856 resultados para Population set-based methods


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DIGE is a protein labelling and separation technique allowing quantitative proteomics of two or more samples by optical fluorescence detection of differentially labelled proteins that are electrophoretically separated on the same gel. DIGE is an alternative to quantitation by MS-based methodologies and can circumvent their analytical limitations in areas such as intact protein analysis, (linear) detection over a wide range of protein abundances and, theoretically, applications where extreme sensitivity is needed. Thus, in quantitative proteomics DIGE is usually complementary to MS-based quantitation and has some distinct advantages. This review describes the basics of DIGE and its unique properties and compares it to MS-based methods in quantitative protein expression analysis.

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Objective: To test the hypothesis that measles vaccination was involved in the pathogenesis of autism spectrum disorders (ASD) as evidenced by signs of a persistent measles infection or abnormally persistent immune response shown by circulating measles virus or raised antibody titres in children with ASD who had been vaccinated against measles, mumps and rubella (MMR) compared with controls. Design: Case-control study, community based. Methods: A community sample of vaccinated children aged 10-12 years in the UK with ASD (n = 98) and two control groups of similar age, one with special educational needs but no ASD (n = 52) and one typically developing group (n = 90), were tested for measles virus and antibody response to measles in the serum. Results: No difference was found between cases and controls for measles antibody response. There was no dose-response relationship between autism symptoms and antibody concentrations. Measles virus nucleic acid was amplified by reverse transcriptase-PCR in peripheral blood mononuclear cells from one patient with autism and two typically developing children. There was no evidence of a differential response to measles virus or the measles component of the MMR in children with ASD, with or without regression, and controls who had either one or two doses of MMR. Only one child from the control group had clinical symptoms of possible enterocolitis. Conclusion: No association between measles vaccination and ASD was shown.

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In this work a hybrid technique that includes probabilistic and optimization based methods is presented. The method is applied, both in simulation and by means of real-time experiments, to the heating unit of a Heating, Ventilation Air Conditioning (HVAC) system. It is shown that the addition of the probabilistic approach improves the fault diagnosis accuracy.

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A first step in interpreting the wide variation in trace gas concentrations measured over time at a given site is to classify the data according to the prevailing weather conditions. In order to classify measurements made during two intensive field campaigns at Mace Head, on the west coast of Ireland, an objective method of assigning data to different weather types has been developed. Air-mass back trajectories calculated using winds from ECMWF analyses, arriving at the site in 1995–1997, were allocated to clusters based on a statistical analysis of the latitude, longitude and pressure of the trajectory at 12 h intervals over 5 days. The robustness of the analysis was assessed by using an ensemble of back trajectories calculated for four points around Mace Head. Separate analyses were made for each of the 3 years, and for four 3-month periods. The use of these clusters in classifying ground-based ozone measurements at Mace Head is described, including the need to exclude data which have been influenced by local perturbations to the regional flow pattern, for example, by sea breezes. Even with a limited data set, based on 2 months of intensive field measurements in 1996 and 1997, there are statistically significant differences in ozone concentrations in air from the different clusters. The limitations of this type of analysis for classification and interpretation of ground-based chemistry measurements are discussed.

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In situ analysis has become increasingly important for contaminated land investigation and remediation. At present, portable techniques are used mainly as scanning tools to assess the spread and magnitude of the contamination, and are an adjunct to conventional laboratory analyses. A site in Cornwall, containing naturally occurring radioactive material (NORM), provided an opportunity for Reading University PhD student Anna Kutner to compare analytical data collected in situ with data generated by laboratory-based methods. The preliminary results in this paper extend the author‟s poster presentation at last September‟s GeoSpec2010 conference held in Lancaster.

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This study analyzes the issue of American option valuation when the underlying exhibits a GARCH-type volatility process. We propose the usage of Rubinstein's Edgeworth binomial tree (EBT) in contrast to simulation-based methods being considered in previous studies. The EBT-based valuation approach makes an implied calibration of the pricing model feasible. By empirically analyzing the pricing performance of American index and equity options, we illustrate the superiority of the proposed approach.

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An algorithm for tracking multiple feature positions in a dynamic image sequence is presented. This is achieved using a combination of two trajectory-based methods, with the resulting hybrid algorithm exhibiting the advantages of both. An optimizing exchange algorithm is described which enables short feature paths to be tracked without prior knowledge of the motion being studied. The resulting partial trajectories are then used to initialize a fast predictor algorithm which is capable of rapidly tracking multiple feature paths. As this predictor algorithm becomes tuned to the feature positions being tracked, it is shown how the location of occluded or poorly detected features can be predicted. The results of applying this tracking algorithm to data obtained from real-world scenes are then presented.

