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.

Rendezvous of Multiple UAVs with Collision Avoidance Using Consensus

This paper addresses the problem of multiple unmanned aerial vehicle (UAV) rendezvous when the UAVs have to perform maneuvers to avoid collisions with other UAVs. The proposed solution consists of using velocity control and a wandering maneuver, if needed, of the UAVs based on a consensus among them on the estimated time of arrival at the point of the rendezvous. This algorithm, with a slight modification is shown to be useful in tracking stationary or slowly moving targets with a standoff distance. The proposed algorithm is simple and computationally efficient. The simulation results demonstrate the efficacy of the proposed approach. DOI: 10.1061/(ASCE)AS.1943-5525.0000145. (C) 2012 American Society of Civil Engineers.

Non-Stationary Semi-Markov Decision Processes on a Finite Horizon

We introduce and study a class of non-stationary semi-Markov decision processes on a finite horizon. By constructing an equivalent Markov decision process, we establish the existence of a piecewise open loop relaxed control which is optimal for the finite horizon problem.

Fracture processes of self compacting Concrete using image analysis

The mode I fracture toughness of concrete can be experimentally determined using three point bend beam in conjunction with digital image correlation (DIC). Three different geometrically similar sizes of beams are cast for this study. To study the influence of fly ash and silica fume on fracture toughness of SCC, three SCC mixes are prepared with and without mineral additions. The scanning electron microscope (SEM) images are taken on the fractured surface to add information on fracture process in SCC. From this study, it is concluded that the fracture toughness of SCC with mineral addition is higher when compared to those without mineral addition.

A novel Q-learning algorithm with function approximation for constrained Markov decision processes

We present a novel multi-timescale Q-learning algorithm for average cost control in a Markov decision process subject to multiple inequality constraints. We formulate a relaxed version of this problem through the Lagrange multiplier method. Our algorithm is different from Q-learning in that it updates two parameters - a Q-value parameter and a policy parameter. The Q-value parameter is updated on a slower time scale as compared to the policy parameter. Whereas Q-learning with function approximation can diverge in some cases, our algorithm is seen to be convergent as a result of the aforementioned timescale separation. We show the results of experiments on a problem of constrained routing in a multistage queueing network. Our algorithm is seen to exhibit good performance and the various inequality constraints are seen to be satisfied upon convergence of the algorithm.

Some implications of lepton flavor violating processes in a supersymmetric Type II seesaw model at TeV scale

We have conceived a supersymmetric Type II seesaw model at TeV scale, which has some additional particles consisting of scalar and fermionic triplet Higgs states, whose masses are around a few hundred GeV. In this particular model, we have studied constraints on the masses of triplet states arising from the lepton flavor violating (LFV) processes, such as mu -> 3e and mu -> e gamma. We have analyzed the implications of these constraints on other observable quantities such as the muon anomalous magnetic moment and the decay patterns of scalar triplet Higgses. Scalar triplet Higgs states can decay into leptons and into supersymmetric fields. We have found that the constraints from LFV can affect these various decay modes.

Flow cytometry analysis of human fetal osteoblast fate processes on spark plasma sintered hydroxyapatite-titanium biocomposites

Hydroxyapatite (HA)-based biocomposites have been widely investigated for a multitude of applications and these studies have been largely driven to improve mechanical properties (toughness and strength) without compromising cytocompatibility properties. Apart from routine cell viability/proliferation analysis, limited efforts have been made to quantify the fate processes (cell proliferation, cell cycle, and cell apoptosis) of human fetal osteoblast (hFOB) cells on HA-based composites, in vitro. In this work, the osteoblast cell fate process has been studied on a model hydroxyapatite-titanium (HA-Ti) system using the flow cytometry. In order to retain both HA and Ti, the novel processing technique, that is, spark plasma sintering, was suitably adopted. The cell fate processes of hFOBs, as evaluated using a flow cytometry, revealed statistically insignificant differences among HA-10 wt % Ti and HA and control (tissue culture polystyrene surface) in terms of osteoblast apoptosis, proliferation index as well as division index. For the first time, we provide quantified flow cytometry results to demonstrate that 10 wt % Ti additions to HA do not have any significant influence on the fate processes of human osteoblast-like cells, in vitro.

Validation based sparse Gaussian processes for ordinal regression

This paper proposes a sparse modeling approach to solve ordinal regression problems using Gaussian processes (GP). Designing a sparse GP model is important from training time and inference time viewpoints. We first propose a variant of the Gaussian process ordinal regression (GPOR) approach, leave-one-out GPOR (LOO-GPOR). It performs model selection using the leave-one-out cross-validation (LOO-CV) technique. We then provide an approach to design a sparse model for GPOR. The sparse GPOR model reduces computational time and storage requirements. Further, it provides faster inference. We compare the proposed approaches with the state-of-the-art GPOR approach on some benchmark data sets. Experimental results show that the proposed approaches are competitive.

