26 resultados para Serial-correlation common features
Resumo:
The response of ten atmospheric general circulation models to orbital forcing at 6 kyr BP has been investigated using the BIOME model, which predicts equilibrium vegetation distribution, as a diagnostic. Several common features emerge: (a) reduced tropical rain forest as a consequence of increased aridity in the equatorial zone, (b) expansion of moisture-demanding vegetation in the Old World subtropics as a consequence of the expansion of the Afro–Asian monsoon, (c) an increase in warm grass/shrub in the Northern Hemisphere continental interiors in response to warming and enhanced aridity, and (d) a northward shift in the tundra–forest boundary in response to a warmer growing season at high northern latitudes. These broadscale features are consistent from model to model, but there are differences in their expression at a regional scale. Vegetation changes associated with monsoon enhancement and high-latitude summer warming are consistent with palaeoenvironmental observations, but the simulated shifts in vegetation belts are too small in both cases. Vegetation changes due to warmer and more arid conditions in the midcontinents of the Northern Hemisphere are consistent with palaeoenvironmental data from North America, but data from Eurasia suggests conditions were wetter at 6 kyr BP than today. The models show quantitatively similar vegetation changes in the intertropical zone, and in the northern and southern extratropics. The small differences among models in the magnitude of the global vegetation response are not related to differences in global or zonal climate averages, but reflect differences in simulated regional features. Regional-scale analyses will therefore be necessary to identify the underlying causes of such differences among models.
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On-going human population growth and changing patterns of resource consumption are increasing global demand for ecosystem services, many of which are provided by soils. Some of these ecosystem services are linearly related to the surface area of pervious soil, whereas others show non-linear relationships, making ecosystem service optimization a complex task. As limited land availability creates conflicting demands among various types of land use, a central challenge is how to weigh these conflicting interests and how to achieve the best solutions possible from a perspective of sustainable societal development. These conflicting interests become most apparent in soils that are the most heavily used by humans for specific purposes: urban soils used for green spaces, housing, and other infrastructure and agricultural soils for producing food, fibres and biofuels. We argue that, despite their seemingly divergent uses of land, agricultural and urban soils share common features with regards to interactions between ecosystem services, and that the trade-offs associated with decision-making, while scale- and context-dependent, can be surprisingly similar between the two systems. We propose that the trade-offs within land use types and their soil-related ecosystems services are often disproportional, and quantifying these will enable ecologists and soil scientists to help policy makers optimizing management decisions when confronted with demands for multiple services under limited land availability.
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Researchers are increasingly relying on e-journals to access literature within their fields. The design of the interfaces to these journals is determined by the individual host or publisher and there appears to be little standardization. This exploratory study samples a set of sixteen home screens of e-journals from different disciplines and identifies common features across the set. The particular wording used to identify the features and their locations are recorded. An online survey of e-journal readers investigates where users would normally expect to locate features when first accessing a journal article. Comparison of observed and expected locations confirms inconsistencies across interfaces in terminology and locations. Mental models of the interface design do not appear to be well developed. A move toward standardization, based on some existing conventions, is desirable.
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Background. The anaerobic spirochaete Brachyspira pilosicoli causes enteric disease in avian, porcine and human hosts, amongst others. To date, the only available genome sequence of B. pilosicoli is that of strain 95/1000, a porcine isolate. In the first intra-species genome comparison within the Brachyspira genus, we report the whole genome sequence of B. pilosicoli B2904, an avian isolate, the incomplete genome sequence of B. pilosicoli WesB, a human isolate, and the comparisons with B. pilosicoli 95/1000. We also draw on incomplete genome sequences from three other Brachyspira species. Finally we report the first application of the high-throughput Biolog phenotype screening tool on the B. pilosicoli strains for detailed comparisons between genotype and phenotype. Results. Feature and sequence genome comparisons revealed a high degree of similarity between the three B. pilosicoli strains, although the genomes of B2904 and WesB were larger than that of 95/1000 (~2,765, 2.890 and 2.596 Mb, respectively). Genome rearrangements were observed which correlated largely with the positions of mobile genetic elements. Through comparison of the B2904 and WesB genomes with the 95/1000 genome, features that we propose are non-essential due to their absence from 95/1000 include a peptidase, glycine reductase complex components and transposases. Novel bacteriophages were detected in the newly-sequenced genomes, which appeared to have involvement in intra- and inter-species horizontal gene transfer. Phenotypic differences predicted from genome analysis, such as the lack of genes for glucuronate catabolism in 95/1000, were confirmed by phenotyping. Conclusions. The availability of multiple B. pilosicoli genome sequences has allowed us to demonstrate the substantial genomic variation that exists between these strains, and provides an insight into genetic events that are shaping the species. In addition, phenotype screening allowed determination of how genotypic differences translated to phenotype. Further application of such comparisons will improve understanding of the metabolic capabilities of Brachyspira species.
