Thermally developing combined electroosmotic and pressure-driven flow of nanofluids in a microchannel under the effect of magnetic field

In the present study, the heat transfer characteristics of thermally developing magnetohydroclynamic flow of nanofluid through microchannel are delineated by following a semi analytical approach. The combined influences of pressure driven flow, electroosmotic transport and magnetic field is taken into account for the analysis of the complex microscale thermal transport processes. Solutions for the normalized temperature distributions and the Nusselt number variations, considering the simultaneous interplay of electrokinetic effects (electroosmosis), magnetic effects, Joule heating and viscous dissipation are obtained, for constant wall temperature condition. Particular attention is paid to assess the role of nanolluids in altering the transport phenomena, through variations in the effective nanoparticle volume fractions, as well as the aggregate structure of the particulate phases. It is observed that magnetohydrodynamic effect reduces advective transport of the liquid resulting in gradual reduction of heat transfer. Increase in nanoparticle volume fraction shows decrease in heat transfer. Similar effects are observed with increase in aggregate sizes of the nanoparticles. The effect of the nanofluids on system irreversibility is also studied through entropy generation analysis due to flow and heat transfer in the microchannel. Total entropy generation is found to be dominant at the thermally developing region of the microchannel, whereas it drops sharply at the thermally developed region. Presence of nanoparticles in the base fluid reduces the total entropy generation in the microchannel, thereby indicating decrease in thermodynamic irreversibility with increasing nanoparticle volume fraction. (C) 2014 Elsevier Ltd. All rights reserved.

Fabrication of novel Ag3PO4/BiOBr heterojunction with high stability and enhanced visible-light-driven photocatalytic activity

Herein, we report a facile and effective method to enhance the photocatalytic activity of bismuth oxybromide (BiOBr) semiconductor through the fabrication of heterojunction with Ag3PO4. The as synthesized Ag3PO4/BiOBr microspheres were characterized with transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), X-ray diffraction (XRD) and UV-vis diffuse reflectance spectroscopy (DRS). The new Ag3PO4/BiOBr heterojunctions exhibited wide absorption in the visible-light region and compared to pure BiOBr and Ag3PO4 samples displayed exceptionally high photocatalytic activity for the degradation of typical organic pollutants such as Rhodamine B (RhB) and phenol. The optimal Ag/Bi weight ratio in Ag3PO4/BiOBr microsphere (AB7) was found to be 0.7. The enhanced photocatalytic activity was related to the efficient separation of electron-hole pairs derived from matching band potentials between BiOBr and Ag3PO4 which results into the generation of natural energy bias at heterojunction and subsequent transfer of photoinduced charge carriers. Moreover, the synthesized samples exhibited almost no loss of activity even after 6 recycling runs indicating their high photocatalytic stability. Considering the facile and environment friendly route for the synthesis of Ag3PO4/BiOBr hybrids with enhanced visible-light induced photocatalytic activity, it is possible to widely apply these hybrids in various fields such as waste water treatment. (C) 2015 Elsevier B.V. All rights reserved.

Fully developed thermal transport in combined pressure and electroosmotically driven flow of nanofluid in a microchannel under the effect of a magnetic field

This paper critically analyzes, for the first time, the effect of nanofluid on thermally fully developed magnetohydrodynamic flows through microchannel, by considering combined effects of externally applied pressure gradient and electroosmosis. The classical boundary condition of uniform wall heat flux is considered, and the effects of viscous dissipation as well as Joule heating have been taken into account. Closed-form analytical expressions for the pertinent velocity and temperature distributions and the Nusselt number variations are obtained, in order to examine the role of nanofluids in influencing the fully developed thermal transport in electroosmotic microflows under the effect of magnetic field. Fundamental considerations are invoked to ascertain the consequences of particle agglomeration on the thermophysical properties of the nanofluid. The present theoretical formalism addresses the details of the interparticle interaction kinetics in tune with the pertinent variations in the effective particulate dimensions, volume fractions of the nanoparticles, as well as the aggregate structure of the particulate system. It is revealed that the inclusion of nanofluid changes the transport characteristics and system irreversibility to a considerable extent and can have significant consequences in the design of electroosmotically actuated microfluidic systems.

