Peraluminous sapphirine-cordierite pods in Mg-rich orthopyroxene granulite from southern India: Implications for lower crustal processes

Sapphirine-cordierite intergrowths occur as pods within garnet-absent, high-Mg orthopyroxene-granulite xenoliths in the Kambam valley, Madurai Block, southern India. Whereas the cores of the pods are composed of sapphirine (X-Mg = 0.871-0.897) - cordierite (X-Mg = 0.892-0.931) intergrowth along with rutile, zircon and monazite, the rims are characterized by cordierite, apatite, plagioclase, K-feldspar, quartz and minor calcite. The surrounding matrix comprises orthopyroxene (maximum Al2O3 4.1 wt.%, X-Mg 0.848-0.850), plagioclase, biotite and quartz, similar to the assemblage in the surrounding charnockites. Sapphirine in the Kambam rocks is characterized by high Al contents with an end-member composition in the range of 7:9:3 and 3:5:1. The occurrence of peraluminous sapphirine in association with cordierite and in the absence of phases such as sillimanite and garnet is distinct from ultrahigh-temperature assemblages in other localities within the Madurai Block. The peraluminous composition of the pods suggests that these domains could represent cryptic pathways through which aluminous melts migrated. The reaction of such peraluminous melts with Mg-rich orthopyroxene in the host granulite at temperatures of 1025 degrees C and pressures around 8 kbar as computed from phase equilibria modeling followed by an isobaric cooling is inferred to have generated the sapphirine-cordierite pods. The unusual high-Mg orthopyroxene granulite suggests interaction of supracrustal rocks with mafic magmas, which probably acted as the heat source for the partial melting of lower crust and UHT metamorphism.

Lead Retention by Soils at Field Moisture Contents

The majority of studies pertaining to lead retention by clays and soils have examined the mechanisms, kinetics, and adsorption isotherms using the batch experiment technique that employs solid: water extracts of 1:10 and 1:20. Field soil deposits generally have much lower gravimetric water content ranging between 9 and 45%. Given the wide disparity in the solids: water ratio employed in the batch experiment technique and that prevailing in field deposits, this paper examines the lead retention characteristics of soils at field moisture contents (6%, 13%, and 25%) using artificially lead-contaminated soil specimens. A residually derived (i.e., formed by in-situ weathering of parent rock) red soil was used to prepare the artificially contaminated soil specimens. The impact of variations in clay content on lead retention was examined by diluting the residual soil with various amounts (0 to 60%) of river sand. Soil specimens remolded at 6 and 13% moisture contents produced very stiff to hard soils on compaction, while specimens remolded at 25% moisture content existed in the slurry state. The soil specimens were contaminated with low (30mg/kg) to high (2500mg/kg) concentrations of lead ions by remolding them with 160ppm to 10,000ppm ionic lead solutions. Lead retention by soils at field moisture contents was determined by extracting the lead from the soil using a water leach test. Experimental results showed that the bulk (71 to 99%) of the added lead was retained by the soil in insoluble form at the field moisture content. Correlations between the amount of lead retained and soil/solution parameters indicated that the amounts of Pb retained at field moisture content is a function of the initial Pb addition, total sand content, effective clay porosity, and soil pH.

Scalable multi-dimensional user intent identification using tree structured distributions

The problem of identifying user intent has received considerable attention in recent years, particularly in the context of improving the search experience via query contextualization. Intent can be characterized by multiple dimensions, which are often not observed from query words alone. Accurate identification of Intent from query words remains a challenging problem primarily because it is extremely difficult to discover these dimensions. The problem is often significantly compounded due to lack of representative training sample. We present a generic, extensible framework for learning the multi-dimensional representation of user intent from the query words. The approach models the latent relationships between facets using tree structured distribution which leads to an efficient and convergent algorithm, FastQ, for identifying the multi-faceted intent of users based on just the query words. We also incorporated WordNet to extend the system capabilities to queries which contain words that do not appear in the training data. Empirical results show that FastQ yields accurate identification of intent when compared to a gold standard.

A constellation power allocation scheme for two-user Gaussian MAC

Constellation Constrained (CC) capacity regions of two-user Gaussian Multiple Access Channels (GMAC) have been recently reported, wherein introducing appropriate rotation between the constellations of the two users is shown to maximally enlarge the CC capacity region. Such a Non-Orthogonal Multiple Access (NO-MA) method of enlarging the CC capacity region is referred to as Constellation Rotation (CR) scheme. In this paper, we propose a novel NO-MA technique called Constellation Power Allocation (CPA) scheme to enlarge the CC capacity region of two-user GMAC. We show that the CPA scheme offers CC sum capacities equal (at low SNR values) or close (at high SNR values) to those offered by the CR scheme with reduced ML decoding complexity for some QAM constellations. For the CR scheme, code pairs approaching the CC sum capacity are known only for the class of PSK and PAM constellations but not for QAM constellations. In this paper, we design code pairs with the CPA scheme to approach the CC sum capacity for 16-QAM constellations. Further, the CPA scheme used for two-user GMAC with random phase offsets is shown to provide larger CC sum capacities at high SNR values compared to the CR scheme.

