Relation between the work function and Young's modulus of RhSi and estimate of Schottky-barrier height at RhSi/Si interface: An ab-initio study

Density-functional calculations are performed to explore the relationship between the work function and Young's modulus of RhSi, and to estimate the p-Schottky-barrier height (SBH) at the Si/RhSi(010) interface. It is shown that the Young's modulus and the workfunction of RhSi satisfy the generic sextic relation, proposed recently for elemental metals. The calculated p-SBH at the Si/RhSi interface is found to differ only by 0.04 eV in opposite limits, viz., no-pinning and strong pinning. We find that the p-SBH is reduced as much as by 0.28 eV due to vacancies at the interface. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4761994]

Serodiagnosis of Tuberculosis in Asian Elephants (Elephas maximus) in Southern India: A Latent Class Analysis

Background: Mycobacterium tuberculosis, a causative agent of chronic tuberculosis disease, is widespread among some animal species too. There is paucity of information on the distribution, prevalence and true disease status of tuberculosis in Asian elephants (Elephas maximus). The aim of this study was to estimate the sensitivity and specificity of serological tests to diagnose M. tuberculosis infection in captive elephants in southern India while simultaneously estimating sero-prevalence. Methodology/Principal Findings: Health assessment of 600 elephants was carried out and their sera screened with a commercially available rapid serum test. Trunk wash culture of select rapid serum test positive animals yielded no animal positive for M. tuberculosis isolation. Under Indian field conditions where the true disease status is unknown, we used a latent class model to estimate the diagnostic characteristics of an existing (rapid serum test) and new (four in-house ELISA) tests. One hundred and seventy nine sera were randomly selected for screening in the five tests. Diagnostic sensitivities of the four ELISAs were 91.3-97.6% (95% Credible Interval (CI): 74.8-99.9) and diagnostic specificity were 89.6-98.5% (95% CI: 79.4-99.9) based on the model we assumed. We estimate that 53.6% (95% CI: 44.6-62.8) of the samples tested were free from infection with M. tuberculosis and 15.9% (97.5% CI: 9.8 - to 24.0) tested positive on all five tests. Conclusions/Significance: Our results provide evidence for high prevalence of asymptomatic M. tuberculosis infection in Asian elephants in a captive Indian setting. Further validation of these tests would be important in formulating area-specific effective surveillance and control measures.

A UNIFIED APPROACH FOR OPTIMIZATION OF SNAKUSCULES AND OVUSCULES

Automated image segmentation techniques are useful tools in biological image analysis and are an essential step in tracking applications. Typically, snakes or active contours are used for segmentation and they evolve under the influence of certain internal and external forces. Recently, a new class of shape-specific active contours have been introduced, which are known as Snakuscules and Ovuscules. These contours are based on a pair of concentric circles and ellipses as the shape templates, and the optimization is carried out by maximizing a contrast function between the outer and inner templates. In this paper, we present a unified approach to the formulation and optimization of Snakuscules and Ovuscules by considering a specific form of affine transformations acting on a pair of concentric circles. We show how the parameters of the affine transformation may be optimized for, to generate either Snakuscules or Ovuscules. Our approach allows for a unified formulation and relies only on generic regularization terms and not shape-specific regularization functions. We show how the calculations of the partial derivatives may be made efficient thanks to the Green's theorem. Results on synthesized as well as real data are presented.

Spectral moment sum rules for the retarded Green's function and self-energy of the inhomogeneous Bose-Hubbard model in equilibrium and nonequilibrium

We derive exact expressions for the zeroth and the first three spectral moment sum rules for the retarded Green's function and for the zeroth and the first spectral moment sum rules for the retarded self-energy of the inhomogeneous Bose-Hubbard model in nonequilibrium, when the local on-site repulsion and the chemical potential are time-dependent, and in the presence of an external time-dependent electromagnetic field. We also evaluate these expressions for the homogeneous case in equilibrium, where all time dependence and external fields vanish. Unlike similar sum rules for the Fermi-Hubbard model, in the Bose-Hubbard model case, the sum rules often depend on expectation values that cannot be determined simply from parameters in the Hamiltonian like the interaction strength and chemical potential but require knowledge of equal-time many-body expectation values from some other source. We show how one can approximately evaluate these expectation values for the Mott-insulating phase in a systematic strong-coupling expansion in powers of the hopping divided by the interaction. We compare the exact moment relations to the calculated moments of spectral functions determined from a variety of different numerical approximations and use them to benchmark their accuracy. DOI: 10.1103/PhysRevA.87.013628

