985 resultados para Relative intensity


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The relationship between springtime air pollution transport of ozone (O3) and carbon monoxide (CO) and mid-latitude cyclones is explored for the first time using the Monitoring Atmospheric Composition and Climate (MACC) reanalysis for the period 2003–2012. In this study, the most intense spring storms (95th percentile) are selected for two regions, the North Pacific (NP) and the North Atlantic (NA). These storms (∼60 storms over each region) often track over the major emission sources of East Asia and eastern North America. By compositing the storms, the distributions of O3 and CO within a "typical" intense storm are examined. We compare the storm-centered composite to background composites of "average conditions" created by sampling the reanalysis data of the previous year to the storm locations. Mid-latitude storms are found to redistribute concentrations of O3 and CO horizontally and vertically throughout the storm. This is clearly shown to occur through two main mechanisms: (1) vertical lifting of CO-rich and O3-poor air isentropically, from near the surface to the mid- to upper-troposphere in the region of the warm conveyor belt; and (2) descent of O3-rich and CO-poor air isentropically in the vicinity of the dry intrusion, from the stratosphere toward the mid-troposphere. This can be seen in the composite storm's life cycle as the storm intensifies, with area-averaged O3 (CO) increasing (decreasing) between 200 and 500 hPa. The influence of the storm dynamics compared to the background environment on the composition within an area around the storm center at the time of maximum intensity is as follows. Area-averaged O3 at 300 hPa is enhanced by 50 and 36% and by 11 and 7.6% at 500 hPa for the NP and NA regions, respectively. In contrast, area-averaged CO at 300 hPa decreases by 12% for NP and 5.5% for NA, and area-averaged CO at 500 hPa decreases by 2.4% for NP while there is little change over the NA region. From the mid-troposphere, O3-rich air is clearly seen to be transported toward the surface, but the downward transport of CO-poor air is not discernible due to the high levels of CO in the lower troposphere. Area-averaged O3 is slightly higher at 1000 hPa (3.5 and 1.8% for the NP and NA regions, respectively). There is an increase of CO at 1000 hPa for the NP region (3.3%) relative to the background composite and a~slight decrease in area-averaged CO for the NA region at 1000 hPa (-2.7%).

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There is increasing concern that the intensification of dairy production reduces the concentrations of nutritionally desirable compounds in milk. This study therefore compared important quality parameters (protein and fatty acid profiles; α-tocopherol and carotenoid concentrations) in milk from four dairy systems with contrasting production intensities (in terms of feeding regimens and milking systems). The concentrations of several nutritionally desirable compounds (β-lactoglobulin, omega-3 fatty acids, omega-3/omega-6 ratio, conjugated linoleic acid c9t11, and/or carotenoids) decreased with increasing feeding intensity (organic outdoor ≥ conventional outdoor ≥ conventional indoors). Milking system intensification (use of robotic milking parlors) had a more limited effect on milk composition, but increased mastitis incidence. Multivariate analyses indicated that differences in milk quality were mainly linked to contrasting feeding regimens and that milking system and breed choice also contributed to differences in milk composition between production systems.

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Aim Most vascular plants on Earth form mycorrhizae, a symbiotic relationship between plants and fungi. Despite the broad recognition of the importance of mycorrhizae for global carbon and nutrient cycling, we do not know how soil and climate variables relate to the intensity of colonization of plant roots by mycorrhizal fungi. Here we quantify the global patterns of these relationships. Location Global. Methods Data on plant root colonization intensities by the two dominant types of mycorrhizal fungi world-wide, arbuscular (4887 plant species in 233 sites) and ectomycorrhizal fungi (125 plant species in 92 sites), were compiled from published studies. Data for climatic and soil factors were extracted from global datasets. For a given mycorrhizal type, we calculated at each site the mean root colonization intensity by mycorrhizal fungi across all potentially mycorrhizal plant species found at the site, and subjected these data to generalized additive model regression analysis with environmental factors as predictor variables. Results We show for the first time that at the global scale the intensity of plant root colonization by arbuscular mycorrhizal fungi strongly relates to warm-season temperature, frost periods and soil carbon-to-nitrogen ratio, and is highest at sites featuring continental climates with mild summers and a high availability of soil nitrogen. In contrast, the intensity of ectomycorrhizal infection in plant roots is related to soil acidity, soil carbon-to-nitrogen ratio and seasonality of precipitation, and is highest at sites with acidic soils and relatively constant precipitation levels. Main conclusions We provide the first quantitative global maps of intensity of mycorrhizal colonization based on environmental drivers, and suggest that environmental changes will affect distinct types of mycorrhizae differently. Future analyses of the potential effects of environmental change on global carbon and nutrient cycling via mycorrhizal pathways will need to take into account the relationships discovered in this study.

