23 resultados para Belkin, Debbie

em CentAUR: Central Archive University of Reading - UK


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Understanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator only

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The ability of climate models to reproduce and predict land surface anomalies is an important but little-studied topic. In this study, an atmosphere and ocean assimilation scheme is used to determine whether HadCM3 can reproduce and predict snow water equivalent and soil moisture during the 1997–1998 El Nino Southern Oscillation event. Soil moisture is reproduced more successfully, though both snow and soil moisture show some predictability at 1- and 4-month lead times. This result suggests that land surface anomalies may be reasonably well initialized for climate model predictions and hydrological applications using atmospheric assimilation methods over a period of time.

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Snow properties have been retrieved from satellite data for many decades. While snow extent is generally felt to be obtained reliably from visible-band data, there is less confidence in the measurements of snow mass or water equivalent derived from passive microwave instruments. This paper briefly reviews historical passive microwave instruments and products, and compares the large-scale patterns from these sources to those of general circulation models and leading reanalysis products. Differences are seen to be large between the datasets, particularly over Siberia. A better understanding of the errors in both the model-based and measurement-based datasets is required to exploit both fully. Techniques to apply to the satellite measurements for improved large-scale snow data are suggested.

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We propose a new satellite mission to deliver high quality measurements of upper air water vapour. The concept centres around a LiDAR in limb sounding by occultation geometry, designed to operate as a very long path system for differential absorption measurements. We present a preliminary performance analysis with a system sized to send 75 mJ pulses at 25 Hz at four wavelengths close to 935 nm, to up to 5 microsatellites in a counter-rotating orbit, carrying retroreflectors characterized by a reflected beam divergence of roughly twice the emitted laser beam divergence of 15 µrad. This provides water vapour profiles with a vertical sampling of 110 m; preliminary calculations suggest that the system could detect concentrations of less than 5 ppm. A secondary payload of a fairly conventional medium resolution multispectral radiometer allows wide-swath cloud and aerosol imaging. The total weight and power of the system are estimated at 3 tons and 2,700 W respectively. This novel concept presents significant challenges, including the performance of the lasers in space, the tracking between the main spacecraft and the retroreflectors, the refractive effects of turbulence, and the design of the telescopes to achieve a high signal-to-noise ratio for the high precision measurements. The mission concept was conceived at the Alpbach Summer School 2010.

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Pharmacovigilance is essential for developing reliable information on the safety of herbal medicines as used in Europe and the US. The existing systems were developed for synthetic medicines and require some modification to address the specific differences of medicinal herbs. Traditional medicine from many different cultures is used in Europe and the US which adds to the complexities and difficulties of even basic questions such as herb naming systems and chemical variability. Allied to this also is the perception that a ‘natural’ or herbal product must be safe simply because it is not synthetic which means that the safety element of monitoring for such medicines can be overlooked because of the tag associated with such products. Cooperation between orthodox physicians and traditional practitioners is needed to bring together the full case details. Independent scientific assistance on toxicological investigation, botanical verification can be invaluable for full evaluation of any case report. Systematic pharmacovigilance is essential to build up reliable information on the safety of herbal medicines for the development of appropriate guidelines for safe effective use.

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Ethnopharmacological relevance: Studies on traditional Chinese medicine (TCM), like those of other systems of traditional medicine (TM), are very variable in their quality, content and focus, resulting in issues around their acceptability to the global scientific community. In an attempt to address these issues, an European Union funded FP7 consortium, composed of both Chinese and European scientists and named “Good practice in traditional Chinese medicine” (GP-TCM), has devised a series of guidelines and technical notes to facilitate good practice in collecting, assessing and publishing TCM literature as well as highlighting the scope of information that should be in future publications on TMs. This paper summarises these guidelines, together with what has been learned through GP-TCM collaborations, focusing on some common problems and proposing solutions. The recommendations also provide a template for the evaluation of other types of traditional medicine such as Ayurveda, Kampo and Unani. Materials and methods: GP-TCM provided a means by which experts in different areas relating to TCM were able to collaborate in forming a literature review good practice panel which operated through e-mail exchanges, teleconferences and focused discussions at annual meetings. The panel involved coordinators and representatives of each GP-TCM work package (WP) with the latter managing the testing and refining of such guidelines within the context of their respective WPs and providing feedback. Results: A Good Practice Handbook for Scientific Publications on TCM was drafted during the three years of the consortium, showing the value of such networks. A “deliverable – central questions – labour division” model had been established to guide the literature evaluation studies of each WP. The model investigated various scoring systems and their ability to provide consistent and reliable semi-quantitative assessments of the literature, notably in respect of the botanical ingredients involved and the scientific quality of the work described. This resulted in the compilation of (i) a robust scoring system and (ii) a set of minimum standards for publishing in the herbal medicines field, based on an analysis of the main problems identified in published TCM literature.

