Analysis of shear bands in slow granular flows using a frictional Cosserat model

The slow flow of granular materials is often marked by the existence of narrow shear layers, adjacent to large regions that suffer little or no deformation. This behaviour, in the regime where shear stress is generated primarily by the frictional interactions between grains, has so far eluded theoretical description. In this paper, we present a rigid-plastic frictional Cosserat model that captures thin shear layers by incorporating a microscopic length scale. We treat the granular medium as a Cosserat continuum, which allows the existence of localised couple stresses and, therefore, the possibility of an asymmetric stress tensor. In addition, the local rotation is an independent field variable and is not necessarily equal to the vorticity. The angular momentum balance, which is implicitly satisfied for a classical continuum, must now be solved in conjunction with the linear momentum balances. We extend the critical state model, used in soil plasticity, for a Cosserat continuum and obtain predictions for flow in plane and cylindrical Couette devices. The velocity profile predicted by our model is in qualitative agreement with available experimental data. In addition, our model can predict scaling laws for the shear layer thickness as a function of the Couette gap, which must be verified in future experiments. Most significantly, our model can determine the velocity field in viscometric flows, which classical plasticity-based model cannot.

Model of resistances in systems of Tomonaga-Luttinger liquid wires

In a recent paper, we combined the technique of bosonization with the concept of a Rayleigh dissipation function to develop a model for resistances in one-dimensional systems of interacting spinless electrons Europhys. Lett. 93, 57007 (2011)]. We also studied the conductance of a system of three wires by using a current splitting matrix M at the junction. In this paper, we extend our earlier work in several ways. The power dissipated in a three-wire system is calculated as a function of M and the voltages applied in the leads. By combining two junctions of three wires, we examine a system consisting of two parallel resistances. We study the conductance of this system as a function of the M matrices and the two resistances; we find that the total resistance is generally quite different from what one expects for a classical system of parallel resistances. We do a sum over paths to compute the conductance of this system when one of the two resistances is taken to be infinitely large. We study the conductance of a three-wire system of interacting spin-1/2 electrons, and show that the charge and spin conductances can generally be different from each other. Finally, we consider a system of two wires that are coupled by a dissipation function, and we show that this leads to a current in one wire when a voltage bias is applied across the other wire.

Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedicated Environments

Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active area of research for several years. The existing curve fitting strategies for performance modeling utilize data from experiments that are conducted under uniform loading conditions. Hence the accuracy of these models degrade when the load conditions on the machines and network change. In this paper, we analyze a curve fitting model that attempts to predict execution times for any load conditions that may exist on the systems during application execution. Based on the experiments conducted with the model for a parallel eigenvalue problem, we propose a multi-dimensional curve-fitting model based on rational polynomials for performance predictions of parallel applications in non-dedicated environments. We used the rational polynomial based model to predict execution times for 2 other parallel applications on systems with large load dynamics. In all the cases, the model gave good predictions of execution times with average percentage prediction errors of less than 20%

Characterization of structural and free energy properties of promoters associated with Primary and Operon TSS in Helicobacter pylori genome and their orthologs

Promoter regions in the genomes of all domains of life show similar trends in several structural properties such as stability, bendability, curvature, etc. In current study we analysed the stability and bendability of various classes of promoter regions (based on the recent identification of different classes of transcription start sites) of Helicobacter pylori 26695 strain. It is found that primary TSS and operon-associated TSS promoters show significantly strong features in their promoter regions. DNA free-energy-based promoter prediction tool PromPredict was used to annotate promoters of different classes, and very high recall values (similar to 80%) are obtained for primary TSS. Orthologous genes from other strains of H. pylori show conservation of structural properties in promoter regions as well as coding regions. PromPredict annotates promoters of orthologous genes with very high recall and precision.

