The vorticity axis flip and its control on mineralization

This paper discusses the possible role of vorticity axis flip in controlling fluid flow and consequent development of hydrothermal deposits. Structural, kinematic and vorticity data from the vicinity of the Singhbhum Shear Zone (SSZ) are used to propose a two stage model to explain hydrothermal mineralization. It is suggested that in the initial stage, fractures, weak planes, foliations and/or shear zones develop. Fracture permeability is weak at this stage, as a consequence of which fluid pressure builds up. Variation in stress orientation during a later stage of deformation results in enhancement of fracture network, fracture permeability and its anisotropy. If a significant vorticity axis flip accompanies this variation in stress orientation, then it pumps the fluids into the fracture network, thus yielding hydrothermal mineral deposits. In the case of SSZ, the vorticity axis flip is envisaged to have taken place from steeply plunging (anticlockwise) during the early stage, to sub-horizontal during the late stage. The SSZ became a northerly dipping thrust at this late stage and the rotation around the sub-horizontal vorticity axis was such that the rocks comprising the northern block were thrust over southern block (Singhbhum granitoid). According to the author, this vorticity axis flip must have been critical in pumping up the fluids along the SSZ to form quartz veins that host mineral deposits.     

Well behaved class of charge analogue of Heintzmann’s relativistic exact solution

We present a well behaved class of Charge Analogue of Heintzmann (Z. Phys. 228:489, 1969) solution. This solution describes charge fluid balls with positively finite central pressure and positively finite central density ; their ratio is less than one and causality condition is obeyed at the centre. The outmarch of pressure, density, pressure-density ratio and the adiabatic speed of sound is monotonically decreasing, however, the electric intensity is monotonically increasing in nature. The solution gives us wide range of constant K (1.25≤K≤15) for which the solution is well behaved and therefore, suitable for modeling of super dense star. For this solution the mass of a star is maximized with all degrees of suitability and by assuming the surface density ρ _b =2×10¹⁴ g/cm³. Corresponding to K=1.25 and X=0.42, the maximum mass of the star comes out to be 3.64M _Θ with linear dimension 24.31 km and central redshift 1.5316.     

Explosive erosion during the Phoenix landing exposes subsurface water on Mars

While steady thruster jets caused only modest surface erosion during previous spacecraft landings on the Moon and Mars, the pulsed jets from the Phoenix spacecraft led to extensive alteration of its landing site on the martian arctic, exposed a large fraction of the subsurface water ice under the lander, and led to the discovery of evidence for liquid saline water on Mars. Here we report the discovery of the ‘explosive erosion’ process that led to this extensive erosion. We show that the impingement of supersonic pulsed jets fluidizes porous soils and forms cyclic shock waves which propagate through the soil and produce erosion rates more than an order of magnitude larger than that of other jet-induced processes. The understanding of ‘explosive erosion’ allows the calculation of bulk physical properties of the soils altered by it, provides insight into a new behavior of granular flow at extreme conditions and explains the rapid alteration of the Phoenix landing site’s ground morphology at the northern arctic plains of Mars.     

Does AMS data from micaceous quartzite provide information about shape of the strain ellipsoid?

Anisotropy of magnetic susceptibility (AMS) in micaceous quartzites with mean susceptibility (K _m) >50 × 10⁻⁶ SI units is known to be on account of the orientation distribution of the para/ferromagnetic minerals (e.g. micas, magnetite), which comprise the minor phase in the rocks. However, the strain in such deformed micaceous quartzites is dominantly accommodated by the quartz grains, which are the major phase in them. The objective of this paper is to explore the extent to which AMS data from micaceous quartzites provide information about the shape of the strain ellipsoid. AMS analysis of 3 quartzite blocks is performed, and the shape of the AMS ellipsoid is recorded to be oblate. From AMS data, the three principal planes of the AMS ellipsoid are identified in each block and thin sections are prepared along them. Quartz grain shape (aspect ratio, R _q), intensity of quartz and mica shape preferred orientation (κ_q and κ_mi, respectively) and 2D strain (E) recorded by quartz are measured in each section. R _q, κ_q, κ_mi and E are all noted to be minimum in the section parallel to the magnetic foliation plane as compared to the other two sections. This indicates that the quartz grains have oblate shapes in 3D and accommodated flattening strain, which is similar to the shape of the AMS ellipsoid. The role of mica in causing Zener drag and pinning of quartz grain boundaries is discussed. It is concluded that during progressive deformation, migration of pinned grain boundaries is inhibited. This causes enhanced recrystallization at the grain boundaries adjacent to the pinned ones, thus guiding the shape modification of quartz grains. A strong correlation is demonstrated between κ_q and κ_mi as well as κ_mi and E. It is inferred that fabric evolution of quartz was controlled by mica. Hence, the shape of the AMS ellipsoid, which is on account of mica, provides information about shape of the strain ellipsoid.     

