751 resultados para Lucey, Helen


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Task relevance affects emotional attention in healthy individuals. Here, we investigate whether the association between anxiety and attention bias is affected by the task relevance of emotion during an attention task. Participants completed two visual search tasks. In the emotion-irrelevant task, participants were asked to indicate whether a discrepant face in a crowd of neutral, middle-aged faces was old or young. Irrelevant to the task, target faces displayed angry, happy, or neutral expressions. In the emotion-relevant task, participants were asked to indicate whether a discrepant face in a crowd of middle-aged neutral faces was happy or angry (target faces also varied in age). Trait anxiety was not associated with attention in the emotion-relevant task. However, in the emotion-irrelevant task, trait anxiety was associated with a bias for angry over happy faces. These findings demonstrate that the task relevance of emotional information affects conclusions about the presence of an anxiety-linked attention bias.

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A data insertion method, where a dispersion model is initialized from ash properties derived from a series of satellite observations, is used to model the 8 May 2010 Eyjafjallajökull volcanic ash cloud which extended from Iceland to northern Spain. We also briefly discuss the application of this method to the April 2010 phase of the Eyjafjallajökull eruption and the May 2011 Grímsvötn eruption. An advantage of this method is that very little knowledge about the eruption itself is required because some of the usual eruption source parameters are not used. The method may therefore be useful for remote volcanoes where good satellite observations of the erupted material are available, but little is known about the properties of the actual eruption. It does, however, have a number of limitations related to the quality and availability of the observations. We demonstrate that, using certain configurations, the data insertion method is able to capture the structure of a thin filament of ash extending over northern Spain that is not fully captured by other modeling methods. It also verifies well against the satellite observations according to the quantitative object-based quality metric, SAL—structure, amplitude, location, and the spatial coverage metric, Figure of Merit in Space.

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Extratropical cyclones produce the majority of precipitation in many regions of the extratropics. This study evaluates the ability of a climate model, HiGEM, to reproduce the precipitation associated with extratropical cyclones. The model is evaluated using the ERA-Interim reanalysis and GPCP dataset. The analysis employs a cyclone centred compositing technique, evaluates composites across a range of geographical areas and cyclone intensities and also investigates the ability of the model to reproduce the climatological distribution of cyclone associated precipitation across the Northern Hemisphere. Using this phenomena centred approach provides an ability to identify the processes which are responsible for climatological biases in the model. Composite precipitation intensities are found to be comparable when all cyclones across the Northern Hemisphere are included. When the cyclones are filtered by region or intensity, differences are found, in particular, HiGEM produces too much precipitation in its most intense cyclones relative to ERA-Interim and GPCP. Biases in the climatological distribution of cyclone associated precipitation are also found, with biases around the storm track regions associated with both the number of cyclones in HiGEM and also their average precipitation intensity. These results have implications for the reliability of future projections of extratropical precipitation from the model.

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The cold sector of a midlatitude storm is characterized by distinctive features such as strong surface heat fluxes, shallow convection, convective precipitation and synoptic subsidence. In order to evaluate the contribution of processes occurring in the cold sector to the mean climate, an appropriate indicator is needed. This study describes the systematic presence of negative potential vorticity (PV) behind the cold front of extratropical storms in winter. The origin of this negative PV is analyzed using ERA-Interim data, and PV tendencies averaged over the depth of the boundary layer are evaluated. It is found that negative PV is generated by diabatic processes in the cold sector and by Ekman pumping at the low centre, whereas positive PV is generated by Ekman advection of potential temperature in the warm sector. We suggest here that negative PV at low levels can be used to identify the cold sector. A PV-based indicator is applied to estimate the respective contributions of the cold sector and the remainder of the storm to upward motion and large-scale and convective precipitation. We compare the PV-based indicator with other distinctive features that could be used as markers of the cold sector and find that potential vorticity is the best criterion when taken alone and the best when combined with any other.