A finite population model of mlecular evolution: theory and computation

This article is concerned with the evolution of haploid organisms that reproduce asexually. In a seminal piece of work, Eigen and coauthors proposed the quasispecies model in an attempt to understand such an evolutionary process. Their work has impacted antiviral treatment and vaccine design strategies. Yet, predictions of the quasispecies model are at best viewed as a guideline, primarily because it assumes an infinite population size, whereas realistic population sizes can be quite small. In this paper we consider a population genetics-based model aimed at understanding the evolution of such organisms with finite population sizes and present a rigorous study of the convergence and computational issues that arise therein. Our first result is structural and shows that, at any time during the evolution, as the population size tends to infinity, the distribution of genomes predicted by our model converges to that predicted by the quasispecies model. This justifies the continued use of the quasispecies model to derive guidelines for intervention. While the stationary state in the quasispecies model is readily obtained, due to the explosion of the state space in our model, exact computations are prohibitive. Our second set of results are computational in nature and address this issue. We derive conditions on the parameters of evolution under which our stochastic model mixes rapidly. Further, for a class of widely used fitness landscapes we give a fast deterministic algorithm which computes the stationary distribution of our model. These computational tools are expected to serve as a framework for the modeling of strategies for the deployment of mutagenic drugs.

Model independent bounds on the modulus of the pion form factor on the unitarity cut below the omega pi threshold

We calculate upper and lower bounds on the modulus of the pion electromagnetic form factor on the unitarity cut below the omega pi inelastic threshold, using as input the phase in the elastic region known via the Fermi-Watson theorem from the pi pi P-wave phase shift, and a suitably weighted integral of the modulus squared above the inelastic threshold. The normalization at t = 0, the pion charge radius and experimental values at spacelike momenta are used as additional input information. The bounds are model independent, in the sense that they do not rely on specific parametrizations and do not require assumptions on the phase of the form factor above the inelastic threshold. The results provide nontrivial consistency checks on the recent experimental data on the modulus available below the omega pi threshold from e(+)e(-) annihilation and tau-decay experiments. In particular, at low energies the calculated bounds offer a more precise description of the modulus than the experimental data.

The evolution of complexity in social organization-A model using dominance-subordinate behavior in two social wasp species

Dominance and subordinate behaviors are important ingredients in the social organizations of group living animals. Behavioral observations on the two eusocial species Ropalidia marginata and Ropalidia cyathiformis suggest varying complexities in their social systems. The queen of R. cyathiformis is an aggressive individual who usually holds the top position in the dominance hierarchy although she does not necessarily show the maximum number of acts of dominance, while the R. marginata queen rarely shows aggression and usually does not hold the top position in the dominance hierarchy of her colony. In R. marginata, more workers are involved in dominance-subordinate interactions as compared to R. cyathiformis. These differences are reflected in the distribution of dominance-subordinate interactions among the hierarchically ranked individuals in both the species. The percentage of dominance interactions decreases gradually with hierarchical ranks in R. marginata while in R. cyathiformis it first increases and then decreases. We use an agent-based model to investigate the underlying mechanism that could give rise to the observed patterns for both the species. The model assumes, besides some non-interacting individuals, the interaction probabilities of the agents depend on their pre-differentiated winning abilities. Our simulations show that if the queen takes up a strategy of being involved in a moderate number of dominance interactions, one could get the pattern similar to R. cyathiformis, while taking up the strategy of very low interactions by the queen could lead to the pattern of R. marginata. We infer that both the species follow a common interaction pattern, while the differences in their social organization are due to the slight changes in queen as well as worker strategies. These changes in strategies are expected to accompany the evolution of more complex societies from simpler ones.

Group testing based spectrum hole search using a simple sub-nyquist sampling scheme

In this paper, we consider the problem of finding a spectrum hole of a specified bandwidth in a given wide band of interest. We propose a new, simple and easily implementable sub-Nyquist sampling scheme for signal acquisition and a spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy in the frequency domain by testing a group of adjacent subbands in a single test. The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent sub-bands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes. We extend this framework to a multi-stage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including non-contiguous spectrum hole search. Further, we provide the analytical means to optimize the hypothesis tests with respect to the detection thresholds, number of samples and group size to minimize the detection delay under a given error rate constraint. Depending on the sparsity and SNR, the proposed algorithms can lead to significantly lower detection delays compared to a conventional bin-by-bin energy detection scheme; the latter is in fact a special case of the group test when the group size is set to 1. We validate our analytical results via Monte Carlo simulations.

