49 resultados para Radial architectures

em CentAUR: Central Archive University of Reading - UK


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As a soil dries, the earthworms in that soil dehydrate and become less active. Moisture stress may weaken an earthworm, lowering the radial pressure that the animal can produce. This possibility was investigated for the earthworm Aporrectodea caliginosa (Savigny). Pressures were compared for saturated earthworms (worms taken from saturated soil) and stressed earthworms (worms that had been partially dehydrated by leaving them in dry soil). A load cell was used to record the forces that earthworms produced as they moved through artificial burrows (holes that had been drilled through blocks of aluminium or Perspex). The radial pressure was calculated using the forces exerted and the dimensions of the artificial burrows. There was a negative correlation between burrow diameter and radial pressure, although radial pressure was independent of the length of the block through which the earthworms had burrowed. The highest radial pressures were produced by the anterior segments of the animal. Partial dehydration caused the earthworms to become quiescent, but did not decrease the radial pressure that the earthworms produced. It is suggested that coelomic fluid is retained in the anterior segments while the rest of the animal dehydrates. Dehydrated earthworms became lethargic, and we suggest that lethargy is due to the loss of coelomic fluid from the posterior segments. Coelomic fluid is known to be lost through dorsal pores. In burrowing species of earthworm such as Aporrectodea caliginosa, these pores are only present on the posterior segments.

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On 15-17 February 2008, a CME with an approximately circular cross section was tracked through successive images obtained by the Heliospheric Imager (HI) instrument onboard the STEREO-A spacecraft. Reasoning that an idealised flux rope is cylindrical in shape with a circular cross-section, best fit circles are used to determine the radial width of the CME. As part of the process the radial velocity and longitude of propagation are determined by fits to elongation-time maps as 252±5 km/s and 70±5° respectively. With the longitude known, the radial size is calculated from the images, taking projection effects into account. The radial width of the CME, S (AU), obeys a power law with heliocentric distance, R, as the CME travels between 0.1 and 0.4 AU, such that S=0.26 R0.6±0.1. The exponent value obtained is compared to published studies based on statistical surveys of in situ spacecraft observations of ICMEs between 0.3 and 1.0 AU, and general agreement is found. This paper demonstrates the new opportunities provided by HI to track the radial width of CMEs through the previously unobservable zone between the LASCO field of view and Helios in situ measurements.

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We survey observations of the radial magnetic field in the heliosphere as a function of position, sunspot number, and sunspot cycle phase. We show that most of the differences between pairs of simultaneous observations, normalized using the square of the heliocentric distance and averaged over solar rotations, are consistent with the kinematic "flux excess" effect whereby the radial component of the frozen-in heliospheric field is increased by longitudinal solar wind speed structure. In particular, the survey shows that, as expected, the flux excess effect at high latitudes is almost completely absent during sunspot minimum but is almost the same as within the streamer belt at sunspot maximum. We study the uncertainty inherent in the use of the Ulysses result that the radial field is independent of heliographic latitude in the computation of the total open solar flux: we show that after the kinematic correction for the excess flux effect has been made it causes errors that are smaller than 4.5%, with a most likely value of 2.5%. The importance of this result for understanding temporal evolution of the open solar flux is reviewed.

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A survey of the non-radial flows (NRFs) during nearly five years of interplanetary observations revealed the average non-radial speed of the solar wind flows to be �30 km/s, with approximately one-half of the large (>100 km/s) NRFs associated with ICMEs. Conversely, the average non-radial flow speed upstream of all ICMEs is �100 km/s, with just over one-third preceded by large NRFs. These upstream flow deflections are analysed in the context of the large-scale structure of the driving ICME. We chose 5 magnetic clouds with relatively uncomplicated upstream flow deflections. Using variance analysis it was possible to infer the local axis orientation, and to qualitatively estimate the point of interception of the spacecraft with the ICME. For all 5 events the observed upstream flows were in agreement with the point of interception predicted by variance analysis. Thus we conclude that the upstream flow deflections in these events are in accord with the current concept of the large scale structure of an ICME: a curved axial loop connected to the Sun, bounded by a curved (though not necessarily circular)cross section.

