University of Exeter

About: University of Exeter is a education organization based out in Exeter, United Kingdom. It is known for research contribution in the topics: Population & Climate change. The organization has 15820 authors who have published 50650 publications receiving 1793046 citations. The organization is also known as: Exeter University & University of the South West of England.

A single-item measure of social identification: Reliability, validity, and utility

Abstract: This paper introduces a single-item social identification measure (SISI) that involves rating one's agreement with the statement 'I identify with my group (or category)' followed by a 7-point scale. Three studies provide evidence of the validity (convergent, divergent, and test-retest) of SISI with a broad range of social groups. Overall, the estimated reliability of SISI is good. To address the broader issue of single-item measure reliability, a meta-analysis of 16 widely used single-item measures is reported. The reliability of single-item scales ranges from low to reasonably high. Compared with this field, reliability of the SISI is high. In general, short measures struggle to achieve acceptable reliability because the constructs they assess are broad and heterogeneous. In the case of social identification, however, the construct appears to be sufficiently homogeneous to be adequately operationalized with a single item.

A Heuristic for Developing Transdiagnostic Models of Psychopathology Explaining Multifinality and Divergent Trajectories

Abstract: Transdiagnostic models of psychopathology are increasingly prominent because they focus on fundamental processes underlying multiple disorders, help to explain comorbidity among disorders, and may lead to more effective assessment and treatment of disorders. Current transdiagnostic models, however, have difficulty simultaneously explaining the mechanisms by which a transdiagnostic risk factor leads to multiple disorders (i.e., multifinality) and why one individual with a particular transdiagnostic risk factor develops one set of symptoms while another with the same transdiagnostic risk factor develops another set of symptoms (i.e., divergent trajectories). In this article, we propose a heuristic for developing transdiagnostic models that can guide theorists in explicating how a transdiagnostic risk factor results in both multifinality and divergent trajectories. We also (a) describe different levels of transdiagnostic factors and their relative theoretical and clinical usefulness, (b) suggest the types of mechanisms by which factors at 1 level may be related to factors at other levels, and (c) suggest the types of moderating factors that may determine whether a transdiagnostic factor leads to certain specific disorders or symptoms and not others. We illustrate this heuristic using research on rumination, a process for which there is evidence it is a transdiagnostic risk factor.

Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge

Abstract: Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studies (n = 15,234 nondiabetic individuals) and a follow-up of 29 independent loci (n = 6,958-30,620). We identify variants at the GIPR locus associated with 2- h glucose level (rs10423928, beta (s.e.m.) = 0.09 (0.01) mmol/l per A allele, P = 2.0 x 10(-15)). The GIPR A-allele carriers also showed decreased insulin secretion (n = 22,492; insulinogenic index, P = 1.0 x 10(-17); ratio of insulin to glucose area under the curve, P = 1.3 x 10(-16)) and diminished incretin effect (n = 804; P = 4.3 x 10(-4)). We also identified variants at ADCY5 (rs2877716, P = 4.2 x 10(-16)), VPS13C (rs17271305, P = 4.1 x 10(-8)), GCKR (rs1260326, P = 7.1 x 10(-11)) and TCF7L2 (rs7903146, P = 4.2 x 10(-10)) associated with 2-h glucose. Of the three newly implicated loci (GIPR, ADCY5 and VPS13C), only ADCY5 was found to be associated with type 2 diabetes in collaborating studies (n = 35,869 cases, 89,798 controls, OR = 1.12, 95% CI 1.09-1.15, P = 4.8 x 10(-18)).

Perception of emotion from dynamic point-light displays represented in dance

Abstract: It is well known that biological motion, as produced by point-light displays on a human body, gives a good representation of the represented body-eg its gender and the nature of the task which it is engaged in. The question is whether it is possible to judge the emotional state of a human body from motion information alone. An ability to make this kind of judgment may imply that people are able to perceive emotion from patterns of movement without having to compute the detailed shape first. Subjects were shown brief video clips of two trained dancers (one male, one female). The dancers were aiming to convey the following emotions: fear, anger, grief, joy, surprise, and disgust. The video clips portrayed fully lit scenes and point-light scenes, with thirteen small points of light attached to the body of each dancer. Half the stimuli were presented the right way up, while half were inverted. The subjects' task was to judge which emotion was being portrayed. Full-body clips gave good recognition of emotionality (88% correct), but the results for upright biological-motion displays were also significantly above chance (63% correct). Inversion of the display reduced biological-motion (but not full-body) performance to close to chance but still significantly above chance. A space-time analysis of the motion of the points of light was carried out, and was related to the discriminability of the different emotions. Biological-motion displays, which convey no information while static, are able to give a rich description of the subject matter, including the ability to judge emotional state. This ability is disrupted when the image is inverted.

Global Carbon Budget 2015

Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quere et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015).