Sedimentation on the Ionian active margin (Hellenic arc) — Provenance of sediments and mechanisms of deposition

Lithological, sedimentological, mineralogical and faunal analyses of twenty cores from the western Peloponnesus margin and adjacent Matapan Trench permit the origin of the sediments and the processes of sedimentation to be defined in some detail.Except for the ash layers derived from the Ischian Province, the major part of the sediment is local in origin (Peloponnesus). Analyses of heavy, light and clay minerals enable three main provinces to be distinguished. Each of these provinces includes one or more slope basins and a portion of trench, without lateral connection between them and mixing of inputs.The diversity and complexity of sedimentary structures, the granulometric characters, the mixed fauna (molluscs and ostracods) and the variability of rates of sedimentation all testify to the prevalence of reworking phenomena and gravitative processes.These data confirm and elaborate on the model of sedimentation deduced from seismic studies in which sediments are successively trapped, released by the slope basins and transferred via channels and canyons towards the underlying trench basins. This “cascade feeding” appears characteristics of this subductive sedimentary environment.     

Analytical queries on semantic trajectories using graph databases

This article studies the analysis of moving object data collected by location‐aware devices, such as GPS, using graph databases. Such raw trajectories can be transformed into so‐called semantic trajectories, which are sequences of stops that occur at “places of interest.” Trajectory data analysis can be enriched if spatial and non‐spatial contextual data associated with the moving objects are taken into account, and aggregation of trajectory data can reveal hidden patterns within such data. When trajectory data are stored in relational databases, there is an “impedance mismatch” between the representation and storage models. Graphs in which the nodes and edges are annotated with properties are gaining increasing interest to model a variety of networks. Therefore, this article proposes the use of graph databases (Neo4j in this case) to represent and store trajectory data, which can thus be analyzed at different aggregation levels using graph query languages (Cypher, for Neo4j). Through a real‐world public data case study, the article shows that trajectory queries are expressed more naturally on the graph‐based representation than over the relational alternative, and perform better in many typical cases.     

Thermodynamic controls on element partitioning between titanomagnetite and andesitic–dacitic silicate melts

Titanomagnetite–melt partitioning of Mg, Mn, Al, Ti, Sc, V, Co, Ni, Cu, Zn, Ga, Zr, Nb, Mo, Hf and Ta was investigated experimentally as a function of oxygen fugacity (fO₂) and temperature (T) in an andesitic–dacitic bulk-chemical compositional range. In these bulk systems, at constant T, there are strong increases in the titanomagnetite–melt partitioning of the divalent cations (Mg²⁺, Mn²⁺, Co²⁺, Ni²⁺, Zn²⁺) and Cu²⁺/Cu⁺ with increasing fO₂ between 0.2 and 3.7 log units above the fayalite–magnetite–quartz buffer. This is attributed to a coupling between magnetite crystallisation and melt composition. Although melt structure has been invoked to explain the patterns of mineral–melt partitioning of divalent cations, a more rigorous justification of magnetite–melt partitioning can be derived from thermodynamic principles, which accounts for much of the supposed influence ascribed to melt structure. The presence of magnetite-rich spinel in equilibrium with melt over a range of fO₂ implies a reciprocal relationship between a(Fe²⁺O) and a(Fe³⁺O_1.5) in the melt. We show that this relationship accounts for the observed dependence of titanomagnetite–melt partitioning of divalent cations with fO₂ in magnetite-rich spinel. As a result of this, titanomagnetite–melt partitioning of divalent cations is indirectly sensitive to changes in fO₂ in silicic, but less so in mafic bulk systems.     

Distribution of Indus born mica along Gulf of Kachchh coast: Implications in understanding current dynamics

Indus is one of the major sources of sediments to the Gulf of Kachchh. Yet only its <63 micron fraction is studied in detail with regards to the offshore current dynamics. Hence here we present our study on characteristic signature of the Indus sediment load (i.e. mica minerals) in >63 micron size fraction along the coast of Gulf of Kachchh. The spatial distribution of mica minerals along the Gulf of Kachchh coast was studied which showed in general decreasing trend as we move along the northern and southern coast of the Gulf of Kachchh but, an increase in amount near the southern mouth at Okha. The study shows that the earlier proposed tidal barrier is ineffective in restricting movement of mica across the mouth of the gulf due to its characteristic transport mechanism. Also the presence of mudflats along the gulf of Kachchh coast plays a vital role as sediment receptors in the active sediment transport processes and mica minerals prove to be a promising simple tracer in studying the Indus born sediments in the region.     

Chemical composition of Russian Arctic precipitation in 2007-2015

The results of observations of the chemical composition of precipitation in the Russian Arctic in 2007-2015 are summarized including the data from NP-35 drifting ice station obtained in 2007-2008 in the framework of the joint program of Arctic and Antarctic Research Institute and Voeikov Main Geophysical Observatory. The qualitative and quantitative difference in the chemical composition of precipitation in the Atlantic, Siberian, and Pacific sectors of the Russian Arctic is revealed. It is found that the concentration of microelements (heavy metals) in precipitation at NP-35 ice station did not exceed 12% of total ions at the lowest mineralization. The comparative analysis is presented of the concentration of sulfate ions in precipitation in Norilsk and at NP-35 ice stations.     

