A meshless adaptive multiscale method for fracture

The paper presents a multiscale method for crack propagation. The coarse region is modelled by the differential reproducing kernel particle method. Fracture in the coarse scale region is modelled with the Phantom node method. A molecular statics approach is employed in the fine scale where crack propagation is modelled naturally by breaking of bonds. The triangular lattice corresponds to the lattice structure of the (111) plane of an FCC crystal in the fine scale region. The Lennard-Jones potential is used to model the atom-atom interactions. The coupling between the coarse scale and fine scale is realized through ghost atoms. The ghost atom positions are interpolated from the coarse scale solution and enforced as boundary conditions on the fine scale. The fine scale region is adaptively refined and coarsened as the crack propagates. The centro symmetry parameter is used to detect the crack tip location. The method is implemented in two dimensions. The results are compared to pure atomistic simulations and show excellent agreement. (C) 2014 Elsevier B. V. All rights reserved.

High quality oxide-free metallic nanoparticles: a strategy for synthesis through laser ablation in aqueous medium

The paper explores the synthesis of oxide-free nanoparticles of Ag and Cu through laser ablation of pure targets under aqueous medium and tuning the quality and size through addition of Polyvinylpyrrolidone (PVP) in the medium. The size distribution of nanoparticles reduces from 37 +/- 30 nm and 13 +/- 5 nm to 32 +/- 12 nm and 4 +/- 1 nm for Ag and Cu with changes in PVP concentration from 0.00 to 0.02 M, respectively. Irregular shaped particles of Ag with Ag2O phase and a Cu-Cu2O core-shell particles form without the addition of PVP, while oxide layer is absent with 0.02 M of PVP. The recent understanding of the mechanism of particle formation during laser ablation under liquid medium allows us to rationalize our observation.

Adaptive evolution of a novel avian-origin influenza A/H7N9 virus

In China, the recent outbreak of novel influenza A/H7N9 virus has been assumed to be severe, and it may possibly turn brutal in the near future. In order to develop highly protective vaccines and drugs for the A/H7N9 virus, it is critical to find out the selection pressure of each amino acid site. In the present study, six different statistical methods consisting of four independent codon-based maximum likelihood (CML) methods, one hierarchical Bayesian (HB) method and one branch-site (BS) method, were employed to determine if each amino acid site of A/H7N9 virus is under natural selection pressure. Functions for both positively and negatively selected sites were inferred by annotating these sites with experimentally verified amino acid sites. Comprehensively, the single amino acid site 627 of PB2 protein was inferred as positively selected and it function was identified as a T-cell epitope (TCE). Among the 26 negatively selected amino acid sites of PB2, PB1, PA, HA, NP, NA, M1 and NS2 proteins, only 16 amino acid sites were identified to be involved in TCEs. In addition, 7 amino acid sites including, 608 and 609 of PA, 480 of NP, and 24, 25, 109 and 205 of M1, were identified to be involved in both B-cell epitopes (BCEs) and TCEs. Conversely, the function of positions 62 of PA, and, 43 and 113 of HA was unknown. In conclusion, the seven amino acid sites engaged in both BCEs and TCEs were identified as highly suitable targets, as these sites will be predicted to play a principal role in inducing strong humoral and cellular immune responses against A/H7N9 virus. (C) 2014 Elsevier Inc. All rights reserved.

Coordinate Hyperactivation of Notch1 and Ras/MAPK Pathways Correlates with Poor Patient Survival: Novel Therapeutic Strategy for Aggressive Breast Cancers

Aberrant activation of Notch and Ras pathways has been detected in breast cancers. A synergy between these two pathways has also been shown in breast cell transformation in culture. Yet, the clinical relevance of Notch-Ras cooperation in breast cancer progression remains unexplored. In this study, we show that coordinate hyperactivation of Notch1 and Ras/MAPK pathways in breast cancer patient specimens, as assessed by IHC for cleaved Notch1 and pErk1/2, respectively, correlated with early relapse to vital organs and poor overall survival. Interestingly, majority of such Notch1 (high)Erk(high) cases encompassed the highly aggressive triple-negative breast cancers (TNBC), and were enriched in stem cell markers. We further show that combinatorial inhibition of Notch1 and Ras/MAPK pathways, using a novel mAb against Notch1 and a MEK inhibitor, respectively, led to a significant reduction in proliferation and survival of breast cancer cells compared with individual inhibition. Combined inhibition also abrogated sphere-forming potential, and depleted the putative cancer stem-like cell subpopulation. Most importantly, combinatorial inhibition of Notch1 and Ras/MAPK pathways completely blocked tumor growth in a panel of breast cancer xenografts, including the TNBCs. Thus, our study identifies coordinate hyperactivation of Notch1 and Ras/MAPK pathways as novel biomarkers for poor breast cancer outcome. Furthermore, based on our preclinical data, we propose combinatorial targeting of these two pathways as a treatment strategy for highly aggressive breast cancers, particularly the TNBCs that currently lack any targeted therapeutic module. (C) 2014 AACR.

