Magma genesis in a battered Moon: Effects of basin-forming impacts

Magma genesis in the Moon could have been significantly altered by large impacts if they melted solidified residual liquids and late cumulates from the ‘magma ocean’. Calculations of the heat required to melt these materials, under different assumed conditions, are compared to estimates of the total kinetic energy of the Imbrium impact. For a significant amount of these materials to have been melted, they must have been near their solidus temperatures, the impacts must have been very large, and the lunar lithosphere must have been locally heated at depths of 70 to 140 km. Unless the Imbrium impact released at least the maximum estimated kinetic energy, only larger impacts, e.g., the proposed ‘Gargantuan’ impact, could have augmented the intrinsic lunar heat budget enough to locally alter the abundance, timing of eruption, and chemical compositions of lunar magmas. The mechanical and thermal energy generated by such an impact could have been critical in creating (1) the higher concentrations of radioactive elements in the Imbrium/Procellarum area by migration of residual liquids driven by differential lithospheric thickness; and (2) hybrid mare basalts (representing varying proportions of late cumulates and/or residual liquids incorporated into primitive magmas rising from the partially molten lunar interior). Complete compositional spectra of lunar basalts are to be expected, from primitive mare basalts to pure KREEP and to Ti-rich varieties. Comparison of the Gargantuan/Imbrium area with ancient basins in the eastern nearside area suggests that the interplay between the Moon's internal heat engine and the timing of large impacts was a crucial factor in determining the time of tunar volcanism and the chemical composition of the lavas.     

Short-Term Ozone Forecasting with a Network Model System during Summer 1999

Within the framework of the Tropospheric Research Programme (TFS) four working groups in Germany (University of Stuttgart, University of Cologne, Research Center Karlsruhe, German Weather Service) formed a network developing a model system for chemistry transport calculations on different scales. The network was optimized, based on each module and combined for the different interfaces in order to perform daily preoperational ozone forecasts and its precursors at the German Weather Service in summer 1999 (May through September). The setup of the model system, the interfaces and changes of each module are described. The results of the whole preoperational episode are displayed and discussed. Main efforts were done analyzing the model climate statistics and the verification of the predictions with an extensive data base of observations at stations in Germany. The results of this extensive verification demonstrate the relatively good performance of the entire forecast system.     

Holocene paleoenvironmental change inferred from two sediment cores collected in the Tibetan lake Taro Co

Journal of Paleolimnology - The Tibetan Plateau, also known as the “Water Tower of Asia” because of its function as a water storage and supply region, responds dramatically to modern...     

Exploring the Functions of Different Forms of Trust in Collaborative Natural Resource Management

Successful natural resource management increasingly requires collaboration across boundaries and between diverse stakeholder groups, and trust is a key ingredient of successful collaboration. This study represents an early qualitative empirical attempt to understand how different forms of trust develop, function, and interact in collaborative natural resource management initiatives. We conducted case studies of four landscape-level initiatives in the Collaborative Forest Landscape Restoration Program (CFLRP). Our results suggest that three forms of trust, affinitive, rational, and procedural trust, were all important for successful collaboration, but different forms of trust appeared to function more powerfully during convening, recruitment, retention, and ongoing collaboration of stakeholders, with affinitive trust particularly important for convening, and rational and procedural trust gaining importance for recruiting and retention of members. We discuss the implications of the findings in both theoretical and practical terms.     

A geomorphologic kinematic‐wave (GKW) model for estimation of floods from small alpine watersheds

A geomorphologic kinematic‐wave (GKW) model was developed for simulation of extreme floods from small alpine catchments. The GKW model couples the kinematic‐wave theory and the geomorphologic representation of the catchment based on the Horton–Strahler ordering scheme. The model was tested on two small alpine catchments in Switzerland, and the agreement between simulated and observed floods was good. Care must however be taken with the computation of slope and roughness parameters. Copyright © 1999 John Wiley & Sons, Ltd.     