A provably tight delay-driven concurrently congestion mitigating global routing algorithm

Routing is a very important step in VLSI physical design. A set of nets are routed under delay and resource constraints in multi-net global routing. In this paper a delay-driven congestion-aware global routing algorithm is developed, which is a heuristic based method to solve a multi-objective NP-hard optimization problem. The proposed delay-driven Steiner tree construction method is of O(n(2) log n) complexity, where n is the number of terminal points and it provides n-approximation solution of the critical time minimization problem for a certain class of grid graphs. The existing timing-driven method (Hu and Sapatnekar, 2002) has a complexity O(n(4)) and is implemented on nets with small number of sinks. Next we propose a FPTAS Gradient algorithm for minimizing the total overflow. This is a concurrent approach considering all the nets simultaneously contrary to the existing approaches of sequential rip-up and reroute. The algorithms are implemented on ISPD98 derived benchmarks and the drastic reduction of overflow is observed. (C) 2014 Elsevier Inc. All rights reserved.

The Self-Association of Graphane Is Driven by London Dispersion and Enhanced Orbital Interactions

We investigated the nature of the cohesive energy between graphane sheets via multiple CH center dot center dot center dot HC interactions, using density functional theory (DFT) including dispersion correction (Grimmes D3 approach) computations of n]graphane sigma dimers (n = 6-73). For comparison, we also evaluated the binding between graphene sheets that display prototypical pi/pi interactions. The results were analyzed using the block-localized wave function (BLW) method, which is a variant of ab initio valence bond (VB) theory. BLW interprets the intermolecular interactions in terms of frozen interaction energy (Delta E-F) composed of electrostatic and Pauli repulsion interactions, polarization (Delta E-pol), charge-transfer interaction (Delta E-CT), and dispersion effects (Delta E-disp). The BLW analysis reveals that the cohesive energy between graphane sheets is dominated by two stabilizing effects, namely intermolecular London dispersion and two-way charge transfer energy due to the sigma CH -> sigma*(HC) interactions. The shift of the electron density around the nonpolar covalent C-H bonds involved in the intermolecular interaction decreases the C-H bond lengths uniformly by 0.001 angstrom. The Delta E-CT term, which accounts for similar to 15% of the total binding energy, results in the accumulation of electron density in the interface area between two layers. This accumulated electron density thus acts as an electronic glue for the graphane layers and constitutes an important driving force in the self-association and stability of graphane under ambient conditions. Similarly, the double faced adhesive tape style of charge transfer interactions was also observed among graphene sheets in which it accounts for similar to 18% of the total binding energy. The binding energy between graphane sheets is additive and can be expressed as a sum of CH center dot center dot center dot HC interactions, or as a function of the number of C-H bonds.

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Sensory cues employed for the acquisition of familiarity-dependent recognition of a shoal of conspecifics by climbing perch (Anabas testudineus Bloch)

In this study we showed that a freshwater fish, the climbing perch (Anabas testudineus) is incapable of using chemical communication but employs visual cues to acquire familiarity and distinguish a familiar group of conspecifics from an unfamiliar one. Moreover, the isolation of olfactory signals from visual cues did not affect the recognition and preference for a familiar shoal in this species.

Structural-modulation-driven spin canting and reentrant glassy magnetic phase in ferromagnetic Lu2MnNiO6

Unusual behavior of reentrant spin-glass (RSG) compound Lu2MnNiO6 has been investigated by magnetometry and neutron diffraction. The system possesses a ferromagnetic (FM) ordering below 40 K and undergoes a RSG transition at 20 K. Additionally, Lu2MnNiO6 retains memory effect above the glassy transition till spins sustain ordering. A novel critical behavior with unusual critical exponents (beta =similar to 0.241 and gamma similar to 1.142) is observed that indicates a canting in the spin structure below the ferromagnetic transition (T-C). A comprehensive analysis of temperature-dependent neutron diffraction data and first-principles calculations divulge that a structural distortion induced by an octahedral tilting results in a canted spin structure below T-C.

