Riemann shock tube: 1D normal shocks in air, simulations and experiments

This paper presents numerical simulation of the evolution of one-dimensional normal shocks, their propagation, reflection and interaction in air using a single diaphragm Riemann shock tube and validate them using experimental results. Mathematical model is derived for one-dimensional compressible flow of viscous and conducting medium. Dimensionless form of the mathematical model is used to construct space-time finite element processes based on minimization of the space-time residual functional. The space-time local approximation functions for space-time p-version hierarchical finite elements are considered in higher order GRAPHICS] spaces that permit desired order of global differentiability of local approximations in space and time. The resulting algebraic systems from this approach yield unconditionally positive-definite coefficient matrices, hence ensure unique numerical solution. The evolution is computed for a space-time strip corresponding to a time increment Delta t and then time march to obtain the evolution up to any desired value of time. Numerical studies are designed using recently invented hand-driven shock tube (Reddy tube) parameters, high/low side density and pressure values, high- and low-pressure side shock tube lengths, so that numerically computed results can be compared with actual experimental measurements.

Collective eigenstates of emission in an N-entity heterostructure and the evaluation of its Green tensors and self-energy components

Optical emission from emitters strongly interacting among themselves and also with other polarizable matter in close proximity has been approximated by emission from independent emitters. This is primarily due to our inability to evaluate the self-energy matrices and radiative properties of the collective eigenstates of emitters in heterogeneous ensembles. A method to evaluate self-energy matrices that is not limited by the geometry and material composition is presented to understand and exploit such collective excitations. Numerical evaluations using this method are used to highlight the significant differences between independent and the collective modes of emission in nanoscale heterostructures. A set of N Lorentz emitters and other polarizable entities is used to represent the coupled system of a generalized geometry in a volume integral approach. Closed form relations between the Green tensors of entity pairs in free space and their correspondents in a heterostructure are derived concisely. This is made possible for general geometries because the global matrices consisting of all free-space Green dyads are subject to conservation laws. The self-energy matrix can then be assembled using the evaluated Green tensors of the heterostructure, but a decomposition of its components into their radiative and nonradiative decay contributions is nontrivial. The relations to compute the observables of the eigenstates (such as quantum efficiency, power/energy of emission, radiative and nonradiative decay rates) are presented. A note on extension of this method to collective excitations, which also includes strong interactions with a surface in the near-field, is added. (C) 2014 Optical Society of America

Hardware Accelerator for 3D Method of Moments based Parasitic Extraction

A Field Programmable Gate Array (FPGA) based hardware accelerator for multi-conductor parasitic capacitance extraction, using Method of Moments (MoM), is presented in this paper. Due to the prohibitive cost of solving a dense algebraic system formed by MoM, linear complexity fast solver algorithms have been developed in the past to expedite the matrix-vector product computation in a Krylov sub-space based iterative solver framework. However, as the number of conductors in a system increases leading to a corresponding increase in the number of right-hand-side (RHS) vectors, the computational cost for multiple matrix-vector products present a time bottleneck, especially for ill-conditioned system matrices. In this work, an FPGA based hardware implementation is proposed to parallelize the iterative matrix solution for multiple RHS vectors in a low-rank compression based fast solver scheme. The method is applied to accelerate electrostatic parasitic capacitance extraction of multiple conductors in a Ball Grid Array (BGA) package. Speed-ups up to 13x over equivalent software implementation on an Intel Core i5 processor for dense matrix-vector products and 12x for QR compressed matrix-vector products is achieved using a Virtex-6 XC6VLX240T FPGA on Xilinx's ML605 board.

Use of a structural alphabet to find compatible folds for amino acid sequences

The structural annotation of proteins with no detectable homologs of known 3D structure identified using sequence-search methods is a major challenge today. We propose an original method that computes the conditional probabilities for the amino-acid sequence of a protein to fit to known protein 3D structures using a structural alphabet, known as Protein Blocks (PBs). PBs constitute a library of 16 local structural prototypes that approximate every part of protein backbone structures. It is used to encode 3D protein structures into 1D PB sequences and to capture sequence to structure relationships. Our method relies on amino acid occurrence matrices, one for each PB, to score global and local threading of query amino acid sequences to protein folds encoded into PB sequences. It does not use any information from residue contacts or sequence-search methods or explicit incorporation of hydrophobic effect. The performance of the method was assessed with independent test datasets derived from SCOP 1.75A. With a Z-score cutoff that achieved 95% specificity (i.e., less than 5% false positives), global and local threading showed sensitivity of 64.1% and 34.2%, respectively. We further tested its performance on 57 difficult CASP10 targets that had no known homologs in PDB: 38 compatible templates were identified by our approach and 66% of these hits yielded correctly predicted structures. This method scales-up well and offers promising perspectives for structural annotations at genomic level. It has been implemented in the form of a web-server that is freely available at http://www.bo-protscience.fr/forsa.