Capacity region of K-user discrete memoryless interference channels with a mixed strong-very strong interference

The capacity region of the 3-user Gaussian Interference Channel (GIC) with mixed strong-very strong interference was established in [1]. The mixed strong-very strong interference conditions considered in [1] correspond to the case where, at each receiver, one of the interfering signals is strong and the other is very strong. In this paper, we derive the capacity region of K-user (K ≥ 3) Discrete Memoryless Interference Channels (DMICs) with a mixed strong-very strong interference. This corresponds to the case where, at each receiver one of the interfering signals is strong and the other (K - 2) interfering signals are very strong. This includes, as a special case, the 3-user DMIC with mixed strong-very strong interference. The proof is specialized to the 3-user GIC case and hence an alternative derivation for the capacity region of the 3-user GIC with mixed strong-very strong interference is provided.

On the generalized degrees of freedom of the K-user symmetric MIMO Gaussian interference channel

This work derives inner and outer bounds on the generalized degrees of freedom (GDOF) of the K-user symmetric MIMO Gaussian interference channel. For the inner bound, an achievable GDOF is derived by employing a combination of treating interference as noise, zero-forcing at the receivers, interference alignment (IA), and extending the Han-Kobayashi (HK) scheme to K users, depending on the number of antennas and the INR/SNR level. An outer bound on the GDOF is derived, using a combination of the notion of cooperation and providing side information to the receivers. Several interesting conclusions are drawn from the bounds. For example, in terms of the achievable GDOF in the weak interference regime, when the number of transmit antennas (M) is equal to the number of receive antennas (N), treating interference as noise performs the same as the HK scheme and is GDOF optimal. For K >; N/M+1, a combination of the HK and IA schemes performs the best among the schemes considered. However, for N/M <; K ≤ N/M+1, the HK scheme is found to be GDOF optimal.

A channel-aware, fast sub-channel to user assignment algorithm in OFDMA systems

Channel-aware assignment of sub-channels to users in the downlink of an OFDMA system demands extensive feedback of channel state information (CSI) to the base station. Since the feedback bandwidth is often very scarce, schemes that limit feedback are necessary. We develop a novel, low feedback splitting-based algorithm for assigning each sub-channel to its best user, i.e., the user with the highest gain for that sub-channel among all users. The key idea behind the algorithm is that, at any time, each user contends for the sub-channel on which it has the largest channel gain among the unallocated sub-channels. Unlike other existing schemes, the algorithm explicitly handles multiple access control aspects associated with the feedback of CSI. A tractable asymptotic analysis of a system with a large number of users helps design the algorithm. It yields 50% to 65% throughput gains compared to an asymptotically optimal one-bit feedback scheme, when the number of users is as small as 10 or as large as 1000. The algorithm is fast and distributed, and scales with the number of users.

MAST: multi-script annotation toolkit for scenic text

This paper describes a semi-automatic tool for annotation of multi-script text from natural scene images. To our knowledge, this is the maiden tool that deals with multi-script text or arbitrary orientation. The procedure involves manual seed selection followed by a region growing process to segment each word present in the image. The threshold for region growing can be varied by the user so as to ensure pixel-accurate character segmentation. The text present in the image is tagged word-by-word. A virtual keyboard interface has also been designed for entering the ground truth in ten Indic scripts, besides English. The keyboard interface can easily be generated for any script, thereby expanding the scope of the toolkit. Optionally, each segmented word can further be labeled into its constituent characters/symbols. Polygonal masks are used to split or merge the segmented words into valid characters/symbols. The ground truth is represented by a pixel-level segmented image and a '.txt' file that contains information about the number of words in the image, word bounding boxes, script and ground truth Unicode. The toolkit, developed using MATLAB, can be used to generate ground truth and annotation for any generic document image. Thus, it is useful for researchers in the document image processing community for evaluating the performance of document analysis and recognition techniques. The multi-script annotation toolokit (MAST) is available for free download.

A Novel Power Allocation Scheme for Two-User GMAC with Finite Input Constellations

Constellation Constrained (CC) capacity regions of two-user Gaussian Multiple Access Channels (GMAC) have been recently reported, wherein an appropriate angle of rotation between the constellations of the two users is shown to enlarge the CC capacity region. We refer to such a scheme as the Constellation Rotation (CR) scheme. In this paper, we propose a novel scheme called the Constellation Power Allocation (CPA) scheme, wherein the instantaneous transmit power of the two users are varied by maintaining their average power constraints. We show that the CPA scheme offers CC sum capacities equal (at low SNR values) or close (at high SNR values) to those offered by the CR scheme with reduced decoding complexity for QAM constellations. We study the robustness of the CPA scheme for random phase offsets in the channel and unequal average power constraints for the two users. With random phase offsets in the channel, we show that the CC sum capacity offered by the CPA scheme is more than the CR scheme at high SNR values. With unequal average power constraints, we show that the CPA scheme provides maximum gain when the power levels are close, and the advantage diminishes with the increase in the power difference.