Evaluation of machine learning tools as a statistical downscaling tool: temperatures projections for multi-stations for Thames River Basin, Canada

Many impact studies require climate change information at a finer resolution than that provided by global climate models (GCMs). This paper investigates the performances of existing state-of-the-art rule induction and tree algorithms, namely single conjunctive rule learner, decision table, M5 model tree, and REPTree, and explores the impact of climate change on maximum and minimum temperatures (i.e., predictands) of 14 meteorological stations in the Upper Thames River Basin, Ontario, Canada. The data used for evaluation were large-scale predictor variables, extracted from National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis dataset and the simulations from third generation Canadian coupled global climate model. Data for four grid points covering the study region were used for developing the downscaling model. M5 model tree algorithm was found to yield better performance among all other learning techniques explored in the present study. Hence, this technique was applied to project predictands generated from GCM using three scenarios (A1B, A2, and B1) for the periods (2046–2065 and 2081–2100). A simple multiplicative shift was used for correcting predictand values. The potential of the downscaling models in simulating predictands was evaluated, and downscaling results reveal that the proposed downscaling model can reproduce local daily predictands from large-scale weather variables. Trend of projected maximum and minimum temperatures was studied for historical as well as downscaled values using GCM and scenario uncertainty. There is likely an increasing trend for T _max and T _min for A1B, A2, and B1 scenarios while decreasing trend has been observed for B1 scenarios during 2081–2100.     

Seasonal disparity in the co-occurrence of arsenic and fluoride in the aquifers of the Brahmaputra flood plains,Northeast India

Arsenic (As) and fluoride (F^?) in groundwater are increasing global water quality and public health concerns. The present study provides a deeper understanding of the impact of seasonal change on the co-occurrence of As and F^?, as both contaminants vary with climatic patterns. Groundwater samples were collected in pre- and post-monsoon seasons (n = 40 in each season) from the Brahmaputra flood plains (BFP) in northeast India to study the effect of season on As and F^? levels. Weathering is a key hydrogeochemical process in the BFP and both silicate and carbonate weathering are enhanced in the post-monsoon season. The increase in carbonate weathering is linked to an elevation in pH during the post-monsoon season. A Piper diagram revealed that bicarbonate-type water, with Na⁺, K⁺, Ca²⁺, and Mg²⁺ cations, is common in both seasons. Correlation between Cl^? and NO₃ ^? (r = 0.74, p = 0.01) in the post-monsoon indicates mobilization of anthropogenic deposits during the rainy season. As was within the 10 µg L^?1 WHO limit for drinking water and F^? was under the 1.5 mg L^?1 limit. A negative correlation between oxidation reduction potential and groundwater As in both seasons (r = ?0.26 and ?0.49, respectively, for pre-monsoon and post-monsoon, p = 0.05) indicates enhanced As levels due to prevailing reducing conditions. Reductive hydrolysis of Fe (hydr)oxides appears to be the predominant process of As release, consistent with a positive correlation between As and Fe in both seasons (r = 0.75 and 0.73 for pre- and post-monsoon seasons, respectively, at p = 0.01). Principal component analysis and hierarchical cluster analysis revealed grouping of Fe and As in both seasons. F^? and sulfate were also clustered during the pre-monsoon season, which could be due to their similar interactions with Fe (hydr)oxides. Higher As levels in the post-monsoon appears driven by the influx of water into the aquifer, which drives out oxygen and creates a more reducing condition suitable for reductive dissolution of Fe (hydr)oxides. An increase in pH promotes desorption of As oxyanions AsO₄ ^3? (arsenate) and AsO₃ ^3? (arsenite) from Fe (hydr)oxide surfaces. Fluoride appears mainly released from F^?-bearing minerals, but Fe (hydr)oxides can be a secondary source of F^?, as suggested by the positive correlation between As and F^? in the pre-monsoon season.     