Observations of rapid mean flow produced in mercury by a moving heater

Abstract

Experimental and theoretical results are described for the moving flame experiment, where a heat source moves under a horizontal, annular channel filled with liquid mercury. The physical range under discussion consists of the creep flow limit, in which inertial forces are less than viscous forces. A mean surface flow was observed on the mercury. This flow was up to four times greater than the heater speed, and in an opposite direction. The ratio of mean flow to heater speed was theoretically and experimentally found to be proportional to the square of the thermal amplitude, in agreement with a special limit of Davey's earlier results. The basic flow here, as contrasted to those flows analyzed by earlier theories, appears to be generated by surface tension. However, the Reynolds stress mechanism which generates the mean flow is the same. Some experimental flows were so rapid that the range of validity of the present, as well as some earlier theories, was exceeded. The present theory suggests that the higher order nonlinearities may have cancellative effects, which implies that the present and some earlier theories are valid beyond their normal range of validity.     

Local hydraulic gradient estimator analysis of long-term monitoring networks

Three measurements of head at unique locations form a three-point estimator of the local magnitude and orientation of the hydraulic gradient. The relative head measurement error (RHME) is defined here as the measurement error normalized by the head drop across the three-point estimator. Monte Carlo simulation results show that estimators with base to height ratios between 0.5 and 5.0 and that are large enough to keep the RHME below 0.05 create the most accurate gradient estimates and provide criteria for identifying good estimators. These criteria are applied to an example ground water monitoring network design problem in the Culebra dolomite near the Waste Isolation Pilot Plant repository to both analyze temporal changes and modify and expand the current monitoring network. Limiting the three-point estimators to those that meet the shape and RHME criteria reduces the number of possible estimators by >50% and leads to approximately 1 order of magnitude decrease in the average estimated magnitude of the gradient relative to using all estimators. Application of these criteria also reduces the variability in estimated gradient magnitude and orientation between the two time periods of measurements. Redundant wells in the network are identified by removing each existing well in turn and determining which removals yield the smallest decrease in the number of acceptable estimators. Optimal new well locations are identified by mapping the increase in total number of acceptable estimators for a single new well placed in the study domain.     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.     

Mineralogical, chemical, and crystallographic properties of supergene jarosite-group minerals from the Xitieshan Pb-Zn sulfide deposit, northern Tibetan Plateau, China

Supergene jarosite-group minerals are widespread in weathering profiles overlying Pb-Zn sulfide ores at Xitieshan, northern Tibetan Plateau, China. They consist predominantly of K-deficient natrojarosite, with lesser amounts of K-rich natrojarosite and plumbojarosite. Electron microprobe (EMP) analyses, scanning electron microcopy (SEM) investigation, and X-ray mapping reveal that the jarosite-group minerals are characterized by spectacular oscillatory zoning composed of alternating growth bands of K-deficient and K-bearing natrojarosite (K₂O >1 wt.%). Plumbojarosite, whenever present, occurs as an overgrowth in the outermost bands, and its composition can be best represented by K_0.29Na_0.19Pb_0.31Fe_2.66Al_0.22(SO₄)_1.65(PO₄)_0.31(AsO₄)_0.04(OH)_7.37. The substitution of monovalent for divalent cations at the A site of plumbojarosite is charge balanced by the substitution of five-valent for six-valent anions in XO₄ at the X site. Thermogravimetric analysis (TGA) of representative samples reveal mass losses of 11.46 wt.% at 446.6 °C and 21.42 wt.% at 683.4 °C due to dehydroxylation and desulfidation, respectively. TGA data also indicate that the natrojarosite structure collapses at 446.6 °C, resulting in the formation of NaFe(SO₄)₂ and minor hematite. The decomposition products of NaFe(SO₄)₂ are hematite and Na₂SO₄. Powder X-ray diffraction (XRD) analyses show that the jarosite-group minerals have mean unit-cell parameters of a?=?7.315 Å and c?=?016.598 Å. XRD and EMP data support the view that substitutions of Na for K in the A site and full Fe occupancy in the B site can considerably decrease the unit-cell parameter c, but only slightly increase a. The results from this study suggest that the observed oscillatory zoning of jarosite-group minerals at Xitieshan resulted mainly from substitutions of K for Na at the A site and P for S at the X site.     

Non-Linear Theory and Power-Law Models for Information Integration and Mineral Resources Quantitative Assessments

Singular physical or chemical processes may result in anomalous amounts of energy release or mass accumulation that, generally, are confined to narrow intervals in space or time. Singularity is a property of different types of non-linear natural processes including cloud formation, rainfall, hurricanes, flooding, landslides, earthquakes, wildfires, and mineralization. The end products of these non-linear processes can be modeled as fractals or multifractals. Hydrothermal processes in the Earth’s crust can result in ore deposits characterized by high concentrations of metals with fractal or multifractal properties. Here we show that the non-linear properties of the end products of singular mineralization processes can be applied for prediction of undiscovered mineral deposits and for quantitative mineral resource assessment, whether for mineral exploration or for regional, national and global planning for mineral resource utilization. In addition to the general theory and framework for the non-linear mineral resources assessment, this paper focuses on several power-law models proposed for characterizing non-linear properties of mineralization and for geoinformation extraction and integration. The theories, methods, and computer system discussed in this paper were validated using a case study dealing with hydrothermal Au mineral potential in southern Nova Scotia, Canada.