Damage limit states of reinforced concrete beams subjected to incremental cyclic loading using relaxation ratio analysis of AE parameters

This paper presents an experimental study on damage assessment of reinforced concrete (RC) beams subjected to incremental cyclic loading. During testing acoustic emissions (AEs) were recorded. The analysis of the AE released was carried out by using parameters relaxation ratio, load ratio and calm ratio. Digital image correlation (DIC) technique and tracking with available MATLAB program were used to measure the displacement and surface strains in concrete. Earlier researchers classified the damage in RC beams using Kaiser effect, crack mouth opening displacement and proposed a standard. In general (or in practical situations), multiple cracks occur in reinforced concrete beams. In the present study damage assessment in RC beams was studied according to different limit states specified by the code of practice IS-456:2000 and AE technique. Based on the two ratios namely load ratio and calm ratio and when the deflection reached approximately 85% of the maximum allowable deflection it was observed that the RC beams were heavily damaged. The combination of AE and DIC techniques has the potential to provide the state of damage in RC structures.

125 GeV Higgs state in the context of four generations with two Higgs doublets

We interpret the recent discovery of a 125 GeV Higgs-like state in the context of a two-Higgs-doublet model with a heavy fourth sequential generation of fermions, in which one Higgs doublet couples only to the fourth-generation fermions, while the second doublet couples to the lighter fermions of the first three families. This model is designed to accommodate the apparent heaviness of the fourth-generation fermions and to effectively address the low-energy phenomenology of a dynamical electroweak-symmetry-breaking scenario. The physical Higgs states of the model are, therefore, viewed as composites primarily of the fourth-generation fermions. We find that the lightest Higgs, h, is a good candidate for the recently discovered 125 GeV spin-zero particle, when tan beta similar to O(1), for typical fourth-generation fermion masses of M-4G = 400-600 GeV, and with a large t-t' mixing in the right-handed quark sector. This, in turn, leads to BR(t' -> th) similar to O(1), which drastically changes the t' decay pattern. We also find that, based on the current Higgs data, this two-Higgs-doublet model generically predicts an enhanced production rate (compared to the Standard Model) in the pp -> h -> tau tau channel, and reduced rates in the VV -> h -> gamma gamma and p (p) over bar /pp -> V -> hV -> Vbb channels. Finally, the heavier CP-even Higgs is excluded by the current data up to m(H) similar to 500 GeV, while the pseudoscalar state, A, can be as light as 130 GeV. These heavier Higgs states and the expected deviations from the Standard Model din some of the Higgs production channels can be further excluded or discovered with more data.

MPI-based parallel synchronous vector evaluated particle swarm optimization for multi-objective design optimization of composite structures

This paper presents a decentralized/peer-to-peer architecture-based parallel version of the vector evaluated particle swarm optimization (VEPSO) algorithm for multi-objective design optimization of laminated composite plates using message passing interface (MPI). The design optimization of laminated composite plates being a combinatorially explosive constrained non-linear optimization problem (CNOP), with many design variables and a vast solution space, warrants the use of non-parametric and heuristic optimization algorithms like PSO. Optimization requires minimizing both the weight and cost of these composite plates, simultaneously, which renders the problem multi-objective. Hence VEPSO, a multi-objective variant of the PSO algorithm, is used. Despite the use of such a heuristic, the application problem, being computationally intensive, suffers from long execution times due to sequential computation. Hence, a parallel version of the PSO algorithm for the problem has been developed to run on several nodes of an IBM P720 cluster. The proposed parallel algorithm, using MPI's collective communication directives, establishes a peer-to-peer relationship between the constituent parallel processes, deviating from the more common master-slave approach, in achieving reduction of computation time by factor of up to 10. Finally we show the effectiveness of the proposed parallel algorithm by comparing it with a serial implementation of VEPSO and a parallel implementation of the vector evaluated genetic algorithm (VEGA) for the same design problem. (c) 2012 Elsevier Ltd. All rights reserved.

