Topodata: Brazilian full coverage refinement of SRTM data

This work presents the selection of a set of geostatistical coefficients suitable for a unified SRTM data refinement from 3″ to 1″ through kriging over the entire Brazilian territory. This selection aimed at data potential for geomorphometric derivations, given by the preservation of detailed geometric characteristics of the resulting digital elevation models (DEM), which are sensitive to refining procedures. The development contained a long-term experimentation stage, when data refinement through kriging was locally developed to support distinct regional projects, followed by a unified selection stage, where the acquired experience was applied to select a single and unified interpolation scheme. In this stage, the selected geostatistical models with promising performances were tested for unified refinement on 40 Brazilian areas with distinct geological settings. Tested areas encompass reliefs varying from mountainous to plain. The effects of data preparation were observed on the perception of patterns (texture and roughness), as well as of singularities (edges, peaks, thalwegs etc.). Results were evaluated mainly through the examination of shaded reliefs, transects and perspectives observed in different scales. Terrains with low slopes and small amplitudes had their DEM promptly affected by the refining methods, as opposed to mountainous terrains. The evaluation, unambiguously confirmed by all consulted interpreters, converged into a refining model with outstanding performance in all tested conditions.     

Inversion of time-dependent nuclear well-logging data using neural networks

The purpose of this work was to investigate a new and fast inversion methodology for the prediction of subsurface formation properties such as porosity, salinity and oil saturation, using time‐dependent nuclear well logging data. Although the ultimate aim is to apply the technique to real‐field data, an initial investigation as described in this paper, was first required; this has been carried out using simulation results from the time‐dependent radiation transport problem within a borehole. Simulated neutron and γ‐ray fluxes at two sodium iodide (NaI) detectors, one near and one far from a pulsed neutron source emitting at ～14 MeV, were used for the investigation. A total of 67 energy groups from the BUGLE96 cross section library together with 567 property combinations were employed for the original flux response generation, achieved by solving numerically the time‐dependent Boltzmann radiation transport equation in its even parity form. Material property combinations (scenarios) and their correspondent teaching outputs (flux response at detectors) are used to train the Artificial Neural Networks (ANNs) and test data is used to assess the accuracy of the ANNs. The trained networks are then used to produce a surrogate model of the expensive, in terms of computational time and resources, forward model with which a simple inversion method is applied to calculate material properties from the time evolution of flux responses at the two detectors. The inversion technique uses a fast surrogate model comprising 8026 artificial neural networks, which consist of an input layer with three input units (neurons) for porosity, salinity and oil saturation; and two hidden layers and one output neuron representing the scalar photon or neutron flux prediction at the detector. This is the first time this technique has been applied to invert pulsed neutron logging tool information and the results produced are very promising. The next step in the procedure is to apply the methodology to real data.     

Dynamical studies of cluster pairs in the Magellanic Clouds

We performed N -body simulations of star cluster encounters with Hernquist's TREECODE in a CRAY YMP-2E computer under different initial conditions (relative positions and velocities, cluster sizes, masses and concentration degrees). The total number of particles per simulation ranged from 1024 to 20480. These models are compared with a series of isodensity maps of cluster pairs in the Magellanic Clouds. Evidence is found that during the interactions, transient morphological effects such as an expanded halo, isophotal deformation and isophotal twisting can occur as a result of tidal effects and dynamical friction. The simulations also show that different outcomes are possible depending on the initial parameters: (i) long-standing changes of concentration degree can occur after the collision; (ii) one member can disaggregate; or (iii) the pair can coalesce into a single cluster with a distinct structure compared with the original ones. These simulations can reproduce a wide range of morphological structures in observed cluster pairs.     