Toll-Like Receptors 7, 8, and 9 Expression and Function in Primary Human Cervical Cancer Langerhans Cells Evidence of Anergy

Objective: Human papillomavirus oncoproteins E6 and E7 down modulate Toll-like receptor (TLR) 9 expression in infected keratinocytes. We explored the status of expression and function of TLR7, TLR8, and TLR9 in primary human Langerhans cells (LCs) isolated from cervical tumors. Methodology: Single-cell suspensions were made from fresh tissues of squamous cell carcinoma (International Federation of Gynecology and Obstetrics stage IB2); myeloid dendritic cells were purified using CD1c magnetic activated cell separation kits. Langerhans cells were further flow sorted into CD1a(+)CD207(+) cells. Acute monocytic leukemia cell line THP-1-derived LCs (moLCs) formed the controls. mRNA from flow-sorted LCs was reverse transcribed to cDNA and TLR7, TLR8, and TLR9 amplified. Monocyte-derived Langerhans cells and cervical tumor LCs were stimulated with TLR7, TLR8, and TLR9 ligands. Culture supernatants were assayed for interleukin (IL) 1 beta, IL-6, IL-10, IL-12p70, interferon (IFN) alpha, interferon gamma, and tumor necrosis factor (TNF) alpha by Luminex multiplex bead array. Human papillomavirus was genotyped. Results: We have for the first time demonstrated that the acute monocytic leukemia cell line THP-1 can be differentiated into LCs in vitro. Although these moLCs. expressed all the 3 TLRs, tumor LCs expressed TLR7 and TLR8, but uniformly lacked TLR9. Also, moLCs secreted IL-6, IL-1 beta, and tumor necrosis factor alpha to TLR8 ligand and interferon alpha in response to TLR9 ligand; in contrast, tumor LCs did not express any cytokine to any of the 3 TLR ligands. Human papillomavirus type 16 was one of the common human papillomavirus types in all cases. Conclusions: Cervical tumor LCs lacked TLR9 expression and were functionally anergic to all the 3: TLR7, TLR8, and TLR9 ligands, which may play a crucial role in immune tolerance. The exact location of block(s) in TLR7 and TLR8 signaling needs to be investigated, which would have important immunotherapeutic implications.

Performance of a class of multi-robot deploy and search strategies based on centroidal voronoi configurations

This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits.

Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset

In the design of practical web page classification systems one often encounters a situation in which the labeled training set is created by choosing some examples from each class; but, the class proportions in this set are not the same as those in the test distribution to which the classifier will be actually applied. The problem is made worse when the amount of training data is also small. In this paper we explore and adapt binary SVM methods that make use of unlabeled data from the test distribution, viz., Transductive SVMs (TSVMs) and expectation regularization/constraint (ER/EC) methods to deal with this situation. We empirically show that when the labeled training data is small, TSVM designed using the class ratio tuned by minimizing the loss on the labeled set yields the best performance; its performance is good even when the deviation between the class ratios of the labeled training set and the test set is quite large. When the labeled training data is sufficiently large, an unsupervised Gaussian mixture model can be used to get a very good estimate of the class ratio in the test set; also, when this estimate is used, both TSVM and EC/ER give their best possible performance, with TSVM coming out superior. The ideas in the paper can be easily extended to multi-class SVMs and MaxEnt models.

Point Spread Function Engineering for Super-Resolution Single-Photon and Multiphoton Fluorescence Microscopy

Super-resolution imaging techniques are of paramount interest for applications in bioimaging and fluorescence microscopy. Recent advances in bioimaging demand application-tailored point spread functions. Here, we present some approaches for generating application-tailored point spread functions along with fast imaging capabilities. Aperture engineering techniques provide interesting solutions for obtaining desired system point spread functions. Specially designed spatial filters—realized by optical mask—are outlined both in a single-lens and 4Pi configuration. Applications include depth imaging, multifocal imaging, and super-resolution imaging. Such an approach is suitable for fruitful integration with most existing state-of-art imaging microscopy modalities.

