66 resultados para fast electrons

em CentAUR: Central Archive University of Reading - UK


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Jupiter’s magnetosphere acts as a point source of near-relativistic electrons within the heliosphere. In this study, three solar cycles of Jovian electron data in near-Earth space are examined. Jovian electron intensity is found to peak for an ideal Parker spiral connection, but with considerable spread about this point. Assuming the peak in Jovian electron counts indicates the best magnetic connection to Jupiter, we find a clear trend for fast and slow solar wind to be over- and under-wound with respect to the ideal Parker spiral, respectively. This is shown to be well explained in terms of solar wind stream interactions. Thus, modulation of Jovian electrons by corotating interaction regions (CIRs) may primarily be the result of changing magnetic connection, rather than CIRs acting as barriers to cross-field diffusion. By using Jovian electrons to remote sensing magnetic connectivity with Jupiter’s magnetosphere, we suggest that they provide a means to validate solar wind models between 1 and 5 AU, even when suitable in situ solar wind observations are not available. Furthermore, using Jovian electron observations as probes of heliospheric magnetic topology could provide insight into heliospheric magnetic field braiding and turbulence, as well as any systematic under-winding of the heliospheric magnetic field relative to the Parker spiral from footpoint motion of the magnetic field.

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A fast radiative transfer model (RTM) to compute emitted infrared radiances for a very high resolution radiometer (VHRR), onboard the operational Indian geostationary satellite Kalpana has been developed and verified. This work is a step towards the assimilation of Kalpana water vapor (WV) radiances into numerical weather prediction models. The fast RTM uses a regression‐based approach to parameterize channel‐specific convolved level to space transmittances. A comparison between the fast RTM and the line‐by‐line RTM demonstrated that the fast RTM can simulate line‐by‐line radiances for the Kalpana WV channel to an accuracy better than the instrument noise, while offering more rapid radiance calculations. A comparison of clear sky radiances of the Kalpana WV channel with the ECMWF model first guess radiances is also presented, aiming to demonstrate the fast RTM performance with the real observations. In order to assimilate the radiances from Kalpana, a simple scheme for bias correction has been suggested.

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Here, we identify the Arabidopsis thaliana ortholog of the mammalian DEAD box helicase, eIF4A-III, the putative anchor protein of exon junction complex (EJC) on mRNA. Arabidopsis eIF4A-III interacts with an ortholog of the core EJC component, ALY/Ref, and colocalizes with other EJC components, such as Mago, Y14, and RNPS1, suggesting a similar function in EJC assembly to animal eIF4A-III. A green fluorescent protein (GFP)-eIF4A-III fusion protein showed localization to several subnuclear domains: to the nucleoplasm during normal growth and to the nucleolus and splicing speckles in response to hypoxia. Treatment with the respiratory inhibitor sodium azide produced an identical response to the hypoxia stress. Treatment with the proteasome inhibitor MG132 led to accumulation of GFP-eIF4A-III mainly in the nucleolus, suggesting that transition of eIF4A-III between subnuclear domains and/or accumulation in nuclear speckles is controlled by proteolysis-labile factors. As revealed by fluorescence recovery after photobleaching analysis, the nucleoplasmic fraction was highly mobile, while the speckles were the least mobile fractions, and the nucleolar fraction had an intermediate mobility. Sequestration of eIF4A-III into nuclear pools with different mobility is likely to reflect the transcriptional and mRNA processing state of the cell.

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Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen’s Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.

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An efficient method is described for the approximate calculation of the intensity of multiply scattered lidar returns. It divides the outgoing photons into three populations, representing those that have experienced zero, one, and more than one forward-scattering event. Each population is parameterized at each range gate by its total energy, its spatial variance, the variance of photon direction, and the covariance, of photon direction and position. The result is that for an N-point profile the calculation is O(N-2) efficient and implicitly includes up to N-order scattering, making it ideal for use in iterative retrieval algorithms for which speed is crucial. In contrast, models that explicitly consider each scattering order separately are at best O(N-m/m!) efficient for m-order scattering and often cannot be performed to more than the third or fourth order in retrieval algorithms. For typical cloud profiles and a wide range of lidar fields of view, the new algorithm is as accurate as an explicit calculation truncated at the fifth or sixth order but faster by several orders of magnitude. (C) 2006 Optical Society of America.