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The structure of the Arctic stratospheric polar vortex in three chemistry–climate models (CCMs) taken from the CCMVal-2 intercomparison is examined using zonal mean and geometric-based methods. The geometric methods are employed by taking 2D moments of potential vorticity fields that are representative of the polar vortices in each of the models. This allows the vortex area, centroid location and ellipticity to be determined, as well as a measure of vortex filamentation. The first part of the study uses these diagnostics to examine how well the mean state, variability and extreme variability of the polar vortices are represented in CCMs compared to ERA-40 reanalysis data, and in particular for the UMUKCA-METO, NIWA-SOCOL and CCSR/NIES models. The second part of the study assesses how the vortices are predicted to change in terms of the frequency of sudden stratospheric warmings and their general structure over the period 1960–2100. In general, it is found that the vortices are climatologically too far poleward in the CCMs and produce too few large-scale filamentation events. Only a small increase is observed in the frequency of sudden stratospheric warming events from the mean of the CCMVal-2 models, but the distribution of extreme variability throughout the winter period is shown to change towards the end of the twentyfirst century.

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We present an approach for dealing with coarse-resolution Earth observations (EO) in terrestrial ecosystem data assimilation schemes. The use of coarse-scale observations in ecological data assimilation schemes is complicated by spatial heterogeneity and nonlinear processes in natural ecosystems. If these complications are not appropriately dealt with, then the data assimilation will produce biased results. The “disaggregation” approach that we describe in this paper combines frequent coarse-resolution observations with temporally sparse fine-resolution measurements. We demonstrate the approach using a demonstration data set based on measurements of an Arctic ecosystem. In this example, normalized difference vegetation index observations are assimilated into a “zero-order” model of leaf area index and carbon uptake. The disaggregation approach conserves key ecosystem characteristics regardless of the observation resolution and estimates the carbon uptake to within 1% of the demonstration data set “truth.” Assimilating the same data in the normal manner, but without the disaggregation approach, results in carbon uptake being underestimated by 58% at an observation resolution of 250 m. The disaggregation method allows the combination of multiresolution EO and improves in spatial resolution if observations are located on a grid that shifts from one observation time to the next. Additionally, the approach is not tied to a particular data assimilation scheme, model, or EO product and can cope with complex observation distributions, as it makes no implicit assumptions of normality.

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Diaminofluoresceins are widely used probes for detection and intracellular localization of NO formation in cultured/isolated cells and intact tissues. The fluorinated derivative, 4-amino-5-methylamino-2′,7′-difluorofluorescein (DAF-FM), has gained increasing popularity in recent years due to its improved NO-sensitivity, pH-stability, and resistance to photo-bleaching compared to the first-generation compound, DAF-2. Detection of NO production by either reagent relies on conversion of the parent compound into a fluorescent triazole, DAF-FM-T and DAF-2-T, respectively. While this reaction is specific for NO and/or reactive nitrosating species, it is also affected by the presence of oxidants/antioxidants. Moreover, the reaction with other molecules can lead to the formation of fluorescent products other than the expected triazole. Thus additional controls and structural confirmation of the reaction products are essential. Using human red blood cells as an exemplary cellular system we here describe robust protocols for the analysis of intracellular DAF-FM-T formation using an array of fluorescence-based methods (laser-scanning fluorescence microscopy, flow cytometry and fluorimetry) and analytical separation techniques (reversed-phase HPLC and LC-MS/MS). When used in combination, these assays afford unequivocal identification of the fluorescent signal as being derived from NO and are applicable to most other cellular systems without or with only minor modifications.

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An automated cloud band identification procedure is developed that captures the meteorology of such events over southern Africa. This “metbot” is built upon a connected component labelling method that enables blob detection in various atmospheric fields. Outgoing longwave radiation is used to flag candidate cloud band days by thresholding the data and requiring detected blobs to have sufficient latitudinal extent and exhibit positive tilt. The Laplacian operator is used on gridded reanalysis variables to highlight other features of meteorological interest. The ability of this methodology to capture the significant meteorology and rainfall of these synoptic systems is tested in a case study. Usefulness of the metbot in understanding event to event similarities of meteorological features is demonstrated, highlighting features previous studies have noted as key ingredients to cloud band development in the region. Moreover, this allows the presentation of a composite cloud band life cycle for southern Africa events. The potential of metbot to study multiscale interactions is discussed, emphasising its key strength: the ability to retain details of extreme and infrequent events. It automatically builds a database that is ideal for research questions focused on the influence of intraseasonal to interannual variability processes on synoptic events. Application of the method to convergence zone studies and atmospheric river descriptions is suggested. In conclusion, a relation-building metbot can retain details that are often lost with object-based methods but are crucial in case studies. Capturing and summarising these details may be necessary to develop deeper process-level understanding of multiscale interactions.