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During the eruption of Eyjafjallajökull in April and May 2010, the London Volcanic Ash  Advisory Centre demonstrated the importance of infrared (IR) satellite imagery for monitoring volcanic ash and validating the Met Office operational model, NAME. This model is used to forecast ash dispersion and forms much of the basis of the advice given to civil aviation. NAME requires a source term describing the properties of the eruption plume at the volcanic source. Elements of the source term are often highly uncertain and significant effort has therefore been invested into the use of satellite observations of ash clouds to constrain them. This paper presents a data insertion method, where satellite observations of downwind ash clouds are used to create effective ‘virtual sources’ far from the vent. Uncertainty in the model output is known to increase over the duration of a model run, as inaccuracies in the source term, meteorological data and the parameterizations of the   modelled processes accumulate. This new technique, where the dispersion model (DM) is ‘reinitialized’ part-­way through a run, could go some way to addressing this.

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Background Childhood dental anxiety is very common, with 10–20 % of children and young people reporting high levels of dental anxiety. It is distressing and has a negative impact on the quality of life of young people and their parents as well as being associated with poor oral health. Affected individuals may develop a lifelong reliance on general anaesthetic or sedation for necessary dental treatment thus requiring the support of specialist dental services. Children and young people with dental anxiety therefore require additional clinical time and can be costly to treat in the long term. The reduction of dental anxiety through the use of effective psychological techniques is, therefore, of high importance. However, there is a lack of high-quality research investigating the impact of cognitive behavioural therapy (CBT) approaches when applied to young people’s dental anxiety. Methods/design The first part of the study will develop a profile of dentally anxious young people using a prospective questionnaire sent to a consecutive sample of 100 young people referred to the Paediatric Dentistry Department, Charles Clifford Dental Hospital, in Sheffield. The second part will involve interviewing a purposive sample of 15–20 dental team members on their perceptions of a CBT self-help resource for dental anxiety, their opinions on whether they might use such a resource with patients, and their willingness to recruit participants to a future randomised controlled trial (RCT) to evaluate the resource. The third part of the study will investigate the most appropriate outcome measures to include in a trial, the acceptability of the resource, and retention and completion rates of treatment with a sample of 60 dentally anxious young people using the CBT resource. Discussion This study will provide information on the profile of dentally anxious young people who could potentially be helped by a guided self-help CBT resource. It will gain the perceptions of dental care team members of guided self-help CBT for dental anxiety in young people and their willingness to recruit participants to a trial. Acceptability of the resource to participants and retention and completion rates will also be investigated to inform a future RCT.

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Individuals with Williams syndrome (WS) often experience significant anxiety. A promising approach to anxiety intervention has emerged from cognitive studies of attention bias to threat. To investigate the utility of this intervention in WS, this study examined attention bias to happy and angry faces in individuals with WS (N=46). Results showed a significant difference in attention bias patterns as a function of IQ and anxiety. Individuals with higher IQ or higher anxiety showed a significant bias toward angry, but not happy faces, whereas individuals with lower IQ or lower anxiety showed the opposite pattern. These results suggest that attention bias interventions to modify a threat bias may be most effectively targeted to anxious individuals with WS with relatively high IQ.

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Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

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Human population growth and resource use, mediated by changes in climate, land use, and water use, increasingly impact biodiversity and ecosystem services provision. However, impacts of these drivers on biodiversity and ecosystem services are rarely analyzed simultaneously and remain largely unknown. An emerging question is how science can improve the understanding of change in biodiversity and ecosystem service delivery and of potential feedback mechanisms of adaptive governance. We analyzed past and future change in drivers in south-central Sweden. We used the analysis to identify main research challenges and outline important research tasks. Since the 19th century, our study area has experienced substantial and interlinked changes; a 1.6°C temperature increase, rapid population growth, urbanization, and massive changes in land use and water use. Considerable future changes are also projected until the mid-21st century. However, little is known about the impacts on biodiversity and ecosystem services so far, and this in turn hampers future projections of such effects. Therefore, we urge scientists to explore interdisciplinary approaches designed to investigate change in multiple drivers, underlying mechanisms, and interactions over time, including assessment and analysis of matching-scale data from several disciplines. Such a perspective is needed for science to contribute to adaptive governance by constantly improving the understanding of linked change complexities and their impacts.