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The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains. The experiments show that features families, intensity self-similarity (ISS), local binary patterns (LBP), local gradient patterns (LGP) and histogram of oriented gradients (HOG), computed from FIR and visible domains are highly complementary, but their relative performance varies across different modalities. In our experiments, the FIR domain has proven superior to the visible one for the task of pedestrian classification, but the overall best results are obtained by a multi-domain multi-modality multi-feature fusion.

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The present study investigates the parsing of pre-nominal relative clauses (RCs) in children for the first time with a realtime methodology that reveals moment-to-moment processing patterns as the sentence unfolds. A self-paced listening experiment with Turkish-speaking children (aged 5–8) and adults showed that both groups display a sign of processing cost both in subject and object RCs at different points through the flow of the utterance when integrating the cues that are uninformative (i.e., ambiguous in function) and that are structurally and probabilistically unexpected. Both groups show a processing facilitation as soon as the morphosyntactic dependencies are completed and parse the unbounded dependencies rapidly using the morphosyntactic cues rather than waiting for the clause-final filler. These findings show that five-year-old children show similar patterns to adults in processing the morphosyntactic cues incrementally and in forming expectations about the rest of the utterance on the basis of the probabilistic model of their language.

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Urban greening solutions such as green roofs help improve residents’ thermal comfort and building insulation. However, not all plants provide the same level of cooling. This is partially due to differences in plant structure and function, including different mechanisms that plants employ to regulate leaf temperature. Ranking of multiple leaf/plant traits involved in the regulation of leaf temperature (and, consequently, plants’ cooling ‘service’) is not well understood. We therefore investigated the relative importance of water loss, leaf colour, thickness and extent of pubescence for the regulation of leaf temperature, in the context of species for semi-extensive green roofs. Leaf temperature were measured with an infrared imaging camera in a range of contrasting genotypes within three plant genera (Heuchera, Salvia and Sempervivum). In three glasshouse experiments (each evaluating three or four genotypes of each genera) we varied water availability to the plants and assessed how leaf temperature altered depending on water loss and specific leaf traits. Greatest reductions in leaf temperature were closely associated with higher water loss. Additionally, in non-succulents (Heuchera, Salvia), lighter leaf colour and longer hair length (on pubescent leaves) both contributed to reduced leaf temperature. However, in succulent Sempervivum, colour/pubescence made no significant contribution; leaf thickness and water loss rate were the key regulating factors. We propose that this can lead to different plant types having significantly different potentials for cooling. We suggest that maintaining transpirational water loss by sustainable irrigation and selecting urban plants with favourable morphological traits is the key to maximising thermal benefits provided by applications such as green roofs.

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We give an a posteriori analysis of a semidiscrete discontinuous Galerkin scheme approximating solutions to a model of multiphase elastodynamics, which involves an energy density depending not only on the strain but also the strain gradient. A key component in the analysis is the reduced relative entropy stability framework developed in Giesselmann (2014, SIAM J. Math. Anal., 46, 3518–3539). This framework allows energy-type arguments to be applied to continuous functions. Since we advocate the use of discontinuous Galerkin methods we make use of two families of reconstructions, one set of discrete reconstructions and a set of elliptic reconstructions to apply the reduced relative entropy framework in this setting.

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We give an a priori analysis of a semi-discrete discontinuous Galerkin scheme approximating solutions to a model of multiphase elastodynamics which involves an energy density depending not only on the strain but also the strain gradient. A key component in the analysis is the reduced relative entropy stability framework developed in Giesselmann (SIAM J Math Anal 46(5):3518–3539, 2014). The estimate we derive is optimal in the L∞(0,T;dG) norm for the strain and the L2(0,T;dG) norm for the velocity, where dG is an appropriate mesh dependent H1-like space.

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This study has explored the prediction errors of tropical cyclones (TCs) in the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) for the Northern Hemisphere summer period for five recent years. Results for the EPS are contrasted with those for the higher-resolution deterministic forecasts. Various metrics of location and intensity errors are considered and contrasted for verification based on IBTrACS and the numerical weather prediction (NWP) analysis (NWPa). Motivated by the aim of exploring extended TC life cycles, location and intensity measures are introduced based on lower-tropospheric vorticity, which is contrasted with traditional verification metrics. Results show that location errors are almost identical when verified against IBTrACS or the NWPa. However, intensity in the form of the mean sea level pressure (MSLP) minima and 10-m wind speed maxima is significantly underpredicted relative to IBTrACS. Using the NWPa for verification results in much better consistency between the different intensity error metrics and indicates that the lower-tropospheric vorticity provides a good indication of vortex strength, with error results showing similar relationships to those based on MSLP and 10-m wind speeds for the different forecast types. The interannual variation in forecast errors are discussed in relation to changes in the forecast and NWPa system and variations in forecast errors between different ocean basins are discussed in terms of the propagation characteristics of the TCs.

