999 resultados para Visibility distance.


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Context. The ESA Rosetta spacecraft, currently orbiting around cornet 67P/Churyumov-Gerasimenko, has already provided in situ measurements of the dust grain properties from several instruments, particularly OSIRIS and GIADA. We propose adding value to those measurements by combining them with ground-based observations of the dust tail to monitor the overall, time-dependent dust-production rate and size distribution. Aims. To constrain the dust grain properties, we take Rosetta OSIRIS and GIADA results into account, and combine OSIRIS data during the approach phase (from late April to early June 2014) with a large data set of ground-based images that were acquired with the ESO Very Large Telescope (VLT) from February to November 2014. Methods. A Monte Carlo dust tail code, which has already been used to characterise the dust environments of several comets and active asteroids, has been applied to retrieve the dust parameters. Key properties of the grains (density, velocity, and size distribution) were obtained from. Rosetta observations: these parameters were used as input of the code to considerably reduce the number of free parameters. In this way, the overall dust mass-loss rate and its dependence on the heliocentric distance could be obtained accurately. Results. The dust parameters derived from the inner coma measurements by OSIRIS and GIADA and from distant imaging using VLT data are consistent, except for the power index of the size-distribution function, which is alpha = -3, instead of alpha = -2, for grains smaller than 1 mm. This is possibly linked to the presence of fluffy aggregates in the coma. The onset of cometary activity occurs at approximately 4.3 AU, with a dust production rate of 0.5 kg/s, increasing up to 15 kg/s at 2.9 AU. This implies a dust-to-gas mass ratio varying between 3.8 and 6.5 for the best-fit model when combined with water-production rates from the MIRO experiment.

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This paper presents an empirical investigation of the appropriateness of distance as a determinant of international transport costs by using Philippine import data. This study addresses three specific questions. First, does distance really matter in the determination of transport costs? Second, if distance is a significant factor, what is the magnitude of its impact? Third, does the impact of distance on transport costs vary by commodity? Results indicate that while distance is important in determining transport costs, using distance alone as the proxy of international transport costs is insufficient, and such use underestimates the impact of distance on international transport costs. Results also indicate that the impact of distance varies across commodity groups, but it is difficult to precisely determine the direction and the magnitude of this impact.

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Geographic distance is a standard proxy for transport costs under the simple assumption that freight fees increase monotonically over space. Using the Japanese Census of Logistics, this paper examines the extent to which transport distance and time affect freight costs across shipping modes, commodity groups, and prefecture pairs. The results show substantial heterogeneity in transport costs and time across shipping modes. Consistent with an iceberg formulation of transport costs, distance has a significantly positive effect on freight costs by air transportation. However, I find the puzzling results that business enterprises are likely to pay more for short-distance shipments by truck, ship, and railroad transportation. As a plausible explanation, I discuss aggregation bias arising from freight-specific premiums for timely, frequent, and small-batch shipments.

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The need for the use of another surveillance system when radar cannot be used is the reason for the development of the Multilateration (MLT) Systems. However, there are many systems that operate in the L-Band (960-1215MHz) that could produce interference between systems. At airports, some interference has been detected between transmissions of MLT systems (1030MHz and 1090MHz) and Distance Measuring Equipment (DME) (960-1215MHz).

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Time series are proficiently converted into graphs via the horizontal visibility (HV) algorithm, which prompts interest in its capability for capturing the nature of different classes of series in a network context. We have recently shown [B. Luque et al., PLoS ONE 6, 9 (2011)] that dynamical systems can be studied from a novel perspective via the use of this method. Specifically, the period-doubling and band-splitting attractor cascades that characterize unimodal maps transform into families of graphs that turn out to be independent of map nonlinearity or other particulars. Here, we provide an in depth description of the HV treatment of the Feigenbaum scenario, together with analytical derivations that relate to the degree distributions, mean distances, clustering coefficients, etc., associated to the bifurcation cascades and their accumulation points. We describe how the resultant families of graphs can be framed into a renormalization group scheme in which fixed-point graphs reveal their scaling properties. These fixed points are then re-derived from an entropy optimization process defined for the graph sets, confirming a suggested connection between renormalization group and entropy optimization. Finally, we provide analytical and numerical results for the graph entropy and show that it emulates the Lyapunov exponent of the map independently of its sign.

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We propose a method to measure real-valued time series irreversibility which combines two different tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This method maps a time series to a directed network according to a geometric criterion. The degree of irreversibility of the series is then estimated by the Kullback-Leibler divergence (i.e. the distinguishability) between the in and out degree distributions of the associated graph. The method is computationally efficient and does not require any ad hoc symbolization process. We find that the method correctly distinguishes between reversible and irreversible stationary time series, including analytical and numerical studies of its performance for: (i) reversible stochastic processes (uncorrelated and Gaussian linearly correlated), (ii) irreversible stochastic processes (a discrete flashing ratchet in an asymmetric potential), (iii) reversible (conservative) and irreversible (dissipative) chaotic maps, and (iv) dissipative chaotic maps in the presence of noise. Two alternative graph functionals, the degree and the degree-degree distributions, can be used as the Kullback-Leibler divergence argument. The former is simpler and more intuitive and can be used as a benchmark, but in the case of an irreversible process with null net current, the degree-degree distribution has to be considered to identify the irreversible nature of the series