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Quite a few texts from England were translated into Irish in the fifteenth and early-sixteenth centuries. The number of these texts was significant enough to suggest that foreign material of this sort enjoyed something of a vogue in late-medieval Ireland. Translated texts include Mandeville’s Travels, Guy of Warwick, Bevis of Hampton, Fierabras and a selection of saints’ lives. Scholars have paid little attention to the origins and initial readerships of these texts, but still less research has been conducted into their afterlife in early modern Ireland. However, a strikingly high number of these works continued to be read and copied well into the seventeenth century and some, such as the Irish translations of Octavian and William of Palerne, only survive in manuscripts from this later period. This paper takes these translations as a test case to explore the ways in which a cross-period approach to such writing is applicable in Ireland, a country where the renaissance is generally considered to have taken little hold. It considers the extent to which Irish reception of this translated material shifts and evolves in the course of this turbulent period and whether the same factors that contributed to the continued demand for a range of similar texts in England into the seventeenth century are also discernible in the Irish context.

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Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.

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Improved understanding and prediction of the fundamental environmental controls on ecosystem service supply across the landscape will help to inform decisions made by policy makers and land-water managers. To evaluate this issue for a local catchment case study, we explored metrics and spatial patterns of service supply for water quality regulation, agriculture production, carbon storage, and biodiversity for the Macronutrient Conwy catchment. Methods included using ecosystem models such as LUCI and JULES, integration of national scale field survey datasets, earth observation products and plant trait databases, to produce finely resolved maps of species richness and primary production. Analyses were done with both 1x1 km gridded and subcatchment data. A common single gradient characterised catchment scale ecosystem services supply with agricultural production and carbon storage at opposing ends of the gradient as reported for a national-scale assessment. Species diversity was positively related to production due to the below national average productivity levels in the Conwy combined with the unimodal relationship between biodiversity and productivity at the national scale. In contrast to the national scale assessment, a strong reduction in water quality as production increased was observed in these low productive systems. Various soil variables were tested for their predictive power of ecosystem service supply. Soil carbon, nitrogen, their ratio and soil pH all had double the power of rainfall and altitude, each explaining around 45% of variation but soil pH is proposed as a potential metric for ecosystem service supply potential as it is a simple and practical metric which can be carried out in the field with crowd-sourcing technologies now available. The study emphasises the importance of considering multiple ecosystem services together due to the complexity of covariation at local and national scales, and the benefits of exploiting a wide range of metrics for each service to enhance data robustness.

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We provide new evidence on sea surface temperature (SST) variations and paleoceanographic/paleoenvironmental changes over the past 1500 years for the north Aegean Sea (NE Mediterranean). The reconstructions are based on multiproxy analyses, obtained from the high resolution (decadal to multidecadal) marine record M2 retrieved from the Athos basin. Reconstructed SSTs show an increase from ca. 850 to 950 AD and from ca. 1100 to 1300 AD. A cooling phase of almost 1.5 �C is observed from ca. 1600 AD to 1700 AD. This seems to have been the starting point of a continuous SST warming trend until the end of the reconstructed period, interrupted by two prominent cooling events at 1832 ± 15 AD and 1995 ± 1 AD. Application of an adaptive Kernel smoothing suggests that the current warming in the reconstructed SSTs of the north Aegean might be unprecedented in the context of the past 1500 years. Internal variability in atmospheric/oceanic circulations systems as well as external forcing as solar radiation and volcanic activity could have affected temperature variations in the north Aegean Sea over the past 1500 years. The marked temperature drop of approximately ~2 �C at 1832 ± 15 yr AD could be related to the 1809 АD ‘unknown’ and the 1815 AD Tambora volcanic eruptions. Paleoenvironmental proxy-indices of the M2 record show enhanced riverine/continental inputs in the northern Aegean after ca. 1450 AD. The paleoclimatic evidence derived from the M2 record is combined with a socio-environmental study of the history of the north Aegean region. We show that the cultivation of temperature-sensitive crops, i.e. walnut, vine and olive, co-occurred with stable and warmer temperatures, while its end coincided with a significant episode of cooler temperatures. Periods of agricultural growth in Macedonia coincide with periods of warmer and more stable SSTs, but further exploration is required in order to identify the causal links behind the observed phenomena. The Black Death likely caused major changes in agricultural activity in the north Aegean region, as reflected in the pollen data from land sites of Macedonia and the M2 proxy-reconstructions. Finally, we conclude that the early modern peaks in mountain vegetation in the Rhodope and Macedonia highlands, visible also in the M2 record, were very likely climate-driven.