Numerical simulation and seismic performance evaluation of buried pipelines rehabilitated with cured‐in‐place‐pipe liner under seismic wave propagation

The cured‐in‐place‐pipe (CIPP) liner technology involves installation of flexible polymeric composite liners coated with thermosetting resin to the inner surfaces of existing buried pipelines. This innovative technology provides an efficient, economic, and environmentally friendly alternative for rehabilitation of structurally compromised underground pipelines without expensive and disruptive excavation. However, the lack of analytical/numerical procedures to quantify the seismic performance of CIPP liner reinforced pipelines remains a barrier to the seismic design and rehabilitation of underground pipelines. This paper first develops an experimentally validated hysteretic model of ductile iron push‐on joints, reinforced with one particular type of CIPP liner under repeated axial loading. A numerical procedure is then proposed to systematically assess the seismic performance and fragility of straight buried pipelines incorporating push‐on joints and subjected to transient ground deformations. The numerical results indicate that CIPP liner‐reinforced pipelines exhibit favorable robust seismic performance with limited joint damage under high‐intensity transient ground deformations. Copyright © 2016 John Wiley & Sons, Ltd.     

Identification of low frequency waves in the vicinity of the terrestrial bow shock

In this paper, methods for the determination of the wave mode for low frequency waves based on observed differences in phase are reviewed. Examples, using measurements made in the terrestrial foreshock and magnetosheath, are used to illustrate the application of these methods. The use of advance methods such as NARMAX modelling or genetic algorithms to identify the plasma wave mode is also discussed.     

The Nu Expression for Probabilistic Data Integration

The general problem of data integration is expressed as that of combining probability distributions conditioned to each individual datum or data event into a posterior probability for the unknown conditioned jointly to all data. Any such combination of information requires taking into account data interaction for the specific event being assessed. The nu expression provides an exact analytical representation of such a combination. This representation allows a clear and useful separation of the two components of any data integration algorithm: individual data information content and data interaction, the latter being different from data dependence. Any estimation workflow that fails to address data interaction is not only suboptimal, but may result in severe bias. The nu expression reduces the possibly very complex joint data interaction to a single multiplicative correction parameter ν ₀, difficult to evaluate but whose exact analytical expression is given; availability of such an expression provides avenues for its determination or approximation. The case ν ₀=1 is more comprehensive than data conditional independence; it delivers a preliminary robust approximation in presence of actual data interaction. An experiment where the exact results are known allows the results of the ν ₀=1 approximation to be checked against the traditional estimators based on assumption of data independence.     

Metrics for the comparative analysis of geospatial datasets with applications to high-resolution grid-based population data

Geospatial data sciences have emerged as critical requirements for high-priority application solutions in diverse areas, including, but not limited to, the mitigation of natural and man-made disasters. Three sets of metrics, adopted or customized from geo-statistics, applied meteorology and signal processing, are tested in terms of their ability to evaluate geospatial datasets, specifically two population databases commonly used for disaster preparedness and consequence management. The two high-resolution, grid-based population datasets are the following: The LandScan dataset available from the Geographic Information Science and Technology (GIST) group at the Oak Ridge National Laboratory (ORNL), and the Gridded Population of the World (GPW) dataset available from the Center for International Earth Science Information Network (CIESIN) group at Columbia University. Case studies evaluate population data across the globe, specifically, the metropolitan areas of Washington DC, USA, Los-Angeles, USA, and Houston, USA, and London, UK, as well as the country of Iran. The geospatial metrics confirm that the two population datasets have significant differences, especially in the context of their utility for disaster readiness and mitigation. While this paper primarily focuses on grid based population datasets and disaster management applications, the sets of metrics developed here can be generalized to other geospatial datasets and applications. Future research needs to develop metrics for geospatial and temporal risks and associated uncertainties in the context of disaster management. The U. S. Government’s right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.     

基于遗传算法的多光谱影像非监督训练分类系统

本文将遗传算法（GA）应用于非监督训练,提高了遥感数据的分类精度。遗传竞争学习算法（GA-CL）综合了遗传算法和简单的竞争学习算法,可用于改进非监督训练的结果。遗传算法在典型样本聚类的过程中可以避免得到局部最优值。Jeffries-Matusita（J-M）距离法是通过统计测量两个训练类别之间的分离度,可用于评价这种算法。将此算法应用于TM数据的结果显示,遗传算法改进了简单的竞争学习算法,与其他非监督训练算法相比,其提供了K-均值,GA-K-均值和简单的竞争学习算法。