Strategy for Enhancing the Dielectric Constant of Organic Semiconductors Without Sacrificing Charge Carrier Mobility and Solubility

Current organic semiconductors for organic photovoltaics (OPV) have relative dielectric constants (relative permittivities, epsilon(r)) in the range of 2-4. As a consequence, Coulombically bound electron-hole pairs (excitons) are produced upon absorption of light, giving rise to limited power conversion efficiencies. We introduce a strategy to enhance epsilon(r) of well-known donors and acceptors without breaking conjugation, degrading charge carrier mobility or altering the transport gap. The ability of ethylene glycol (EG) repeating units to rapidly reorient their dipoles with the charge redistributions in the environment was proven via density functional theory (DFT) calculations. Fullerene derivatives functionalized with triethylene glycol side chains were studied for the enhancement of epsilon(r) together with poly(p-phenylene vinylene) and diketo-pyrrolopyrrole based polymers functionalized with similar side chains. The polymers showed a doubling of epsilon(r) with respect to their reference polymers in identical backbone. Fullerene derivatives presented enhancements up to 6 compared with phenyl-C-61-butyric acid methyl ester (PCBM) as the reference. Importantly, the applied modifications did not affect the mobility of electrons and holes and provided excellent solubility in common organic solvents.

Adaptive mesh generation for singularly perturbed fourth-order ordinary differential equations

In this paper, we consider a singularly perturbed boundary-value problem for fourth-order ordinary differential equation (ODE) whose highest-order derivative is multiplied by a small perturbation parameter. To solve this ODE, we transform the differential equation into a coupled system of two singularly perturbed ODEs. The classical central difference scheme is used to discretize the system of ODEs on a nonuniform mesh which is generated by equidistribution of a positive monitor function. We have shown that the proposed technique provides first-order accuracy independent of the perturbation parameter. Numerical experiments are provided to validate the theoretical results.

Breeding in bamboo: a novel anuran reproductive strategy discovered in Rhacophorid frogs of the Western Ghats, India

Amphibians exhibit extraordinarily diverse sets of reproductive strategies among vertebrates. Understanding life history strategies in an evolutionary framework is lacking for many amphibian species in the tropics. Here, we report a novel reproductive mode where adult frogs enter hollow internodes of bamboo via a small opening, deposit direct developing eggs, and provide parental care. This behaviour is observed in two species of the frog genus Raorchestes. The first description of this unique life history and details of nest site characteristics and embryo development are provided along with ecological comparisons. Evolution of novel reproductive modes and parental care are discussed in context of natural selection. Dearth of natural history information on amphibians in the Western Ghats and much of the South-East Asian region is highlighted with suggestions for further studies.(c) 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 114, 1-11.

Adaptive Flight-Control Design Using Neural-Network-Aided Optimal Nonlinear Dynamic Inversion

A neural-network-aided nonlinear dynamic inversion-based hybrid technique of model reference adaptive control flight-control system design is presented in this paper. Here, the gains of the nonlinear dynamic inversion-based flight-control system are dynamically selected in such a manner that the resulting controller mimics a single network, adaptive control, optimal nonlinear controller for state regulation. Traditional model reference adaptive control methods use a linearized reference model, and the presented control design method employs a nonlinear reference model to compute the nonlinear dynamic inversion gains. This innovation of designing the gain elements after synthesizing the single network adaptive controller maintains the advantages that an optimal controller offers, yet it retains a simple closed-form control expression in state feedback form, which can easily be modified for tracking problems without demanding any a priori knowledge of the reference signals. The strength of the technique is demonstrated by considering the longitudinal motion of a nonlinear aircraft system. An extended single network adaptive control/nonlinear dynamic inversion adaptive control design architecture is also presented, which adapts online to three failure conditions, namely, a thrust failure, an elevator failure, and an inaccuracy in the estimation of C-M alpha. Simulation results demonstrate that the presented adaptive flight controller generates a near-optimal response when compared to a traditional nonlinear dynamic inversion controller.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