Morphology and electrostatics play active role in neuronal differentiation processes on flexible conducting substrates

This commentary discusses and summarizes the key highlights of our recently reported work entitled ``Neuronal Differentiation of Embryonic Stem Cell Derived Neuronal Progenitors Can Be Regulated by Stretchable Conducting Polymers.'' The prospect of controlling the mechanical-rigidity and the surface conductance properties offers a unique combination for tailoring the growth and differentiation of neuronal cells. We emphasize the utility of transparent elastomeric substrates with coatings of electrically conducting polymer to realize the desired substrate-characteristics for cellular development processes. Our study showed that neuronal differentiation from ES cells is highly influenced by the specific substrates on which they are growing. Thus, our results provide a better strategy for regulated neuronal differentiation by using such functional conducting surfaces.

Imprints of Archean to Neoproterozoic crustal processes in the Madurai Block, Southern India

Madurai Block, the largest crustal block in the Southern Granulite Terrane (SGT) of Peninsular India, preserves the imprints of multistage tectonic evolution. Here, we present U-Pb and Hf isotope data on zircons from a charnockite-granite suite in the north-western part of this block. The oscillatory zoning, and the LREE to HREE enriched patterns of the zircons with positive Ce and negative Eu anomalies suggest that the zircon cores are of magmatic origin, with ages in the range of 2634-2435 Ma implying Neoarchean-Paleoproterozoic magmatism followed by subsequent metamorphism and protocontinent formation in the north-western part of the Madurai Block. A regional 550-500 Ma metamorphic overprint is also preserved in the zircons coinciding with the final amalgamation of the Gondwana supercontinent. The Hf isotopic data suggest that the granite and charnockite were derived from isotopically heterogeneous juvenile crustal domains and the charnockites show a significant contribution of mantle-derived components. Therefore, the Hf isotopic data reflect mixing of crustal and mantle-derived sources for the generation of Neoarchean crust in the north-western Madurai Block, possibly in a suprasubduction zone setting during continent building processes. (c) 2014 Elsevier Ltd. All rights reserved.

A modeling study of the processes of surface salinity seasonal cycle in the Bay of Bengal

In response to the Indian Monsoon freshwater forcing, the Bay of Bengal exhibits a very strong seasonal cycle in sea surface salinity (SSS), especially near the mouths of the Ganges-Brahmaputra and along the east coast of India. In this paper, we use an eddy-permitting (similar to 25 km resolution) regional ocean general circulation model simulation to quantify the processes responsible for this SSS seasonal cycle. Despite the absence of relaxation toward observations, the model reproduces the main features of the observed SSS seasonal cycle, with freshest water in the northeastern Bay, particularly during and after the monsoon. The model also displays an intense and shallow freshening signal in a narrow (similar to 100 km wide) strip that hugs the east coast of India, from September to January, in good agreement with high-resolution measurements along two ships of opportunity lines. The mixed layer salt budget confirms that the strong freshening in the northern Bay during the monsoon results from the Ganges-Brahmaputra river discharge and from precipitation over the ocean. From September onward, the East India Coastal Current transports this freshwater southward along the east coast of India, reaching the southern tip of India in November. The surface freshening results in an enhanced vertical salinity gradient that increases salinity of the surface layer by vertical processes. Our results reveal that the erosion of the freshwater tongue along the east coast of India is not driven by northward horizontal advection, but by vertical processes that eventually overcome the freshening by southward advection and restore SSS to its premonsoon values. The salinity-stratified barrier layer hence only acts as a ``barrier'' for vertical heat fluxes, but is associated with intense vertical salt fluxes in the Bay of Bengal.

Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition

A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.

Breakup processes of pressure swirl spray in gaseous cross-flow

Injection of liquid fuel in cross flowing air has been a strategy for future aircraft engines in order to control the emissions. In this context, breakup of a pressure swirl spray in gaseous cross-flow is investigated experimentally. The atomizer discharges a conical swirling sheet of liquid that interacts with cross-flowing air. This complex interaction and the resulting spray structures at various flow conditions are studied through flow visualization using still as well as high speed photography. Experiments are performed over a wide range of aerodynamic Weber number (2-300) and liquid-to-air momentum flux ratio (5-150). Various breakup regimes exhibiting different breakup processes are mapped on a parameter space based on flow conditions. This map shows significant variations from breakup regime map for a plain liquid jet in cross-flow. It is observed that the breakup of leeward side of the sheet is dominated by bag breakup and the windward side of the sheet undergoes breakup through surface waves. Similarities and differences between bag breakup present in plain liquid jet in cross-flow and swirl spray in cross-flow are explained. Multimodal drop size distribution from bag breakup, frequency of bag breakup, wavelength of surface waves and trajectory of spray in cross-flow are measured by analyzing the spray images and parametric study of their variations is also presented. (C) 2014 Elsevier Ltd. All rights reserved.

Sliding Mode Control-Based Autopilots for Leaderless Consensus of Unmanned Aerial Vehicles

In this brief, decentralized sliding mode controllers that enable a connected and leaderless swarm of unmanned aerial vehicles (UAVs) to reach a consensus in altitude and heading angle are presented. In addition, sliding mode control-based autopilot designs to control those states for which consensus is not required are also presented. By equipping each UAV with this combination of controllers, it can autonomously decide on being a member of the swarm or fly independently. The controllers are designed using a coupled nonlinear dynamic model, derived for the YF-22 aircraft, where the aerodynamic forces and moments are linear functions of the states and inputs.