation to resource constraints, the reasons behind the shift from timber to stone construction are more complex and encompass social, cultural and environmental factors.