Chromite-silicate chemistry of the Neoarchean Sittampundi Complex, southern India: Implications for subduction-related arc magmatism

The Neoarchean layered anorthositic complex at Sittampundi in southern India is known for its chromitite layers that are mostly associated with anorthosite (An(90-100)). The chromitites contain FeAl-rich chromites concentrated in layers between amphibole-rich layers with a dominant mineralogy of amphibole-spinel-plagiocase+/-sapphirine. The chromite-rich layers contain only amphibole and plagioclase. Mineral compositions illustrated by X-ray composition maps and profiles show subtle chemical differences. The chrome spinels are of refractory grade with Cr2O3 and Al2O3 contents varying between 34-40 wt.% and 23-28 wt.%. The chromite compositions are noticeably different from those in layered igneous intrusions of the Bushveld-Stillwater type. The existence of original highly calcic plagioclase, FeAl-rich chromite, and magmatic amphibole is consistent with derivation from a parental magma of hydrous tholeiitic composition that was most likely generated in a supra-subduction zone arc setting. In terms of mineralogy and field relations, the Sittampundi chromitites are remarkably similar to anorthosite-hosted chromitites in the Neoarchean Fiskensset anorthositic complex, Greenland. We propose that the Sittampundi chromitites formed by partial melting of unusually aluminous harzburgite in a hydrated mantle wedge above a subduction zone. This melting process produced hydrous, aluminous basalt, which fractionated at depth to give rise to a variety of high-alumina basalt compositions from which the anorthositic complex with its cumulate chromite-rich and amphibole-rich layers formed within the magma chamber of a supra-subduction zone arc. (C) 2011 Elsevier B.V. All rights reserved.

Adaptive constellation rotation scheme for two-user fading MAC with quantized fade state feedback

With no Channel State Information (CSI) at the users, transmission over the two-user Gaussian Multiple Access Channel with fading and finite constellation at the input, will have high error rates due to multiple access interference (MAI). However, perfect CSI at the users is an unrealistic assumption in the wireless scenario, as it would involve extremely large feedback overheads. In this paper we propose a scheme which removes the adverse effect of MAI using only quantized knowledge of fade state at the transmitters such that the associated overhead is nominal. One of the users rotates its constellation relative to the other without varying the transmit power to adapt to the existing channel conditions, in order to meet certain predetermined minimum Euclidean distance requirement in the equivalent constellation at the destination. The optimal rotation scheme is described for the case when both the users use symmetric M-PSK constellations at the input, where M = 2(gimel), gimel being a positive integer. The strategy is illustrated by considering the example where both the users use QPSK signal sets at the input. The case when the users use PSK constellations of different sizes is also considered. It is shown that the proposed scheme has considerable better error performance compared to the conventional non-adaptive scheme, at the cost of a feedback overhead of just log log(2) (M-2/8 - M/4 + 2)] + 1 bits, for the M-PSK case.

Efficient classification using phrases generated by topic models

There are many popular models available for classification of documents like Naïve Bayes Classifier, k-Nearest Neighbors and Support Vector Machine. In all these cases, the representation is based on the “Bag of words” model. This model doesn't capture the actual semantic meaning of a word in a particular document. Semantics are better captured by proximity of words and their occurrence in the document. We propose a new “Bag of Phrases” model to capture this discriminative power of phrases for text classification. We present a novel algorithm to extract phrases from the corpus using the well known topic model, Latent Dirichlet Allocation(LDA), and to integrate them in vector space model for classification. Experiments show a better performance of classifiers with the new Bag of Phrases model against related representation models.

Physical Layer Network Coding for the K-User Multiple Access Relay Channel

We propose a Physical layer Network Coding (PNC) scheme for the K-user wireless Multiple Access Relay Channel, in which K source nodes want to transmit messages to a destination node D with the help of a relay node R. The proposed scheme involves (i) Phase 1 during which the source nodes alone transmit and (ii) Phase 2 during which the source nodes and the relay node transmit. At the end of Phase 1, the relay node decodes the messages of the source nodes and during Phase 2 transmits a many-to-one function of the decoded messages. To counter the error propagation from the relay node, we propose a novel decoder which takes into account the possibility of error events at R. It is shown that if certain parameters are chosen properly and if the network coding map used at R forms a Latin Hypercube, the proposed decoder offers the maximum diversity order of two. Also, it is shown that for a proper choice of the parameters, the proposed decoder admits fast decoding, with the same decoding complexity order as that of the reference scheme based on Complex Field Network Coding (CFNC). Simulation results indicate that the proposed PNC scheme offers a large gain over the CFNC scheme.

An automated approach to network features of protein structure ensembles

Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of 2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.

Near infrared detectors based on HgSe and HgCdSe quantum dots generated at the liquid-liquid interface

HgSe and Hg0.5Cd0.5Se quantum dos (QDs) are synthesized at room temperature by a novel liquid-liquid interface method and their photodetection properties in the near-IR region are investigated. The photodetection properties of our Te-free systems are found to be comparable to those of the previously reported high performance QD vis-IR detectors including HgTe. The present synthesis indicates the cost-effectiveness of selenium based IR detectors owing to the abundance and lower toxicity of selenium compared to tellurium.