5 resultados para complex particle

em CentAUR: Central Archive University of Reading - UK


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The particle size distributions of surface soils from two cultivated silty fields (Moorfield and Railway South) in Herefordshire, UK, were assessed by sampling on 20-m grids across the fields. Moorfield (8 ha) had a uniform landscape sloping mainly in a North-South direction while Railway South (12 ha) had complex undulating landscape characteristics. Samples from 3 surficial layers were also taken at 3 landscape positions at Moorfield to investigate recent (within-season) soil particle redistribution. Size fractions were determined using chemical dispersion, wet sieving (to separate the sand fractions) and laser gramilometry (for the finer fractions). The distribution of various fractions and the relationships between elevation and the various fractions suggest preferential detachment and movement of coarse to very coarse silt fractions (16-63 mu m), which were found mostly at downslope or depositional areas. Upper slope samples had higher clay to fine silt (< 16 mu m) contents than bottom slope samples. The upslope-downslope patterns of size fractions, particularly on uniformly sloping areas, of the 2 fields were similar and their deposited sediments were dominated by coarse silt fractions. Samples from 3 landscape positions at Moorfield became coarser from the less eroded summit, through the eroding side-slope to the bottom-slope depositional area. Within each of these landscape positions the top 0-2.5 cm layers were more enriched in coarse silt fractions than the bottom layers. The spatial patterns of soil particle size distributions in the 2 fields may be a result of sediment detachment and deposition caused by water erosion and tillage operations. (c) 2005 Elsevier B.V. All rights reserved.

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Hydrophobic chemicals are known to associate with sediment particles including those from both suspended particulate matter and bottom deposits. The complex and variable composition of natural particles makes it very difficult therefore, to predict the bioavailability of sediment-bound contaminants. To overcome these problems we have previously devised a test system using artificial particles, with or without humic acids, for use as an experimental model of natural sediments. In the present work we have applied this experimental technique to investigate the bioavailability and bioaccumulation of pyrene by the freshwater fingernail clam Sphaerium corneum. The uptake and accumulation of pyrene in clams exposed to the chemical in the presence of a sample of natural sediment was also investigated. According to the results obtained, particle surface properties and organic matter content are the key factors for assessing the bioavailability and bioaccumulation of pyrene by clams. (C) 2002 Elsevier Science Ltd. All rights reserved.

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Almost all research fields in geosciences use numerical models and observations and combine these using data-assimilation techniques. With ever-increasing resolution and complexity, the numerical models tend to be highly nonlinear and also observations become more complicated and their relation to the models more nonlinear. Standard data-assimilation techniques like (ensemble) Kalman filters and variational methods like 4D-Var rely on linearizations and are likely to fail in one way or another. Nonlinear data-assimilation techniques are available, but are only efficient for small-dimensional problems, hampered by the so-called ‘curse of dimensionality’. Here we present a fully nonlinear particle filter that can be applied to higher dimensional problems by exploiting the freedom of the proposal density inherent in particle filtering. The method is illustrated for the three-dimensional Lorenz model using three particles and the much more complex 40-dimensional Lorenz model using 20 particles. By also applying the method to the 1000-dimensional Lorenz model, again using only 20 particles, we demonstrate the strong scale-invariance of the method, leading to the optimistic conjecture that the method is applicable to realistic geophysical problems. Copyright c 2010 Royal Meteorological Society

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Nonlinear data assimilation is high on the agenda in all fields of the geosciences as with ever increasing model resolution and inclusion of more physical (biological etc.) processes, and more complex observation operators the data-assimilation problem becomes more and more nonlinear. The suitability of particle filters to solve the nonlinear data assimilation problem in high-dimensional geophysical problems will be discussed. Several existing and new schemes will be presented and it is shown that at least one of them, the Equivalent-Weights Particle Filter, does indeed beat the curse of dimensionality and provides a way forward to solve the problem of nonlinear data assimilation in high-dimensional systems.

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Retrograde transport of NF-κB from the synapse to the nucleus in neurons is mediated by the dynein/dynactin motor complex and can be triggered by synaptic activation. The calibre of axons is highly variable ranging down to 100 nm, aggravating the investigation of transport processes in neurites of living neurons using conventional light microscopy. In this study we quantified for the first time the transport of the NF-κB subunit p65 using high-density single-particle tracking in combination with photoactivatable fluorescent proteins in living mouse hippocampal neurons. We detected an increase of the mean diffusion coefficient (Dmean) in neurites from 0.12 ± 0.05 µm2/s to 0.61 ± 0.03 µm2/s after stimulation with glutamate. We further observed that the relative amount of retrogradely transported p65 molecules is increased after stimulation. Glutamate treatment resulted in an increase of the mean retrograde velocity from 10.9 ± 1.9 to 15 ± 4.9 µm/s, whereas a velocity increase from 9 ± 1.3 to 14 ± 3 µm/s was observed for anterogradely transported p65. This study demonstrates for the first time that glutamate stimulation leads to an increased mobility of single NF-κB p65 molecules in neurites of living hippocampal neurons.