Indentation size effect and shear transformation zone size in a bulk metallic glass in two different structural states

The existence of an indentation size effect (ISE) in the onset of yield in a Zr-based bulk metallic glass (BMG) is investigated by employing spherical-tip nanoindentation experiments. Statistically significant data on the load at which the first pop-in in the displacement occurs were obtained for three different tip radii and in two different structural states (as-cast and structurally relaxed) of the BMG. Hertzian contact mechanics were employed to convert the pop-in loads to the maximum shear stress underneath the indenter. Results establish the existence of an ISE in the BMG of both structural states, with shear yield stress increasing with decreasing tip radius. Structural relaxation was found to increase the yield stress and decrease the variability in the data, indicating ``structural homogenization'' with annealing. Statistical analysis of the data was employed to estimate the shear transformation zone (STZ) size. Results of this analysis indicate an STZ size of similar to 25 atoms, which increases to similar to 34 atoms upon annealing. These observations are discussed in terms of internal structure changes that occur during structural relaxation and their interaction with the stressed volumes in spherical indentation of a metallic glass. (C) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Directional grain growth from anisotropic kinetic roughening of grain boundaries in sheared colloidal crystals

The fabrication of functional materials via grain growth engineering implicitly relies on altering the mobilities of grain boundaries (GBs) by applying external fields. Although computer simulations have alluded to kinetic roughening as a potential mechanism for modifying GB mobilities, its implications for grain growth have remained largely unexplored owing to difficulties in bridging the widely separated length and time scales. Here, by imaging GB particle dynamics as well as grain network evolution under shear, we present direct evidence for kinetic roughening of GBs and unravel its connection to grain growth in driven colloidal polycrystals. The capillary fluctuation method allows us to quantitatively extract shear-dependent effective mobilities. Remarkably, our experiments reveal that for sufficiently large strains, GBs with normals parallel to shear undergo preferential kinetic roughening, resulting in anisotropic enhancement of effective mobilities and hence directional grain growth. Single-particle level analysis shows that the mobility anisotropy emerges from strain-induced directional enhancement of activated particle hops normal to the GB plane. We expect our results to influence materials fabrication strategies for atomic and block copolymeric polycrystals as well.

Application of Artificial Neural Networks and Particle Swarm Optimization for the Management of Groundwater Resources

Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. In this study, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) models were developed and coupled for the management of groundwater of Dore river basin in France. The Analytic Element Method (AEM) based flow model was developed and used to generate the dataset for the training and testing of the ANN model. This developed ANN-PSO model was applied to minimize the pumping cost of the wells, including cost of the pipe line. The discharge and location of the pumping wells were taken as the decision variable and the ANN-PSO model was applied to find out the optimal location of the wells. The results of the ANN-PSO model are found similar to the results obtained by AEM-PSO model. The results show that the ANN model can reduce the computational burden significantly as it is able to analyze different scenarios, and the ANN-PSO model is capable of identifying the optimal location of wells efficiently.

Smoothed functional and Quasi-Newton algorithms for routing in multi-stage queueing network with constraints

We consider the problem of optimal routing in a multi-stage network of queues with constraints on queue lengths. We develop three algorithms for probabilistic routing for this problem using only the total end-to-end delays. These algorithms use the smoothed functional (SF) approach to optimize the routing probabilities. In our model all the queues are assumed to have constraints on the average queue length. We also propose a novel quasi-Newton based SF algorithm. Policies like Join Shortest Queue or Least Work Left work only for unconstrained routing. Besides assuming knowledge of the queue length at all the queues. If the only information available is the expected end-to-end delay as with our case such policies cannot be used. We also give simulation results showing the performance of the SF algorithms for this problem.

Monoclonal Antibodies against Hepatitis C Genotype 3a Virus Like Particle Inhibit Virus Entry in Cell Culture System

The envelope protein (E1-E2) of Hepatitis C virus (HCV) is a major component of the viral structure. The glycosylated envelope protein is considered to be important for initiation of infection by binding to cellular receptor(s) and also known as one of the major antigenic targets to host immune response. The present study was aimed at identifying mouse monoclonal antibodies which inhibit binding of virus like particles of HCV to target cells. The first step in this direction was to generate recombinant HCV-like particles (HCV-LPs) specific for genotypes 3a of HCV (prevalent in India) using the genes encoding core, E1 and E2 envelop proteins in a baculovirus expression system. The purified HCV-LPs were characterized by ELISA and electron microscopy and were used to generate monoclonal antibodies (mAbs) in mice. Two monoclonal antibodies (E8G9 and H1H10) specific for the E2 region of envelope protein of HCV genotype 3a, were found to reduce the virus binding to Huh7 cells. However, the mAbs generated against HCV genotype 1b (D2H3, G2C7, E1B11) were not so effective. More importantly, mAb E8G9 showed significant inhibition of the virus entry in HCV JFH1 cell culture system. Finally, the epitopic regions on E2 protein which bind to the mAbs have also been identified. Results suggest a new therapeutic strategy and provide the proof of concept that mAb against HCV-LP could be effective in preventing virus entry into liver cells to block HCV replication.