A unique strategy towards high dielectric constant and low loss with multiwall carbon nanotubes anchored onto graphene oxide sheets

Multiwall carbon nanotubes (MWNTs) were anchored onto graphene oxide sheets (GOs) via diazonium and C-C coupling reactions and characterized by spectroscopic and electron microscopic techniques. The thus synthesized MWNT-GO hybrid was then melt mixed with 50/50 polyamide6-maleic anhydride-modified acrylonitrile-butadiene-styrene (PA6-mABS) blend to design materials with high dielectric constant (30) and low dielectric loss. The phase morphology was studied by SEM and it was observed that the MWNT-GO hybrid was selectively localized in the PA6 phase of the blend. The 30 scales with the concentration of MWNT-GO in the blends, which interestingly showed a very low dielectric loss (< 0.2) making them potential candidate for capacitors. In addition, the dynamic storage modulus scales with the fraction of MWNT-GO in the blends, demonstrating their reinforcing capability as well.

Adaptive executions of hyperbolic block-structured AMR applications on GPU systems

A block-structured adaptive mesh refinement (AMR) technique has been used to obtain numerical solutions for many scientific applications. Some block-structured AMR approaches have focused on forming patches of non-uniform sizes where the size of a patch can be tuned to the geometry of a region of interest. In this paper, we develop strategies for adaptive execution of block-structured AMR applications on GPUs, for hyperbolic directionally split solvers. While effective hybrid execution strategies exist for applications with uniform patches, our work considers efficient execution of non-uniform patches with different workloads. Our techniques include bin-packing work units to load balance GPU computations, adaptive asynchronism between CPU and GPU executions using a knapsack formulation, and scheduling communications for multi-GPU executions. Our experiments with synthetic and real data, for single-GPU and multi-GPU executions, on Tesla S1070 and Fermi C2070 clusters, show that our strategies result in up to a 3.23 speedup in performance over existing strategies.

Adaptive Pulse Width Control and Sampling for Low Power Pulse Oximetry

Remote sensing of physiological parameters could be a cost effective approach to improving health care, and low-power sensors are essential for remote sensing because these sensors are often energy constrained. This paper presents a power optimized photoplethysmographic sensor interface to sense arterial oxygen saturation, a technique to dynamically trade off SNR for power during sensor operation, and a simple algorithm to choose when to acquire samples in photoplethysmography. A prototype of the proposed pulse oximeter built using commercial-off-the-shelf (COTS) components is tested on 10 adults. The dynamic adaptation techniques described reduce power consumption considerably compared to our reference implementation, and our approach is competitive to state-of-the-art implementations. The techniques presented in this paper may be applied to low-power sensor interface designs where acquiring samples is expensive in terms of power as epitomized by pulse oximetry.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

Sulfenyiation of beta-Diketones Using C-H Functionalization Strategy

Sulfenylation of beta-diketones is challenging as beta-diketones undergo deacylation after sulfenylation in the reaction medium. The sulfenylation of beta-diketones without deacylation under metal-free conditions at ambient temperature via a cross dehydrogenative coupling (CDC) strategy is reported. The resultant products can be further manipulated to form alpha,alpha-disubstituted beta-diketones and pyrazoles.

Strategy for Obtaining Bimodal Bubble Size Distribution in Water Blown Polyurethane Foams

Polyurethane foams with multimodal cell distribution exhibit superior mechanical and thermal properties. A technique for generating bimodal bubble size distribution exists in the literature, but it uses supercritical conditions. In the present work, an alternative based on milder operating conditions is proposed. It is a modification of reaction injection molding (RIM), using reactants already seeded with bubbles. The number density of the seeds determines if two nucleating events can occur. A bimodal bubble size distribution is obtained when this happens A mathematical model is used to test this hypothesis by simulating water blown free rise polyurethane foams. The effects of initial concentration of bubbles, temperature of the reactants, and the weight fraction of water are studied. The study reveals that for certain concentrations of initial number of bubbles, when initial temperature and weight fraction of water are high, it is possible to obtain a second nucleation event, leading to bimodal bubble size distribution.