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Three experiments examine whether simple pair-wise comparison judgments, involving the “recognition heuristic” (Goldstein & Gigerenzer, 2002), are sensitive to implicit cues to the nature of the comparison required. Experiments 1 & 2 show that participants frequently choose the recognized option of a pair if asked to make “larger” judgments but are significantly less likely to choose the unrecognized option when asked to make “smaller” judgments. Experiment 3 demonstrates that, overall, participants consider recognition to be a more reliable guide to judgments of a magnitude criterion than lack of recognition and that this intuition drives the framing effect. These results support the idea that, when making pair-wise comparison judgments, inferring that the recognized item is large is simpler than inferring that the unrecognized item is small.

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Magnetic clouds are a subset of interplanetary coronal mass ejections characterized by a smooth rotation in the magnetic field direction, which is interpreted as a signature of a magnetic flux rope. Suprathermal electron observations indicate that one or both ends of a magnetic cloud typically remain connected to the Sun as it moves out through the heliosphere. With distance from the axis of the flux rope, out toward its edge, the magnetic field winds more tightly about the axis and electrons must traverse longer magnetic field lines to reach the same heliocentric distance. This increased time of flight allows greater pitch-angle scattering to occur, meaning suprathermal electron pitch-angle distributions should be systematically broader at the edges of the flux rope than at the axis. We model this effect with an analytical magnetic flux rope model and a numerical scheme for suprathermal electron pitch-angle scattering and find that the signature of a magnetic flux rope should be observable with the typical pitch-angle resolution of suprathermal electron data provided ACE's SWEPAM instrument. Evidence of this signature in the observations, however, is weak, possibly because reconnection of magnetic fields within the flux rope acts to intermix flux tubes.

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Suprathermal electrons (>70 eV) form a small fraction of the total solar wind electron density but serve as valuable tracers of heliospheric magnetic field topology. Their usefulness as tracers of magnetic loops with both feet rooted on the Sun, however, most likely fades as the loops expand beyond some distance owing to scattering. As a first step toward quantifying that distance, we construct an observationally constrained model for the evolution of the suprathermal electron pitch-angle distributions on open field lines. We begin with a near-Sun isotropic distribution moving antisunward along a Parker spiral magnetic field while conserving magnetic moment, resulting in a field-aligned strahl within a few solar radii. Past this point, the distribution undergoes little evolution with heliocentric distance. We then add constant (with heliocentric distance, energy, and pitch angle) ad-hoc pitch-angle scattering. Close to the Sun, pitch-angle focusing still dominates, again resulting in a narrow strahl. Farther from the Sun, however, pitch-angle scattering dominates because focusing is effectively weakened by the increasing angle between the magnetic field direction and intensity gradient, a result of the spiral field. We determine the amount of scattering required to match Ulysses observations of strahl width in the fast solar wind, providing an important tool for inferring the large-scale properties and topologies of field lines in the interplanetary medium. Although the pitch-angle scattering term is independent of energy, time-of-flight effects in the spiral geometry result in an energy dependence of the strahl width that is in the observed sense although weaker in magnitude.

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Suprathermal electrons (E > 80 eV) carry heat flux away from the Sun. Processes controlling the heat flux are not well understood. To gain insight into these processes, we model heat flux as a linear dependence on two independent parameters: electron number flux and electron pitch angle anisotropy. Pitch angle anisotropy is further modeled as a linear dependence on two solar wind components: magnetic field strength and plasma density. These components show no correlation with number flux, reinforcing its independence from pitch angle anisotropy. Multiple linear regression applied to 2 years of Wind data shows good correspondence between modeled and observed heat flux and anisotropy. The results suggest that the interplay of solar wind parameters and electron number flux results in distinctive heat flux dropouts at heliospheric features like plasma sheets but that these parameters continuously modify heat flux. This is inconsistent with magnetic disconnection as the primary cause of heat flux dropouts. Analysis of fast and slow solar wind regimes separately shows that electron number flux and pitch angle anisotropy are equally correlated with heat flux in slow wind but that number flux is the dominant correlative in fast wind. Also, magnetic field strength correlates better with pitch angle anisotropy in slow wind than in fast wind. The energy dependence of the model fits suggests different scattering processes in fast and slow wind.