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By comparing annual and seasonal changes in precipitation over land and ocean since 1950 simulated by the CMIP5 (Coupled Model Intercomparison Project, phase 5) climate models in which natural and anthropogenic forcings have been included, we find that clear global-scale and regional-scale changes due to human influence are expected to have occurred over both land and ocean. These include moistening over northern high latitude land and ocean throughout all seasons and over the northern subtropical oceans during boreal winter. However we show that this signal of human influence is less distinct when considered over the relatively small area of land for which there are adequate observations to make assessments of multi-decadal scale trends. These results imply that extensive and significant changes in precipitation over the land and ocean may have already happened, even though, inadequacies in observations in some parts of the world make it difficult to identify conclusively such a human fingerprint on the global water cycle. In some regions and seasons, due to aliasing of different kinds of variability as a result of sub sampling by the sparse and changing observational coverage, observed trends appear to have been increased, underscoring the difficulties of interpreting the apparent magnitude of observed changes in precipitation.

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It was recently proposed that feelings of contamination can arise in the absence of physical contact with a contaminant. Currently, there are limited data regarding this construct of ‘mental contamination’ although it is hypothesised to be relevant to obsessive compulsive disorder(OCD) where compulsive washing in response to contamination fear is a common presentation (Rachman,2006). This research examined the presence of mental contamination in OCD. Participants (N=177) with obsessive compulsive symptoms completed questionnaires to assess mental contamination, OCD symptoms and thought-action fusion (TAF). Findings indicated that 46% of participants experienced mental contamination, and severity was associated with severity of OCD symptoms and TAF. Mental contamination in the absence of contact contamination was reported by 10.2% of participants. Similar findings were reported in a sub-sample of participants who had received a formal diagnosis of OCD (N=54). These findings suggest that mental contamination is a distinct construct that overlaps with, but is separate from, contact contamination, and provide preliminary empirical support for the construct.

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We describe the CHARMe project, which aims to link climate datasets with publications, user feedback and other items of "commentary metadata". The system will help users learn from previous community experience and select datasets that best suit their needs, as well as providing direct traceability between conclusions and the data that supported them. The project applies the principles of Linked Data and adopts the Open Annotation standard to record and publish commentary information. CHARMe contributes to the emerging landscape of "climate services", which will provide climate data and information to influence policy and decision-making. Although the project focuses on climate science, the technologies and concepts are very general and could be applied to other fields.

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Autism Spectrum Disorder (ASD) is diagnosed on the basis of behavioral symptoms, but cognitive abilities may also be useful in characterizing individuals with ASD. One hundred seventy-eight high-functioning male adults, half with ASD and half without, completed tasks assessing IQ, a broad range of cognitive skills, and autistic and comorbid symptomatology. The aims of the study were, first, to determine whether significant differences existed between cases and controls on cognitive tasks, and whether cognitive profiles, derived using a multivariate classification method with data from multiple cognitive tasks, could distinguish between the two groups. Second, to establish whether cognitive skill level was correlated with degree of autistic symptom severity, and third, whether cognitive skill level was correlated with degree of comorbid psychopathology. Fourth, cognitive characteristics of individuals with Asperger Syndrome (AS) and high-functioning autism (HFA) were compared. After controlling for IQ, ASD and control groups scored significantly differently on tasks of social cognition, motor performance, and executive function (P's < 0.05). To investigate cognitive profiles, 12 variables were entered into a support vector machine (SVM), which achieved good classification accuracy (81%) at a level significantly better than chance (P < 0.0001). After correcting for multiple correlations, there were no significant associations between cognitive performance and severity of either autistic or comorbid symptomatology. There were no significant differences between AS and HFA groups on the cognitive tasks. Cognitive classification models could be a useful aid to the diagnostic process when used in conjunction with other data sources-including clinical history.

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Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes.

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Through close readings of Ann Hawkshaw's poetry in the context of industrial Manchester in the 1840s, this article highlights the interaction of form and content in poetry that makes use of the idea of the past to question or complicate the politics of the present.

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The CHARMe project enables the annotation of climate data with key pieces of supporting information that we term “commentary”. Commentary reflects the experience that has built up in the user community, and can help new or less-expert users (such as consultants, SMEs, experts in other fields) to understand and interpret complex data. In the context of global climate services, the CHARMe system will record, retain and disseminate this commentary on climate datasets, and provide a means for feeding back this experience to the data providers. Based on novel linked data techniques and standards, the project has developed a core system, data model and suite of open-source tools to enable this information to be shared, discovered and exploited by the community.