Effect of Input Source Energy on SASW Evaluation of Cement Concrete Pavement

A series of spectral analyses of surface waves (SASW) tests were conducted on a cement concrete pavement by dropping steel balls of four different values of diameter (D) varying between 25.4 and 76.2 mm. These tests were performed (1) by using different combinations of source to nearest receiver distance (S) and receiver spacing (X), and (2) for two different heights (H) of fall, namely, 0.25 and 0.50 m. The values of the maximum wavelength (lambda(max)) and minimum wavelength (lambda(min)) associated with the combined dispersion curve, corresponding to a particular combination of D and H, were noted to increase almost linearly with an increase in the magnitude of the input source energy (E). A continuous increase in strength and duration of the signals was noted to occur with an increase in the magnitude of D. Based on statistical analysis, two regression equations have been proposed to determine lambda(max) and lambda(min) for different values of source energy. It is concluded that the SASW technique is capable of producing nearly a unique dispersion curve irrespective of (1) diameters and heights of fall of the dropping masses used for producing the vibration, and (2) the spacing between different receivers. The results presented in this paper can be used to provide guidelines for deciding about the input source energy based on the required exploration zone of the pavement. (C) 2014 American Society of Civil Engineers.

Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data

Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of 2 degrees C than MODIS with an error of 3 degrees C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 degrees C & for MODIS data is 3.7 degrees C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect. (C) 2013 Elsevier Ltd. All rights reserved.

Effects of Interface Treatment on the Fatigue Behavior of Shape Memory Alloy Reinforced Polymer Composites

Interfacial properties of Shape Memory Alloy (SMA) reinforced polymer matrix composites can be enhanced by improving the interfacial bonding. This paper focuses on studying the interfacial stresses developed in the SMA-epoxy interface due to various laser shot penning conditions. Fiber-pull test-setup is designed to understand the role of mechanical bias stress cycling and thermal actuation cycling. Phase transformation is tracked over mechanical and thermal fatigue cycles. A micromechanics based model developed earlier based on shear lag in SMA and energy based consistent homogenization is extended here to incorporate the stress-temperature phase diagram parameters for modeling fatigue.

High-Performance Sensors Based on Resistance Fluctuations of Single-Layer-Graphene Transistors

One of the most interesting predicted applications of graphenemonolayer-based devices is as high-quality sensors. In this article, we show, through systematic experiments, a chemical vapor sensor based on the measurement of lowfrequency resistance fluctuations of single-layer-graphene field-effect-transistor devices. The sensor has extremely high sensitivity, very high specificity, high fidelity, and fast response times. The performance of the device using this scheme of measurement (which uses resistance fluctuations as the detection parameter) is more than 2 orders of magnitude better than a detection scheme in which changes in the average value of the resistance is monitored. We propose a number-densityfluctuation-based model to explain the superior characteristics of a noisemeasurement-based detection scheme presented in this article.

Near-Optimal Detection Thresholds for Bayesian Spectrum Sensing Under Fading

This paper considers the problem of energy-based, Bayesian spectrum sensing in cognitive radios under various fading environments. Under the well-known central limit theorem based model for energy detection, we derive analytically tractable expressions for near-optimal detection thresholds that minimize the probability of error under lognormal, Nakagami-m, and Weibull fading. For the Suzuki fading case, a generalized gamma approximation is provided, which saves on the computation of an integral. In each case, the accuracy of the theoretical expressions as compared to the optimal thresholds are illustrated through simulations.

Ultrasonic Guided Wave Based Damage Detection Using Low-dimensional Data from Laser Doppler Scan

In the current state of the art, it remains an open problem to detect damage with partial ultrasonic scan data and with measurements at coarser spatial scale when the location of damage is not known. In the present paper, a recent development of finite element based model reduction scheme in frequency domain that employs master degrees of freedom covering the surface scan region of interests is reported in context of non-contact ultrasonic guided wave based inspection. The surface scan region of interest is grouped into master and slave degrees of freedom. A finite element wise damage factor is derived which represents damage state over distributed areas or sharp condition of inter-element boundaries (for crack). Laser Doppler Vibrometer (LDV) scan data obtained from plate type structure with inaccessible surface line crack are considered along with the developed reduced order damage model to analyze the extent of scan data dimensional reduction. The proposed technique has useful application in problems where non-contact monitoring of complex structural parts are extremely important and at the same time LDV scan has to be done on accessible surfaces only.