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The dibenzodioxatetraazamacrocycle [26]pbz(2)N(4)O(2) was characterised by single crystal X-ray diffraction and the protonation constants of this compound and the stability constants of its copper(II) and lead(II) complexes were determined by potentiometry in water at 298.2 K in 0.10 mol dm(-3) in KNO3. Mono- and dinuclear complexes were found for both metal ions, the dinuclear complexes being the main species in the 5-7.5 pH range for copper(II) and 7.5-8.5 for lead(II). As expected the values of the stability constants for the copper(II) complexes are lower than those for related macrocycles containing only nitrogen atoms. The presence of mono- and dinuclear copper complexes was also confirmed by electrospray ionization mass spectrometry. These results suggest that the symmetric macrocyclic cavity of [26]pbZ(2)N(4)O(2) has enough space for the coordination of two metal ions. Additionally, NMR spectroscopy showed that the dinuclear complex of lead(II) has high symmetry. The equilibrium constants of the dinuclear copper(II) complexes and dicarboxylate anions (oxalate, malonate and succinate) were also determined in 0.10 mol dm-3 aqueous KNO3 solution. Only species containing one anion, Cu(2)H(h)LA((2+h)), were found, strongly suggesting that the anion bridges the two copper(II) ions. The binding constants of the cascade species formed by [Cu-2[26]pbZ(2)N(4)O(2)(H2O)(4+) with dicarboxylate anions decrease with the increase in length of the alkyl chain of the anion, a fact which was attributed to a higher conformational energy necessary for the rearrangement of the macrocycle to accommodate the larger anions bridging the two copper(II) centres. The variation of the magnetic susceptibility with temperature Of [Cu-2(H-2[26]pbz(2)N(4)O(2))(oxa)(3)]-4H(2)O and [Cu-2([26]pbz(2)N(4)O(2))(suc)Cl-2] were measured and the two complexes showed different behaviour. (c) 2007 Elsevier Ltd. All rights reserved.

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Two mononuclear complexes of manganese(II), [Mn(OCN)(2)(phen)(2)] 1 and [Mn(NCO)(2)(bpy)(2)] 2 [1,10-phenanthroline (phen); 2,2'-bipyridine (bpy)], have been synthesized and characterized by single crystal X-ray analysis, infra-red spectroscopy and magnetic studies. The coordination structure of complex 2 is already reported. The cyanate anions are pendent in both the complexes. In 1, cyanate anion links manganese(II) through O-atom, whereas in 2 it coordinates through N-atom. The mononuclear fragments of 1 are built up to a supramolecular lamellar 3D architecture by pi-pi interactions only. On the other hand, mononuclear fragments of 2 are assembled to a 2D supramolecular brick-wall architecture by C-H-... pi interactions.

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This mini-review outlines recent key developments in the use of dendritic architectures in self-assembly processes via utilisation of molecular recognition motifs.

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With the latest advances in the area of advanced computer architectures we are seeing already large scale machines at petascale level and we are discussing exascale computing. All these require efficient scalable algorithms in order to bridge the performance gap. In this paper examples of various approaches of designing scalable algorithms for such advanced architectures will be given and the corresponding properties of these algorithms will be outlined and discussed. Examples will outline such scalable algorithms applied to large scale problems in the area Computational Biology, Environmental Modelling etc. The key properties of such advanced and scalable algorithms will be outlined.

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We consider a fully complex-valued radial basis function (RBF) network for regression application. The locally regularised orthogonal least squares (LROLS) algorithm with the D-optimality experimental design, originally derived for constructing parsimonious real-valued RBF network models, is extended to the fully complex-valued RBF network. Like its real-valued counterpart, the proposed algorithm aims to achieve maximised model robustness and sparsity by combining two effective and complementary approaches. The LROLS algorithm alone is capable of producing a very parsimonious model with excellent generalisation performance while the D-optimality design criterion further enhances the model efficiency and robustness. By specifying an appropriate weighting for the D-optimality cost in the combined model selecting criterion, the entire model construction procedure becomes automatic. An example of identifying a complex-valued nonlinear channel is used to illustrate the regression application of the proposed fully complex-valued RBF network.

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A basic principle in data modelling is to incorporate available a priori information regarding the underlying data generating mechanism into the modelling process. We adopt this principle and consider grey-box radial basis function (RBF) modelling capable of incorporating prior knowledge. Specifically, we show how to explicitly incorporate the two types of prior knowledge: the underlying data generating mechanism exhibits known symmetric property and the underlying process obeys a set of given boundary value constraints. The class of orthogonal least squares regression algorithms can readily be applied to construct parsimonious grey-box RBF models with enhanced generalisation capability.