Monopoles, Dirac operator, and index theory for fuzzy SU(3) / (U(1) x U(1))

The intersection of the ten-dimensional fuzzy conifold Y-F(10) with S-F(5) x S-F(5) is the compact eight-dimensional fuzzy space X-F(8). We show that X-F(8) is (the analogue of) a principal U(1) x U(1) bundle over fuzzy SU(3) / U(1) x U(1)) ( M-F(6)). We construct M-F(6) using the Gell-Mann matrices by adapting Schwinger's construction. The space M-F(6) is of relevance in higher dimensional quantum Hall effect and matrix models of D-branes. Further we show that the sections of the monopole bundle can be expressed in the basis of SU(3) eigenvectors. We construct the Dirac operator on M-F(6) from the Ginsparg-Wilson algebra on this space. Finally, we show that the index of the Dirac operator correctly reproduces the known results in the continuum.

Optimal control of grinding mill circuit using model predictive static programming: A new nonlinear MPC paradigm

The recently developed reference-command tracking version of model predictive static programming (MPSP) is successfully applied to a single-stage closed grinding mill circuit. MPSP is an innovative optimal control technique that combines the philosophies of model predictive control (MPC) and approximate dynamic programming. The performance of the proposed MPSP control technique, which can be viewed as a `new paradigm' under the nonlinear MPC philosophy, is compared to the performance of a standard nonlinear MPC technique applied to the same plant for the same conditions. Results show that the MPSP control technique is more than capable of tracking the desired set-point in the presence of model-plant mismatch, disturbances and measurement noise. The performance of MPSP and nonlinear MPC compare very well, with definite advantages offered by MPSP. The computational speed of MPSP is increased through a sequence of innovations such as the conversion of the dynamic optimization problem to a low-dimensional static optimization problem, the recursive computation of sensitivity matrices and using a closed form expression to update the control. To alleviate the burden on the optimization procedure in standard MPC, the control horizon is normally restricted. However, in the MPSP technique the control horizon is extended to the prediction horizon with a minor increase in the computational time. Furthermore, the MPSP technique generally takes only a couple of iterations to converge, even when input constraints are applied. Therefore, MPSP can be regarded as a potential candidate for online applications of the nonlinear MPC philosophy to real-world industrial process plants. (C) 2014 Elsevier Ltd. All rights reserved.

LOWER BOUNDS FOR BOXICITY

An axis-parallel b-dimensional box is a Cartesian product R-1 x R-2 x ... x R-b where R-i is a closed interval of the form a(i),b(i)] on the real line. For a graph G, its boxicity box(G) is the minimum dimension b, such that G is representable as the intersection graph of boxes in b-dimensional space. Although boxicity was introduced in 1969 and studied extensively, there are no significant results on lower bounds for boxicity. In this paper, we develop two general methods for deriving lower bounds. Applying these methods we give several results, some of which are listed below: 1. The boxicity of a graph on n vertices with no universal vertices and minimum degree delta is at least n/2(n-delta-1). 2. Consider the g(n,p) model of random graphs. Let p <= 1 - 40logn/n(2.) Then with high `` probability, box(G) = Omega(np(1 - p)). On setting p = 1/2 we immediately infer that almost all graphs have boxicity Omega(n). Another consequence of this result is as follows: For any positive constant c < 1, almost all graphs on n vertices and m <= c((n)(2)) edges have boxicity Omega(m/n). 3. Let G be a connected k-regular graph on n vertices. Let lambda be the second largest eigenvalue in absolute value of the adjacency matrix of G. Then, the boxicity of G is a least (kappa(2)/lambda(2)/log(1+kappa(2)/lambda(2))) (n-kappa-1/2n). 4. For any positive constant c 1, almost all balanced bipartite graphs on 2n vertices and m <= cn(2) edges have boxicity Omega(m/n).

