Electrophysiological evidence for changes in attentional orienting and selection in functional somatic symptoms

Neurophysiology Objective: We investigated changes in attention mechanisms in people who report a high number of somatic symptoms which cannot be associated with a physical cause. Method: Based on scores on the Somatoform Disorder Questionnaire (SDQ-20; Nijenhuis et al., 1996) we compared two non-clinical groups, one with high symptoms on the SDQ-20 and a control group with low or no symptoms. We recorded EEG whilst participants performed an exogenous tactile attention task where they had to discriminate between tactile targets following a tactile cue to the same or opposite hand. Results: The neural marker of attentional orienting to the body, the Late Somatosensory Negativity (LSN), was diminished in the high symptoms group and attentional modulation of touch processing was prolonged at mid and enhanced at later latency stages in this group. Conclusion: These results confirm that attentional processes are altered in people with somatic symptoms, even in a non-clinical group. Furthermore, the observed pattern fits explanations of changes in prior beliefs or expectations leading to diminished amplitudes of the marker of attentional orienting to the body (i.e. the LSN) and enhanced attentional gain of touch processing. Significance: This study shows that high somatic symptoms are associated with neurocognitive attention changes

Single stage experimental evaluation of compressor blading with slots and vortex generators. Part 2 - Data and performance for stage 5 without slots or vortex generators

Comparison performance data of compressor blading without slots or vortex generator

Observation requirements for unmanned planetary missions, part 2

Observation requirements for unmanned planetary mission

Benefits from clinicians and healthcare organisations engaging in research

In Editor’s Choice, Godlee supports and re-emphasises the positive points about National Institute for Health Research (NIHR) clinical research networks that are made in Gulland’s article.1 2 We welcome this support for research networks and for the part they can play in a more fully integrated research and healthcare system. Research engagement by clinicians and healthcare organisations is widely held to improve health services performance. However, we found the issue to be complex in our review conducted for the NIHR Health Services and Delivery Research (HS&DR) Programme in 2012-13.3 Thirty three papers were included in the analysis, and 28 were positive about improved performance, although only seven identified improved outcomes rather than improved processes. Diverse mechanisms contributed to these improvements. In a subsequent article we consider more recent evidence,4 including that UK NHS trusts active in research have lower risk adjusted mortality for acute admissions.5 Increased attention to this issue covers not only clinician participation but also organisational developments in the NIHR and NHS, such as Collaborations for Leadership in Applied Health Research and Care (CLAHRC) and Academic Health Science Networks (AHSNs).6 7 These seek to promote better integration of research and healthcare systems by strengthening research networks, developing research capacity, and ensuring that healthcare organisations (both providers and commissioners) see research as an integral component of their overall structure. Such initiatives need to be linked to further empirical analysis that considers not only the research engagement of all relevant actors but also the organisational determinants of the impact on practice of such engagement

Single stage experimental evaluation of slotted rotor and stator blading. Part I - Analysis and design

Analysis and design of slotted rotor and stator blading for application to compressors in advanced airbreathing propulsion system

Benchmark ultra-cool dwarfs in widely separated binary systems

Ultra-cool dwarfs as wide companions to subgiants, giants, white dwarfs and main sequence stars can be very good benchmark objects, for which we can infer physical properties with minimal reference to theoretical models, through association with the primary stars. We have searched for benchmark ultra-cool dwarfs in widely separated binary systems using SDSS, UKIDSS, and 2MASS. We then estimate spectral types using SDSS spectroscopy and multi-band colors, place constraints on distance, and perform proper motions calculations for all candidates which have sufficient epoch baseline coverage. Analysis of the proper motion and distance constraints show that eight of our ultra-cool dwarfs are members of widely separated binary systems. Another L3.5 dwarf, SDSS 0832, is shown to be a companion to the bright K3 giant Eta Cancri. Such primaries can provide age and metallicity constraints for any companion objects, yielding excellent benchmark objects. This is the first wide ultra-cool dwarf + giant binary system identified.Comment: 4 pages, 3 figures, conference, "New Technologies for Probing the Diversity of Brown Dwarfs and Exoplanets", oral tal

Combining local- and large-scale models to predict the distributions of invasive plant species

Habitat-distribution models are increasingly used to predict the potential distributions of invasive species and to inform monitoring. However, these models assume that species are in equilibrium with the environment, which is clearly not true for most invasive species. Although this assumption is frequently acknowledged, solutions have not been adequately addressed. There are several potential methods for improving habitat-distribution models. Models that require only presence data may be more effective for invasive species, but this assumption has rarely been tested. In addition, combining modeling types to form ‘ensemble’ models may improve the accuracy of predictions. However, even with these improvements, models developed for recently invaded areas are greatly influenced by the current distributions of species and thus reflect near- rather than long-term potential for invasion. Larger scale models from species’ native and invaded ranges may better reflect long-term invasion potential, but they lack finer scale resolution. We compared logistic regression (which uses presence/absence data) and two presence-only methods for modeling the potential distributions of three invasive plant species on the Olympic Peninsula in Washington State, USA. We then combined the three methods to create ensemble models. We also developed climate-envelope models for the same species based on larger scale distributions and combined models from multiple scales to create an index of near- and long-term invasion risk to inform monitoring in Olympic National Park (ONP). Neither presence-only nor ensemble models were more accurate than logistic regression for any of the species. Larger scale models predicted much greater areas at risk of invasion. Our index of near- and long-term invasion risk indicates that \u3c4% of ONP is at high near-term risk of invasion while 67-99% of the Park is at moderate or high long-term risk of invasion. We demonstrate how modeling results can be used to guide the design of monitoring protocols and monitoring results can in turn be used to refine models. We propose that by using models from multiple scales to predict invasion risk and by explicitly linking model development to monitoring, it may be possible to overcome some of the limitations of habitat-distribution models