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Dystrophin is the product of the Duchenne muscular dystrophy (DMD) gene. Dystrophin-related protein (utrophin), an autosomal homologue of dystrophin, was studied in skeletal muscle from normal fetuses aged 9-26 weeks and one stillbirth of 41 weeks' gestation, and compared with low- and high-risk DMD fetuses aged 9-20 weeks. Utrophin was present at the sarcolemma from before 9 weeks' gestation, although there was variability in intensity both within and between myotubes. Sarcolemmal immunolabelling became more uniform, and levels of utrophin increased to a maximum at approximately 17-18 weeks. Levels then declined, until by 26 weeks sarcolemmal labelling was negligible and levels were similar to adult control muscle. By 41 weeks there was virtually no sarcolemmal labelling, although immunolabelling of capillaries was bright. Similar results were obtained with normal and DMD fetal muscle. Utrophin is therefore expressed in the presence and absence of dystrophin and down-regulated before birth in normal fetal muscle fibres. Samples were not available to determine whether or when, utrophin levels decline in DMD fetal muscle. On Western blots, utrophin was shown to have a smaller relative molecular mass than adult dystrophin, but similar to the fetal isoform. Blood vessels were brightly immunolabelled at all ages, although utrophin immunolabelling of peripheral nerves increased with gestational age.

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The contraction of a species’ distribution range, which results from the extirpation of local populations, generally precedes its extinction. Therefore, understanding drivers of range contraction is important for conservation and management. Although there are many processes that can potentially lead to local extirpation and range contraction, three main null models have been proposed: demographic, contagion, and refuge. The first two models postulate that the probability of local extirpation for a given area depends on its relative position within the range; but these models generate distinct spatial predictions because they assume either a ubiquitous (demographic) or a clinal (contagion) distribution of threats. The third model (refuge) postulates that extirpations are determined by the intensity of human impacts, leading to heterogeneous spatial predictions potentially compatible with those made by the other two null models. A few previous studies have explored the generality of some of these null models, but we present here the first comprehensive evaluation of all three models. Using descriptive indices and regression analyses we contrast the predictions made by each of the null models using empirical spatial data describing range contraction in 386 terrestrial vertebrates (mammals, birds, amphibians, and reptiles) distributed across the World. Observed contraction patterns do not consistently conform to the predictions of any of the three models, suggesting that these may not be adequate null models to evaluate range contraction dynamics among terrestrial vertebrates. Instead, our results support alternative null models that account for both relative position and intensity of human impacts. These new models provide a better multifactorial baseline to describe range contraction patterns in vertebrates. This general baseline can be used to explore how additional factors influence contraction, and ultimately extinction for particular areas or species as well as to predict future changes in light of current and new threats.

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The importance of managing land to optimise carbon sequestration for climate change mitigation is widely recognised, with grasslands being identified as having the potential to sequester additional carbon. However, most soil carbon inventories only consider surface soils, and most large scale surveys group ecosystems into broad habitats without considering management intensity. Consequently, little is known about the quantity of deep soil carbon and its sensitivity to management. From a nationwide survey of grassland soils to 1 m depth, we show that carbon in grasslands soils is vulnerable to management and that these management effects can be detected to considerable depth down the soil profile, albeit at decreasing significance with depth. Carbon concentrations in soil decreased as management intensity increased, but greatest soil carbon stocks (accounting for bulk density differences), were at intermediate levels of management. Our study also highlights the considerable amounts of carbon in sub-surface soil below 30cm, which is missed by standard carbon inventories. We estimate grassland soil carbon in Great Britain to be 2097 Tg C to a depth of 1 m, with ~60% of this carbon being below 30cm. Total stocks of soil carbon (t ha-1) to 1 m depth were 10.7% greater at intermediate relative to intensive management, which equates to 10.1 t ha-1 in surface soils (0-30 cm), and 13.7 t ha-1 in soils from 30-100 cm depth. Our findings highlight the existence of substantial carbon stocks at depth in grassland soils that are sensitive to management. This is of high relevance globally, given the extent of land cover and large stocks of carbon held in temperate managed grasslands. Our findings have implications for the future management of grasslands for carbon storage and climate mitigation, and for global carbon models which do not currently account for changes in soil carbon to depth with management.

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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.