Long-Term Sustained Release of Salicylic Acid from Cross-Linked Biodegradable Polyester Induces a Reduced Foreign Body Response in Mice

There has been a continuous surge toward developing new biopolymers that exhibit better in vivo biocompatibility properties in terms of demonstrating a reduced foreign body response (FBR). One approach to mitigate the undesired FBR is to develop an implant capable of releasing anti-inflammatory molecules in a sustained manner over a long time period. Implants causing inflammation are also more susceptible to infection. In this article, the in vivo biocompatibility of a novel, biodegradable salicylic acid releasing polyester (SAP) has been investigated by subcutaneous implantation in a mouse model. The tissue response to SAP was compared with that of a widely used biodegradable polymer, poly(lactic acid-co-glycolic acid) (PLGA), as a control over three time points: 2, 4, and 16 weeks postimplantation. A long-term in vitro study illustrates a continuous, linear (zero order) release of salicylic acid with a cumulative mass percent release rate of 7.34 x 10(-4) h(-1) over similar to 1.5-17 months. On the basis of physicochemical analysis, surface erosion for SAP and bulk erosion for PLGA have been confirmed as their dominant degradation modes in vivo. On the basis of the histomorphometrical analysis of inflammatory cell densities and collagen distribution as well as quantification of proinflammatory cytokine levels (TNF-alpha and IL-1 beta), a reduced foreign body response toward SAP with respect to that generated by PLGA has been unambiguously established. The favorable in vivo tissue response to SAP, as manifest from the uniform and well-vascularized encapsulation around the implant, is consistent with the decrease in inflammatory cell density and increase in angiogenesis with time. The above observations, together with the demonstration of long-term and sustained release of salicylic acid, establish the potential use of SAP for applications in improved matrices for tissue engineering and chronic wound healing.

Non-Abelian gauge redundancy and entropic ambiguities

The von Neumann entropy of a generic quantum state is not unique unless the state can be uniquely decomposed as a sum of extremal or pure states. Therefore one reaches the remarkable possibility that there may be many entropies for a given state. We show that this happens if the GNS representation (of the algebra of observables in some quantum state) is reducible, and some representations in the decomposition occur with non-trivial degeneracy. This ambiguity in entropy, which can occur at zero temperature, can often be traced to a gauge symmetry emergent from the non-trivial topological character of the configuration space of the underlying system. We also establish the analogue of an H-theorem for this entropy by showing that its evolution is Markovian, determined by a stochastic matrix. After demonstrating this entropy ambiguity for the simple example of the algebra of 2 x 2 matrices, we argue that the degeneracies in the GNS representation can be interpreted as an emergent broken gauge symmetry, and play an important role in the analysis of emergent entropy due to non-Abelian anomalies. We work out the simplest situation with such non-Abelian symmetry, that of an ethylene molecule.

Fly ash cenospheres as reinforcement in different polymer composites - a comparative study of physical and mechanical properties

The work reports the preparation of fly ash cenospheres bearing polymer composites, using various polymer matrix materials namely, low density polyethylene, high density polyethylene, polystyrene and polymethylmethacrylate followed by evaluation of properties. The composites are synthesized by including about 18% by weight fly ash cenospheres, into various polymer matrices using brabender facility in the temperature range 120-160 degrees C and at a mixing pressure of 50 MPa. Subsequently, they are cast into sheets through compression moulding. The test samples, made from the sheets, are characterized for physical as well as mechanical properties such as density, hardness, compression strength, impact response, wear and friction. The investigation reveals that the addition of fly ash cenospheres to various polymer matrices results in reduction of density. Further, improvements in the slide wear resistance and decrease in the co-efficient of friction values are noticed. As for interpreting the slide wear data, recourse to examination under scanning electron microscope is made in this paper. As regards the mechanical properties, hardness increases while the compression strength and impact energy decreases with inclusion of cenospheres in all the four types of samples investigated.

Carbon-Nanohorn-Reinforced Polymer Matrix Composites: Synergetic Benefits in Mechanical Properties

Mechanical properties of single-walled carbon nanohoms (SWNH) and SWNH plus few-layer graphene (EG)-reinforced poly(vinyl alcohol) (PVA) matrix composites have been measured using the nanoindentation technique. The elastic modulus (E) and hardness (H) of PVA were found to improve by similar to 315% and similar to 135%, respectively, upon the addition of just 0.4 wt % SWNH. These properties were found to be comparable to those obtained upon the addition of 0.2 wt % single-walled nanotubes (SWNT) to PVA. Furthermore, upon binary addition of 0.2 wt % EG and 0.4 wt % SWNH to PVA, benefits in the form of similar to 400% and similar to 330% synergy in E and H, respectively, were observed, along with an increased resistance to viscoelastic deformation. The reasons for these improvements are discussed in terms of the dimensionality of nanocarbon, the effectiveness of nanocarbon and polymer matrix interaction, and the influence of nanocarbon on the degree of crystallinity of the polymer. The results from SWNH reinforcement in this study demonstrate the scope for a novel and, in contrast to SWNT composites, a commercially feasible opportunity for strengthening polymer matrices.