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Health care provision is significantly impacted by the ability of the health providers to engineer a viable healthcare space to support care stakeholders needs. In this paper we discuss and propose use of organisational semiotics as a set of methods to link stakeholders to systems, which allows us to capture clinician activity, information transfer, and building use; which in tern allows us to define the value of specific systems in the care environment to specific stakeholders and the dependence between systems in a care space. We suggest use of a semantically enhanced building information model (BIM) to support the linking of clinician activity to the physical resource objects and space; and facilitate the capture of quantifiable data, over time, concerning resource use by key stakeholders. Finally we argue for the inclusion of appropriate stakeholder feedback and persuasive mechanism, to incentivise building user behaviour to support organisational level sustainability policy.

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The group of haemosporidian parasites is of general interest to basic and applied science, since several species infect mammals, leading to malaria and associated disease symptoms. Although the great majority of haemosporidian parasites appear in bird hosts, as in the case of Leucocytozoon buteonis, there is little genomic information about genetic aspects of their co-evolution with hosts. Consequently, there is a high need for parasite-enrichment strategies enabling further analyses of the genomes, namely without exposure to DNA-intercalating dyes. Here, we used flow cytometry without an additional labelling step to enrich L. buteonis from infected buzzard blood. A specific, defined area of two-dimensional scattergramms was sorted and the fraction was further analysed. The successful enrichment of L. buteonis in the sorted fraction was demonstrated by Giemsa-staining and qPCR revealing a clear increase of parasite-specific genes, while host-specific genes were significantly decreased. This is the first report describing a labelling-free enrichment approach of L. buteonis from infected buzzard blood. The enrichment of parasites presented here is free of nucleic acid-intercalating dyes which may interfere with fluorescence-based methods or subsequent sequencing approaches.

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Temperature is a key variable for monitoring global climate change. Here we perform a trend analysis of Swiss temperatures from 1959 to 2008, using a new 2 × 2 km gridded data-set based on carefully homogenised ground observations from MeteoSwiss. The aim of this study is twofold: first, to discuss the spatial and altitudinal temperature trend characteristics in detail, and second, to quantify the contribution of changes in atmospheric circulation and local effects to these trends. The seasonal trends are all positive and mostly significant with an annual average warming rate of 0.35 °C/decade (∼1.6 times the northern hemispheric warming rate), ranging from 0.17 in autumn to 0.48 °C/decade in summer. Altitude-dependent trends are found in autumn and early winter where the trends are stronger at low altitudes (<800 m asl), and in spring where slightly stronger trends are found at altitudes close to the snow line. Part of the trends can be explained by changes in atmospheric circulation, but with substantial differences from season to season. In winter, circulation effects account for more than half the trends, while this contribution is much smaller in other seasons. After removing the effect of circulation, the trends still show seasonal variations with higher values in spring and summer. The circulation-corrected trends are closer to the values simulated by a set of ENSEMBLES regional climate models, with the models still tending towards a trend underestimation in spring and summer. Our results suggest that both circulation changes and more local effects are important to explain part of recent warming in spring, summer, and autumn. Snow-albedo feedback effects could be responsible for the stronger spring trends at altitudes close to the snow line, but the overall effect is small. In autumn, the observed decrease in fog frequency might be a key process in explaining the stronger temperature trends at low altitudes.

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There remains large disagreement between ice-water path (IWP) in observational data sets, largely because the sensors observe different parts of the ice particle size distribution. A detailed comparison of retrieved IWP from satellite observations in the Tropics (!30 " latitude) in 2007 was made using collocated measurements. The radio detection and ranging(radar)/light detection and ranging (lidar) (DARDAR) IWP data set, based on combined radar/lidar measurements, is used as a reference because it provides arguably the best estimate of the total column IWP. For each data set, usable IWP dynamic ranges are inferred from this comparison. IWP retrievals based on solar reflectance measurements, in the moderate resolution imaging spectroradiometer (MODIS), advanced very high resolution radiometer–based Climate Monitoring Satellite Applications Facility (CMSAF), and Pathfinder Atmospheres-Extended (PATMOS-x) datasets, were found to be correlated with DARDAR over a large IWP range (~20–7000 g m -2 ). The random errors of the collocated data sets have a close to lognormal distribution, and the combined random error of MODIS and DARDAR is less than a factor of 2, which also sets the upper limit for MODIS alone. In the same way, the upper limit for the random error of all considered data sets is determined. Data sets based on passive microwave measurements, microwave surface and precipitation products system (MSPPS), microwave integrated retrieval system (MiRS), and collocated microwave only (CMO), are largely correlated with DARDAR for IWP values larger than approximately 700 g m -2 . The combined uncertainty between these data sets and DARDAR in this range is slightly less MODIS-DARDAR, but the systematic bias is nearly an order of magnitude.