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Summary Reasons for performing study: Metabonomics is emerging as a powerful tool for disease screening and investigating mammalian metabolism. This study aims to create a metabolic framework by producing a preliminary reference guide for the normal equine metabolic milieu. Objectives: To metabolically profile plasma, urine and faecal water from healthy racehorses using high resolution 1H-NMR spectroscopy and to provide a list of dominant metabolites present in each biofluid for the benefit of future research in this area. Study design: This study was performed using seven Thoroughbreds in race training at a single time-point. Urine and faecal samples were collected non-invasively and plasma was obtained from samples taken for routine clinical chemistry purposes. Methods: Biofluids were analysed using 1H-NMR spectroscopy. Metabolite assignment was achieved via a range of 1D and 2D experiments. Results: A total of 102 metabolites were assigned across the three biological matrices. A core metabonome of 14 metabolites was ubiquitous across all biofluids. All biological matrices provided a unique window on different aspects of systematic metabolism. Urine was the most populated metabolite matrix with 65 identified metabolites, 39 of which were unique to this biological compartment. A number of these were related to gut microbial host co-metabolism. Faecal samples were the most metabolically variable between animals; acetate was responsible for the majority (28%) of this variation. Short chain fatty acids were the predominant features identified within this biofluid by 1H-NMR spectroscopy. Conclusions: Metabonomics provides a platform for investigating complex and dynamic interactions between the host and its consortium of gut microbes and has the potential to uncover markers for health and disease in a variety of biofluids. Inherent variation in faecal extracts along with the relative abundance of microbial-mammalian metabolites in urine and invasive nature of plasma sampling, infers that urine is the most appropriate biofluid for the purposes of metabonomic analysis.
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Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.
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This study has investigated serial (temporal) clustering of extra-tropical cyclones simulated by 17 climate models that participated in CMIP5. Clustering was estimated by calculating the dispersion (ratio of variance to mean) of 30 December-February counts of Atlantic storm tracks passing nearby each grid point. Results from single historical simulations of 1975-2005 were compared to those from historical ERA40 reanalyses from 1958-2001 ERA40 and single future model projections of 2069-2099 under the RCP4.5 climate change scenario. Models were generally able to capture the broad features in reanalyses reported previously: underdispersion/regularity (i.e. variance less than mean) in the western core of the Atlantic storm track surrounded by overdispersion/clustering (i.e. variance greater than mean) to the north and south and over western Europe. Regression of counts onto North Atlantic Oscillation (NAO) indices revealed that much of the overdispersion in the historical reanalyses and model simulations can be accounted for by NAO variability. Future changes in dispersion were generally found to be small and not consistent across models. The overdispersion statistic, for any 30 year sample, is prone to large amounts of sampling uncertainty that obscures the climate change signal. For example, the projected increase in dispersion for storm counts near London in the CNRMCM5 model is 0.1 compared to a standard deviation of 0.25. Projected changes in the mean and variance of NAO are insufficient to create changes in overdispersion that are discernible above natural sampling variations.
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Holm oak (Quercus ilex), a widespread urban street tree in the Mediterranean region, is widely used as biomonitor of persistent atmospheric pollutants, especially particulate-bound metals. By using lab- and field-based experimental approaches, we compared the leaf-level capacity for particles’ capture and retention between Q. ilex and other common Mediterranean urban trees: Quercus cerris, Platanus × hispanica, Tilia cordata and Olea europaea. All applied methods were effective in quantifying particulate capture and retention, although not univocal in ranking species performances. Distinctive morphological features of leaves led to differences in species’ ability to trap and retain particles of different size classes and to accumulate metals after exposure to traffic in an urban street. Overall, P. × hispanica and T. cordata showed the largest capture potential per unit leaf area for most model particles (Na+ and powder particles), and street-level Cu and Pb, while Q. ilex acted intermediately. After wash-off experiments, P. × hispanica leaves had the greatest retention capacity among the tested species and O. europaea the lowest. We concluded that the Platanus planting could be considered in Mediterranean urban environments due to its efficiency in accumulating and retaining airborne particulates; however, with atmospheric pollution being typically higher in winter, the evergreen Q. ilex represents a better year-round choice to mitigate the impact of airborne particulate pollutants.