Surface motions and intraplate continental deformation in Alaska driven by mantle flow

The degree to which the lithosphere and mantle are coupled and contribute to surface deformation beneath continental regions remains a fundamental question in the field of geodynamics. Here we use a new approach with a surface deformation field constrained by GPS, geologic, and seismicity data, together with a lithospheric geodynamic model, to solve for tractions inferred to be generated by mantle convection that (1) drive extension within interior Alaska generating southward directed surface motions toward the southern convergent plate boundary, (2) result in accommodation of the relative motions between the Pacific and North America in a comparatively small zone near the plate boundary, and (3) generate the observed convergence within the North American plate interior in the Mackenzie mountains in northwestern Canada. The evidence for deeper mantle influence on surface deformation beneath a continental region suggests that this mechanism may be an important contributing driver to continental plate assemblage and breakup.

Sonic hedgehog-Dependent Induction of MicroRNA 31 and MicroRNA 150 Regulates Mycobacterium bovis BCG-Driven Toll-Like Receptor 2 Signaling

Hedgehog (HH) signaling is a significant regulator of cell fate decisions during embryogenesis, development, and perpetuation of various disease conditions. Testing whether pathogen-specific HH signaling promotes unique innate recognition of intracellular bacteria, we demonstrate that among diverse Gram-positive or Gram-negative microbes, Mycobacterium bovis BCG, a vaccine strain, elicits a robust activation of Sonic HH (SHH) signaling in macrophages. Interestingly, sustained tumor necrosis factor alpha (TNF-alpha) secretion by macrophages was essential for robust SHH activation, as TNF-alpha(-/-) macrophages exhibited compromised ability to activate SHH signaling. Neutralization of TNF-alpha or blockade of TNF-alpha receptor signaling significantly reduced the infection-induced SHH signaling activation both in vitro and in vivo. Intriguingly, activated SHH signaling downregulated M. bovis BCG-mediated Toll-like receptor 2 (TLR2) signaling events to regulate a battery of genes associated with divergent functions of M1/M2 macrophages. Genome-wide expression profiling as well as conventional gain-of-function or loss-of-function analysis showed that SHH signaling-responsive microRNA 31 (miR-31) and miR-150 target MyD88, an adaptor protein of TLR2 signaling, thus leading to suppression of TLR2 responses. SHH signaling signatures could be detected in vivo in tuberculosis patients and M. bovis BCG-challenged mice. Collectively, these investigations identify SHH signaling to be what we believe is one of the significant regulators of host-pathogen interactions.

Anisotropic magnetic couplings and structure-driven canted to collinear transitions in Sr2IrO4 by magnetically constrained noncollinear DFT

We study the canted magnetic state in Sr2IrO4 using fully relativistic density functional theory (DFT) including an on-site Hubbard U correction. A complete magnetic phase diagram with respect to the tetragonal distortion and the rotation of IrO6 octahedra is constructed, revealing the presence of two types of canted to collinear magnetic transitions: a spin-flop transition with increasing tetragonal distortion and a complete quenching of the basal weak ferromagnetic moment below a critical octahedral rotation. Moreover, we put forward a scheme to study the anisotropic magnetic couplings by mapping magnetically constrained noncollinear DFT onto a general spin Hamiltonian. This procedure allows for the simultaneous account and direct control of the lattice, spin, and orbital interactions within a fully ab initio scheme. We compute the isotropic, single site anisotropy and Dzyaloshinskii-Moriya (DM) coupling parameters, and clarify that the origin of the canted magnetic state in Sr2IrO4 arises from the structural distortions and the competition between isotropic exchange and DM interactions.

Dual Stress and Thermally Driven Mechanical Properties of the Same Organic Crystal: 2,6-Dichlorobenzylidene-4-fluoro-3-nitroaniline

