The effect of electrode dislocation on lower back surface electromyography amplitude

Surface Electromyography (SEMG) plays an important role in the understanding of trunk muscle activity during various postures and movements. The Root Mean Square (RMS) is used to quantify the muscle activation amplitude and was shown to be a valuable parameter in research focusing on the etiology and maintenance of chronic lower back pain.\ud The aim of the current study was to determine the effect of electrode dislocation on the RMS of the low back muscles

What are sources of carbon lock-in in energy-intensive industry? A case study into Dutch chemicals production

Keeping global mean temperature rise well below 2 °C requires deep emission reductions in all industrial sectors, but several barriers inhibit such transitions. A special type of barrier is carbon lock-in, defined as a process whereby various forms of increasing returns to adoption inhibit innovation and the competitiveness of low-carbon alternatives, resulting in further path dependency. Here, we explore potential carbon lock-in in the Dutch chemical industry via semi-structured interviews with eleven key actors. We find that carbon lock-in may be the result of (i) technological incompatibility between deep emission reduction options over time, (ii) system integration in chemical clusters, (iii) increasing sunk costs as firms continue to invest in incremental improvements in incumbent installations, (iv) governmental policy inconsistency between targets for energy efficiency and deep emission reductions, and (v) existing safety routines and standards. We also identify barriers that do not have the self-reinforcing character of lock-in, but do inhibit deep emission reductions. Examples include high operating costs of low-carbon options and low risk acceptance by capital providers and shareholders. Rooted in the Dutch policy setting, we discuss policy responses for avoiding carbon lock-in and overcoming barriers based on the interviews, such as transition plans for individual industries and infrastructure subsidies

Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank

Depression is assessed in various ways in research, with large population studies often relying on minimal phenotyping. Genetic results suggest clinical diagnoses and self-report measures of depression show some core similarities, but also important differences. It is not yet clear how neuroimaging associations depend on levels of phenotyping. We studied 39,300 UK Biobank imaging participants (20,701 female; aged 44.6 to 82.3 years, M = 64.1, SD = 7.5) with structural neuroimaging and lifetime depression data. Past depression phenotypes included a single-item self-report measure, an intermediate measure of ‘probable’ lifetime depression, derived from multiple questionnaire items relevant to a history of depression, and a retrospective clinical diagnosis according to DSM-IV criteria. We tested (i) associations between brain structural measures and each depression phenotype, and (ii) effects of phenotype on these associations. Depression-brain structure associations were small (β < 0.1) for all phenotypes, but still significant after FDR correction for many regional metrics. Lifetime depression was consistently associated with reduced white matter integrity across phenotypes. Cortical thickness showed negative associations with Self-reported Depression in particular. Phenotype effects were small across most metrics, but significant for cortical thickness in most regions. We report consistent effects of lifetime depression in brain structural measures, including reduced integrity of thalamic radiations and association fibres. We also observed significant differences in associations with cortical thickness across depression phenotypes. Although these results did not relate to level of phenotyping as expected, effects of phenotype definition are still an important consideration for future depression research

Associations of negative affective biases and depressive symptoms in a community-based sample

Acknowledgements. We thank professor Jonathan Roiser (University College London, UK) and professor emeritus Ian Deary (University of Edinburgh, UK) for their input on task selection and statistical analysis. We also acknowledge all researchers who have contributed to the collection of data for the current study. Most importantly, we would like to thank all participants of Generation Scotland, and particularly those of the STRADL subcohort, for their participation in the research. Financial support. Stratifying Resilience and Depression Longitudinally is supported by the Wellcome Trust through a Strategic Award (Grant No. 104036/Z/14/Z) and through an Investigator Award (Grant No. 220857/Z/ 20/Z). The Chief Scientist Office of the Scottish Government Health Department (Grant No. CZD/16/6), Scottish Funding Council (Grant No. HR03006) and Wellcome Trust (Grant No. 216767/Z/19/Z) provided core support for Generation Scotland.Peer reviewedPublisher PD

Associations of negative affective biases and depressive symptoms in a community-based sample

Background: Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls. Methods: Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. Conclusions: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals

Search for magnetic monopoles in √s = 7 TeV pp collisions with the ATLAS detector

This Letter presents a search for magnetic monopoles with the ATLAS detector at the CERN Large Hadron Collider using an integrated luminosity of 2.0  fb−1 of pp collisions recorded at a center-of-mass energy of √s = 7 TeV. No event is found in the signal region, leading to an upper limit on the production cross section at 95% confidence level of 1.6/ϵ fb for Dirac magnetic monopoles with the minimum unit magnetic charge and with mass between 200 GeV and 1500 GeV, where ϵ is the monopole reconstruction efficiency. The efficiency ϵ is high and uniform in the fiducial region given by pseudorapidity |η|<1.37 and transverse kinetic energy 600-700<Ekinsinθ<1400 GeV. The minimum value of 700 GeV is for monopoles of mass 200 GeV, whereas the minimum value of 600 GeV is applicable for higher mass monopoles. Therefore, the upper limit on the production cross section at 95% confidence level is 2 fb in this fiducial region. Assuming the kinematic distributions from Drell-Yan pair production of spin-1/2 Dirac magnetic monopoles, the efficiency is in the range 1%-10%, leading to an upper limit on the cross section at 95% confidence level that varies from 145 fb to 16 fb for monopoles with mass between 200 GeV and 1200 GeV. This limit is weaker than the fiducial limit because most of these monopoles lie outside the fiducial region