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Background Autism spectrum conditions (ASC) are a group of neurodevelopmental conditions characterized by difficulties in social interaction and communication alongside repetitive and stereotyped behaviours. ASC are heritable, and common genetic variants contribute substantial phenotypic variability. More than 600 genes have been implicated in ASC to date. However, a comprehensive investigation of candidate gene association studies in ASC is lacking. Methods In this study, we systematically reviewed the literature for association studies for 552 genes associated with ASC. We identified 58 common genetic variants in 27 genes that have been investigated in three or more independent cohorts and conducted a meta-analysis for 55 of these variants. We investigated publication bias and sensitivity and performed stratified analyses for a subset of these variants. Results We identified 15 variants nominally significant for the mean effect size, 8 of which had P values below a threshold of significance of 0.01. Of these 15 variants, 11 were re-investigated for effect sizes and significance in the larger Psychiatric Genomics Consortium dataset, and none of them were significant. Effect direction for 8 of the 11 variants were concordant between both the datasets, although the correlation between the effect sizes from the two datasets was poor and non-significant. Conclusions This is the first study to comprehensively examine common variants in candidate genes for ASC through meta-analysis. While for majority of the variants, the total sample size was above 500 cases and 500 controls, the total sample size was not large enough to accurately identify common variants that contribute to the aetiology of ASC.
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An in vitro study was conducted to investigate the effects of condensed tannins (CT) structural properties, i.e. average polymer size (or mean degree of polymerization); percentage of cis flavan-3-ols and percentage of prodelphinidins in CT extracts on methane production (CH4) and fermentation characteristics. CT were extracted from eight plants in order to obtain different CT types: black currant leaves, goat willow leaves, goat willow twigs, pine bark, red currant leaves, sainfoin plants, weeping willow catkins and white clover flowers. They were analysed for CT content and CT composition by thiolytic degradation, followed by HPLC analysis. Grass silage was used as a control substrate. Condensed tannins were added to the substrate at a concentration of 40 g/kg, with or without polyethylene glycol (+ or −PEG 6000 treatment) to inactivate tannins, and then incubated for 72 h in mixed buffered rumen fluid from three different lactating dairy cows per run. Total cumulative gas production (GP) was measured by an automated gas production system. During the incubation, 12 gas samples (10 μl) were collected from each bottle headspace at 0, 2, 4, 6, 8, 12, 24, 30, 36, 48, 56 and 72 h of incubation and analyzed for CH4. A modified Michaelis–Menten model was fitted to the CH4 concentration patterns and model estimates were used to calculate total cumulative CH4 production (GPCH4). Total cumulative gas production and GPCH4 curves were fitted using biphasic and monophasic modified Michaelis-Menten models, respectively. Addition of PEG increased GP, GPCH4, and CH4 concentration compared to the −PEG treatment. All CT types reduced GPCH4 and CH4 concentration. All CT increased the half time of GP and GPCH4. Moreover, all CT decreased the maximum rate of fermentation for GPCH4 and rate of substrate degradation. The correlation between CT structure and GPCH4 and fermentation characteristics showed that the proportion of prodelphinidins within CT had the largest effect on fermentation characteristics, followed by average 27 polymer size and percentage of cis-flavan-3-ols.
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The challenge of moving past the classic Window Icons Menus Pointer (WIMP) interface, i.e. by turning it ‘3D’, has resulted in much research and development. To evaluate the impact of 3D on the ‘finding a target picture in a folder’ task, we built a 3D WIMP interface that allowed the systematic manipulation of visual depth, visual aides, semantic category distribution of targets versus non-targets; and the detailed measurement of lower-level stimuli features. Across two separate experiments, one large sample web-based experiment, to understand associations, and one controlled lab environment, using eye tracking to understand user focus, we investigated how visual depth, use of visual aides, use of semantic categories, and lower-level stimuli features (i.e. contrast, colour and luminance) impact how successfully participants are able to search for, and detect, the target image. Moreover in the lab-based experiment, we captured pupillometry measurements to allow consideration of the influence of increasing cognitive load as a result of either an increasing number of items on the screen, or due to the inclusion of visual depth. Our findings showed that increasing the visible layers of depth, and inclusion of converging lines, did not impact target detection times, errors, or failure rates. Low-level features, including colour, luminance, and number of edges, did correlate with differences in target detection times, errors, and failure rates. Our results also revealed that semantic sorting algorithms significantly decreased target detection times. Increased semantic contrasts between a target and its neighbours correlated with an increase in detection errors. Finally, pupillometric data did not provide evidence of any correlation between the number of visible layers of depth and pupil size, however, using structural equation modelling, we demonstrated that cognitive load does influence detection failure rates when there is luminance contrasts between the target and its surrounding neighbours. Results suggest that WIMP interaction designers should consider stimulus-driven factors, which were shown to influence the efficiency with which a target icon can be found in a 3D WIMP interface.