Graphene scavenges free radicals to synergistically enhance structural properties in a gamma-irradiated polyethylene composite through enhanced interfacial interactions

A unique strategy for scavenging free radicals in situ on exposure to gamma irradiation in polyethylene (PE) nanocomposites is presented. Blends of ultra-high molecular weight PE and linear low-density PE (PEB) and their nanocomposites with graphene (GPEB) were prepared by melt mixing to develop materials for biomedical implants. The effect of gamma irradiation on the microstructure and mechanical properties was systematically investigated. The neat blend and the nanocomposite were subjected to gamma-ray irradiation in order to improve the interfacial adhesion between PE and graphene sheets. Structural and thermal characterization revealed that irradiation induced crosslinking and increased the crystallinity of the polymer blend. The presence of graphene further enhanced the crystallinity via crosslinks between the polymer matrix and the filler on irradiation. Graphene was found to scavenge free radicals as confirmed by electron paramagnetic resonance spectroscopy. Irradiation of graphene-containing polymer composites resulted in the largest increase in modulus and hardness compared to either irradiation or addition of graphene to PEB alone. This study provides new insight into the role of graphene in polymer matrices during irradiation and suggests that irradiated graphene-polymer composites could emerge as promising materials for use as articulating surfaces in biomedical implants.

Meshless Local Petrov-Galerkin Method for Rotating Euler-Bernoulli Beam

Free vibration problem of a rotating Euler-Bernoulli beam is solved with a truly meshless local Petrov-Galerkin method. Radial basis function and summation of two radial basis functions are used for interpolation. Radial basis function satisfies the Kronecker delta property and makes it simpler to apply the essential boundary conditions. Interpolation with summation of two radial basis functions increases the node carrying capacity within the sub-domain of the trial function and higher natural frequencies can be computed by selecting the complete domain as a sub-domain of the trial function. The mass and stiffness matrices are derived and numerical results for frequencies are obtained for a fixed-free beam and hinged-free beam simulating hingeless and articulated helicopter blades. Stiffness and mass distribution suitable for wind turbine blades are also considered. Results show an accurate match with existing literature.

Interlaboratory comparison of magnesium isotopic compositions of 12 felsic to ultramafic igneous rock standards analyzed by MC-ICPMS

To evaluate the interlaboratory mass bias for high-precision stable Mg isotopic analysis of natural materials, a suite of silicate standards ranging in composition from felsic to ultramafic were analyzed in five laboratories by using three types of multicollector inductively coupled plasma mass spectrometer (MC-ICPMS). Magnesium isotopic compositions from all labs are in agreement for most rocks within quoted uncertainties but are significantly (up to 0.3 parts per thousand in Mg-26/Mg-24, > 4 times of uncertainties) different for some mafic samples. The interlaboratory mass bias does not correlate with matrix element/Mg ratios, and the mechanism for producing it is uncertain but very likely arises from column chemistry. Our results suggest that standards with different matrices are needed to calibrate the efficiency of column chemistry and caution should be taken when dealing with samples with complicated matrices. Well-calibrated standards with matrix elements matching samples should be used to reduce the interlaboratory mass bias.

Noble metal ions in CeO2 and TiO2: synthesis, structure and catalytic properties

In the past four decades, CeO2 has been recognized as an attractive material in the area of auto exhaust catalysis because of its unique redox properties. In the presence of CeO2, the catalytic activity of noble metals supported on Al2O3 is enhanced due to higher dispersion of noble metals in their ionic form. In the last few years, we have been exploring an entirely new approach of dispersing noble metal ions on CeO2 and TiO2 matrices for redox catalysis. In this study, the dispersion of noble metal ions by solution combustion as well as other methods over CeO2 and TiO2 resulting mainly in Ce1-xMxO2-delta, Ce1-x-yTixMyO2-delta, Ce1-x-ySnxMyO2-delta, Ce1-x-yFexMyO2-delta, Ce1-x-yZrxMyO2-delta and Ti1-xMxO2-delta (M = Pd, Pt, Rh and Ru) catalysts, the structure of these materials, their catalytic properties toward different types of catalysis, structure-property relationships and mechanisms of catalytic reactions are reviewed. In these catalysts, noble metal ions are incorporated into a substrate matrix to a certain limit in a solid solution form. Lower valent noble metal-ion substitution in CeO2 and TiO2 creates noble metal ionic sites and oxide ion vacancies that act as adsorption sites for redox catalysis. It has been demonstrated that these new generation noble metal ionic catalysts (NMIC) have been found to be catalytically more active than conventional nanocrystalline noble metal catalysts dispersed on oxide supports.