Asymptotics of the invariant measure in mean field models with jumps

We consider the asymptotics of the invariant measure for the process of spatial distribution of N coupled Markov chains in the limit of a large number of chains. Each chain reflects the stochastic evolution of one particle. The chains are coupled through the dependence of transition rates on the spatial distribution of particles in the various states. Our model is a caricature for medium access interactions in wireless local area networks. Our model is also applicable in the study of spread of epidemics in a network. The limiting process satisfies a deterministic ordinary differential equation called the McKean-Vlasov equation. When this differential equation has a unique globally asymptotically stable equilibrium, the spatial distribution converges weakly to this equilibrium. Using a control-theoretic approach, we examine the question of a large deviation from this equilibrium.

Packing in molten globules and native states

Close packing of hydrophobic residues in the protein interior is an important determinant of protein stability. Cavities introduced by large to small substitutions are known to destabilize proteins. Conversely, native states of proteins and protein fragments can be stabilized by filling in existing cavities. Molten globules (MGs) were initially used to describe a state of protein which has well-defined secondary structure but little or no tertiary packing. Subsequent studies have shown that MGs do have some degree of native-like topology and specific packing. Wet molten globules (WMGs) with hydrated cores and considerably decreased packing relative to the native state have been studied extensively. Recently there has been renewed interest in identification and characterization of dry molten globules (DMGs). These are slightly expanded forms of the native state which show increased conformational flexibility, native-like main-chain hydrogen bonding and dry interiors. The generality of occurrence of DMGs during protein unfolding and the extent and nature of packing in DMGs remain to be elucidated. Packing interactions in native proteins and MGs can be probed through mutations. Next generation sequencing technologies make it possible to determine relative populations of mutants in a large pool. When this is coupled to phenotypic screens or cell-surface display, it becomes possible to rapidly examine large panels of single-site or multi-site mutants. From such studies, residue specific contributions to protein stability and function can be estimated in a highly parallelized fashion. This complements conventional biophysical methods for characterization of packing in native states and molten globules.

Motion segmentation using curve fitting on Lagrangian particle trajectories

In this paper we present a segmentation algorithm to extract foreground object motion in a moving camera scenario without any preprocessing step such as tracking selected features, video alignment, or foreground segmentation. By viewing it as a curve fitting problem on advected particle trajectories, we use RANSAC to find the polynomial that best fits the camera motion and identify all trajectories that correspond to the camera motion. The remaining trajectories are those due to the foreground motion. By using the superposition principle, we subtract the motion due to camera from foreground trajectories and obtain the true object-induced trajectories. We show that our method performs on par with state-of-the-art technique, with an execution time speed-up of 10x-40x. We compare the results on real-world datasets such as UCF-ARG, UCF Sports and Liris-HARL. We further show that it can be used toper-form video alignment.

Electronic energy transfer between long-range resonance states of 3-mercaptopropionic acid capped CdTe quantum dots in aqueous media

We demonstrate electronic energy transfer between resonance states of 2 and 2.8 nm CdTe quantum dots in aqueous media using steady-state photoluminescence spectroscopy without using any external linker molecule. With increasing concentration of larger dots, there is subsequent quenching of luminescence in smaller dots accompanied by the enhancement of luminescence in larger dots. Our experimental evidence suggests that there is long-range resonance energy transfer among electronic excitations, specifically from the electronically confined states of the smaller dots to the higher excited states of the larger dots.

Tunability of electronic states in ultrathin gold nanowires

The electronic state in ultrathin gold nanowires is tuned by careful engineering of the device architecture via a chemical methodology. The electrons are localized to an insulating state (showing variable range hopping transport) by simply bringing them close to the substrate, while the insertion of an interlayer leads to a Tomonaga Luttinger liquid state.

Determination of favorable inter-particle interactions for formation of substitutionally ordered solid phases from a binary mixture of oppositely charged colloidal suspensions

The solid phase formed by a binary mixture of oppositely charged colloidal particles can be either substitutionally ordered or substitutionally disordered depending on the nature and strength of interactions among the particles. In this work, we use Monte Carlo molecular simulations along with the Gibbs-Duhem integration technique to map out the favorable inter-particle interactions for the formation of substitutionally ordered crystalline phases from a fluid phase. The inter-particle interactions are modeled using the hard core Yukawa potential but the method can be easily extended to other systems of interest. The study obtains a map of interactions depicting regions indicating the type of the crystalline aggregate that forms upon phase transition.