A comparative evaluation of groundwater suitability for irrigation and drinking purposes in two intensively cultivated districts of Punjab, India

Punjab is the most cultivated state in India with the highest consumption of fertilizers. Patiala and Muktsar districts are two agricultural dominated districts of Punjab located in extreme south-east and south-west of the state. This paper highlights temporal variations of the groundwater quality and compares its suitability for irrigation and drinking purpose in these two districts. Water samples were collected in March and September 2003, representing the pre-monsoon and post-monsoon seasons, respectively. Water samples were analysed for almost all major cations, anions, dissolved heavy metals and turbidity. Parameters like sodium adsorption ratio, % sodium, residual sodium carbonate, total hardness, potential salinity, Kelley’s ratio, magnesium ratio, index of base exchange and permeability index were calculated on the basis of chemical data. A questionnaire was also used to investigate perception of villagers on taste and odour. Comparison of the concentration of the chemical constituents with WHO (world health organization) drinking water standards of 2004 and various classifications show that present status of groundwater in Patiala is better for irrigation and drinking purposes except for a few locations with a caution that it may deteriorate in near future. In Muktsar, groundwater is not suitable for drinking. Higher total hardness (TH) and total dissolved solids at numerous places indicate the unsuitability of groundwater for drinking and irrigation. Results obtained in this forms baseline data for the utility of groundwater. In terms of monsoon impact, Patiala groundwater shows dilution and flushing but Muktsar samples show excessive leaching of different chemical components into the groundwater leading to the enrichment of different anions and cations indicating pollution from extraneous sources. No clear correlation between the quality parameters studied here and perceived quality in terms of satisfactory taste response were obtained at electrical conductivity values higher than the threshold minimum acceptable value.     

Copper Ore Identification using Spectral Similarity Measurement from Hyperion Image,Mapping of Porphyry Copper Mineralized Zone

This work illustrates the effectiveness of hyperspectal image spectroscopy and lab spectroscopy in identification techniques of minerals in alteration zone of ore body. The adopted procedure involves testing of Hyperion image spectra, their processing for noise, spectral matching and spectral similarity measurement with selected library spectra. Average weighted spectral similarity; visual and statistical matching techniques were used to select end-members from image spectra. Minimum noise fraction and pixel purity index technique were used to retrieve end-member spectra from hyperion image. Hyperspectral image like hyperion has the capability to deliver laboratory standard spectroscopic result. This paper illustrates the capability of hyperion image spectra in copper ore identification and mapping of chalcopyrite outcrop. A systematic approach has been made in this paper. This approach describes how image end member spectra and laboratory spectra can be co-related to fetch accurate spectral form of chalcopyrite ores. Thus, statistical and graphical comparison has been carried out between image derived end member spectra and laboratory spectra of chalcopyrite for better accuracy. The visual measurements is satisfactory, R = 0.973 for fine and 0.976 for medium grained chalcopyrite ore. Excellent statistical significance levels (90–97%) are found while comparing these spectra. There are many success stories of sub-pixel and N-dimensional feature space methods to separate the hydrothermal alteration zones from iron oxide mixed ore bodies. Thus, unmixing methods are very useful for mapping of most dominating mineral parts of a pixel from hyperspectral images which have coarse spatial resolution. Finally, mapping of mineralized zone has been achieved through sub-pixel based classifiers like spectral angle mapper (SAM), constrained energy minimization (CEM) and adaptive coherence estimator (ACE) techniques.