An elastic organic crystal, 2,6-dichlorobenzylidine-4-fluoro-3-nitroaniline (DFNA), which also shows thermosalient behavior, is studied. The presence of these two distinct properties in the same crystal is unusual and unprecedented because they follow respectively from isotropy and anisotropy in the crystal packing. Therefore, while both properties lead from the crystal structure, the mechanisms for bending and thermosalience are quite independent of one another. Crystals of the low-temperature (a) form of the title compound are bent easily without any signs of fracture with the application of deforming stress, and this bending is within the elastic limit. The crystal structure of the a-form was determined (P2(1)/c, Z = 4, a = 3.927(7) angstrom, b = 21.98(4) angstrom, c = 15.32(3) angstrom). There is an irreversible phase transition at 138 degrees C of this form to the high-temperature beta-form followed by melting at 140 degrees C. Variable-temperature X-ray powder diffraction was used to investigate the structural changes across the phase transition and, along with an FTIR study, establishes the structure of the beta-form. A possible rationale for strain build-up is given. Thermosalient behavior arises from anisotropic changes in the three unit cell parameters across the phase transition, notably an increase in the b axis parameter from 21.98 to 22.30 angstrom. A rationale is provided for the existence of both elasticity and thermosalience in the same crystal. FTIR studies across the phase transition reveal important mechanistic insights: (i) increased pi...pi repulsions along 100] lead to expansion along the a axis; (ii) change in alignment of C-Cl and NO2 groups result from density changes; and (iii) competition between short-range repulsive (pi...pi) interactions and long-range attractive dipolar interactions (C-Cl and NO2) could lie at the origin of the existence of two distinctive properties.

Internal noise-driven generalized Langevin equation from a nonlocal continuum model

Starting with a micropolar formulation, known to account for nonlocal microstructural effects at the continuum level, a generalized Langevin equation (GLE) for a particle, describing the predominant motion of a localized region through a single displacement degree of freedom, is derived. The GLE features a memory-dependent multiplicative or internal noise, which appears upon recognizing that the microrotation variables possess randomness owing to an uncertainty principle. Unlike its classical version, the present GLE qualitatively reproduces the experimentally measured fluctuations in the steady-state mean square displacement of scattering centers in a polyvinyl alcohol slab. The origin of the fluctuations is traced to nonlocal spatial interactions within the continuum, a phenomenon that is ubiquitous across a broad class of response regimes in solids and fluids. This renders the proposed GLE a potentially useful model in such cases.

Simultaneous acquisition of three NMR spectra in a single experiment for rapid resonance assignments in metabolomics

NMR-based approach to metabolomics typically involves the collection of two-dimensional (2D) heteronuclear correlation spectra for identification and assignment of metabolites. In case of spectral overlap, a 3D spectrum becomes necessary, which is hampered by slow data acquisition for achieving sufficient resolution. We describe here a method to simultaneously acquire three spectra (one 3D and two 2D) in a single data set, which is based on a combination of different fast data acquisition techniques such as G-matrix Fourier transform (GFT) NMR spectroscopy, parallel data acquisition and non-uniform sampling. The following spectra are acquired simultaneously: (1) C-13 multiplicity edited GFT (3,2)D HSQC-TOCSY, (2) 2D H-1- H-1] TOCSY and (3) 2D C-13- H-1] HETCOR. The spectra are obtained at high resolution and provide high-dimensional spectral information for resolving ambiguities. While the GFT spectrum has been shown previously to provide good resolution, the editing of spin systems based on their CH multiplicities further resolves the ambiguities for resonance assignments. The experiment is demonstrated on a mixture of 21 metabolites commonly observed in metabolomics. The spectra were acquired at natural abundance of C-13. This is the first application of a combination of three fast NMR methods for small molecules and opens up new avenues for high-throughput approaches for NMR-based metabolomics.

Segregating Discourse Segments from Engineering Documents for Knowledge Acquisition

The broader goal of the research being described here is to automatically acquire diagnostic knowledge from documents in the domain of manual and mechanical assembly of aircraft structures. These documents are treated as a discourse used by experts to communicate with others. It therefore becomes possible to use discourse analysis to enable machine understanding of the text. The research challenge addressed in the paper is to identify documents or sections of documents that are potential sources of knowledge. In a subsequent step, domain knowledge will be extracted from these segments. The segmentation task requires partitioning the document into relevant segments and understanding the context of each segment. In discourse analysis, the division of a discourse into various segments is achieved through certain indicative clauses called cue phrases that indicate changes in the discourse context. However, in formal documents such language may not be used. Hence the use of a domain specific ontology and an assembly process model is proposed to segregate chunks of the text based on a local context. Elements of the ontology/model, and their related terms serve as indicators of current context for a segment and changes in context between segments. Local contexts are aggregated for increasingly larger segments to identify if the document (or portions of it) pertains to the topic of interest, namely, assembly. Knowledge acquired through such processes enables acquisition and reuse of knowledge during any part of the lifecycle of a product.