A consistent derivation of the wave-energy equation from basic hydrodynamic principles

Based on a decomposition of the velocity into mean flow, turbulent and wave components, momentum and hereafter a wave-energy equation is derived. It contains a turbulent energy dissipation term which is closed by applying a wave-related mixing length model and linear wave theory solutions. This closure produces a non-linear turbulent wave-energy dissipation including the wave energy in a 5/2 power law. The theory is able to predict correctly the shape of deep-water wave spectra according to Phillips' similarity law.Responsible Editor: Hans Burchard     

居民地方感对区域旅游发展支持度影响——以九寨沟旅游核心社区为例

基于"地方感"、"期望理论"两个基本理论,从旅游核心社区居民地方感、旅游发展期望、旅游发展获益感知、旅游发展成本感知以及旅游发展支持度五个结构变量Ⅲ发,通过引入旅游发展期望值作为中介变量,构建居民地方感对旅游发展支持度内部影响机制的理论模型.以世界遗产地几寨沟为实证研究对象,通过验证性因子分析和三阶段结构方程模型的定量分析,校验理论模型中各结构因子、结构因子与其所含维度之间影响路径及其系数,定量测度了居民的旅游发展期望在居民地方感与旅游发展正反影响感知关联中的中介效用和影响机制,及对旅游发展支持度的潜在影响模式.研究结果表明:①居民地方感对居民旅游发展正反影响感知的作用存在差异,地方感对获益感知的作用远大于成本感知.②居民从旅游发展中感知获益有助于他们对当地旅游发展持更积极态度.而成本感知则会产生消极影响.③居民旅游发展期望中介效用的存在性和有效性,居民地方感通过发展期望,强化了对旅游发展影响感知及旅游支持度作用.④发展期望在居民旅游发展正反影响感知两结构模型中的中介效用存在强弱,在感知获益子结构模型的中介作用强于感知成本子模型.     

Dunes on Titan observed by Cassini Radar

Thousands of longitudinal dunes have recently been discovered by the Titan Radar Mapper on the surface of Titan. These are found mainly within ±30° of the equator in optically-, near-infrared-, and radar-dark regions, indicating a strong proportion of organics, and cover well over 5% of Titan's surface. Their longitudinal duneform, interactions with topography, and correlation with other aeolian forms indicate a single, dominant wind direction aligned with the dune axis plus lesser, off-axis or seasonally alternating winds. Global compilations of dune orientations reveal the mean wind direction is dominantly eastwards, with regional and local variations where winds are diverted around topographically high features, such as mountain blocks or broad landforms. Global winds may carry sediments from high latitude regions to equatorial regions, where relatively drier conditions prevail, and the particles are reworked into dunes, perhaps on timescales of thousands to tens of thousands of years. On Titan, adequate sediment supply, sufficient wind, and the absence of sediment carriage and trapping by fluids are the dominant factors in the presence of dunes.     

Groundwater flow regime under natural conditions as inferred from past evidence and contemporary field observations in a semi-arid basin: Cuenca de la Independencia, Guanajuato, México

This study was carried out in the Cuenca de la Independencia, a semi-arid basin in Central Mexico. The objective is to describe the main features of a groundwater flow regime under natural conditions, based on groundwater discharge manifestations. Information obtained from paleoecological, paleontological, archaeological and historical data suggests that, prior to heavy development (starting in the 1950s), the hydrogeologic regime was characterized by a larger groundwater availability in a more humid and colder climate. Manifestations associated to groundwater discharges are springs, lagoons, wetlands, saline soils, chalcedony deposits, phreatophytes, thermalism, and artesianism. The different types of manifestations and their position in the basin indicate the influence of groundwater flow systems hierarchically nested, forming concentric zones at ground level. The groundwater flow regime corresponds to a classical gravity-induced flow system with generation of local, intermediate and regional patterns. Integrating several types of data to establish the flow geometry and its dynamics has proven a useful tool to increase understanding of the original groundwater regimes. This approach can also be applied in other over-exploited semi-arid basins.     

On the use of logistic regression for stellar classification

We are totally immersed in the Big Data era and reliable algorithms and methods for data classification are instrumental for astronomical research. Random Forest and Support Vector Machines algorithms have become popular over the last few years and they are widely used for different stellar classification problems. In this article, we explore an alternative supervised classification method scarcely exploited in astronomy, Logistic Regression, that has been applied successfully in other scientific areas, particularly biostatistics. We have applied this method in order to derive membership probabilities for potential T Tauri star candidates from ultraviolet-infrared colour-colour diagrams.