Subduction,fluids, and accessory minerals: a celebration of the career of Sorena S. Sorensen

ABSTRACT

This is a preface to the topical issue entitled ‘Subduction, Fluids, and Accessory Minerals: A Celebration of the Career of Sorena S. Sorensen’     

SphinX: The Solar Photometer in X-Rays

Solar Photometer in X-rays (SphinX) was a spectrophotometer developed to observe the Sun in soft X-rays. The instrument observed in the energy range ≈?1?–?15 keV with resolution ≈?0.4 keV. SphinX was flown on the Russian CORONAS–PHOTON satellite placed inside the TESIS EUV and X telescope assembly. The spacecraft launch took place on 30 January 2009 at 13:30 UT at the Plesetsk Cosmodrome in Russia. The SphinX experiment mission began a couple of weeks later on 20 February 2009 when the first telemetry dumps were received. The mission ended nine months later on 29 November 2009 when data transmission was terminated. SphinX provided an excellent set of observations during very low solar activity. This was indeed the period in which solar activity dropped to the lowest level observed in X-rays ever. The SphinX instrument design, construction, and operation principle are described. Information on SphinX data repositories, dissemination methods, format, and calibration is given together with general recommendations for data users. Scientific research areas in which SphinX data find application are reviewed.     

Petrology of garnet-, spinel-, and sillimanite-bearing granites from the bavarian forest,West Germany

Mineralogy and Petrology - Samples from 17 small granitic intrusions of late-Variscan age have been investigated for their chemical compositions and petrographic characteristics. All of them...     

An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States

Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.