Fish inspired biomimetic ionic polymer metal composite pectoral fins using labriform propulsion

Ionic polymer metal composites (IPMC) are a new class of smart materials that have attractive characteristics such as muscle like softness, low voltage and power consumption, and good performance in aqueous environments. Thus, IPMC’s provide promising application for biomimetic fish like propulsion systems. In this paper, we design and analyze IPMC underwater propulsor inspired from swimming of Labriform fishes. Different fish species in nature are source of inspiration for different biomimetic flapping IPMC fin design. Here, three fish species with high performance flapping pectoral fin locomotion is chosen and performance analysis of each fin design is done to discover the better configurations for engineering applications. In order to describe the behavior of an active IPMC fin actuator in water, a complex hydrodynamic function is used and structural model of the IPMC fin is obtained by modifying the classical dynamic equation for a slender beam. A quasi-steady blade element model that accounts for unsteady phenomena such as added mass effects, dynamic stall, and the cumulative Wagner effect is used to estimate the hydrodynamic performance of the flapping rectangular shape fin. Dynamic characteristics of IPMC actuated flapping fins having the same size as the actual fins of three different fish species, Gomphosus varius, Scarus frenatus and Sthethojulis trilineata, are analyzed with numerical simulations. Finally, a comparative study is performed to analyze the performance of three different biomimetic IPMC flapping pectoral fins.

Yielding and large deviations in micellar gels: a model

We present a simple model that can be used to account for the rheological behaviour observed in recent experiments on micellar gels. The model combines attachment detachment kinetics with stretching due to shear, and shows well-defined jammed and flowing states. The large-deviation function (LDF) for the coarse-grained velocity becomes increasingly non-quadratic as the applied force F is increased, in a range near the yield threshold. The power fluctuations are found to obey a steady-state fluctuation relation (FR) at small F. However, the FR is violated when F is near the transition from the flowing to the jammed state although the LDF still exists; the antisymmetric part of the LDF is found to be nonlinear in its argument. Our approach suggests that large fluctuations and motion in a direction opposite to an imposed force are likely to occur in a wider class of systems near yielding.

Clusters of bound particles in the derivative delta-function Bose gas

In this paper we discuss a novel procedure for constructing clusters of bound particles in the case of a quantum integrable derivative delta-function Bose gas in one dimension. It is shown that clusters of bound particles can be constructed for this Bose gas for some special values of the coupling constant, by taking the quasi-momenta associated with the corresponding Bethe state to be equidistant points on a single circle in the complex momentum plane. We also establish a connection between these special values of the coupling constant and some fractions belonging to the Farey sequences in number theory. This connection leads to a classification of the clusters of bound particles associated with the derivative delta-function Bose gas and allows us to study various properties of these clusters like their size and their stability under the variation of the coupling constant. (C) 2013 Elsevier B.V. All rights reserved.

Linear Coding Schemes for the Distributed Computation of Subspaces

Let X-1,..., X-m be a set of m statistically dependent sources over the common alphabet F-q, that are linearly independent when considered as functions over the sample space. We consider a distributed function computation setting in which the receiver is interested in the lossless computation of the elements of an s-dimensional subspace W spanned by the elements of the row vector X-1,..., X-m]Gamma in which the (m x s) matrix Gamma has rank s. A sequence of three increasingly refined approaches is presented, all based on linear encoders. The first approach uses a common matrix to encode all the sources and a Korner-Marton like receiver to directly compute W. The second improves upon the first by showing that it is often more efficient to compute a carefully chosen superspace U of W. The superspace is identified by showing that the joint distribution of the {X-i} induces a unique decomposition of the set of all linear combinations of the {X-i}, into a chain of subspaces identified by a normalized measure of entropy. This subspace chain also suggests a third approach, one that employs nested codes. For any joint distribution of the {X-i} and any W, the sum-rate of the nested code approach is no larger than that under the Slepian-Wolf (SW) approach. Under the SW approach, W is computed by first recovering each of the {X-i}. For a large class of joint distributions and subspaces W, the nested code approach is shown to improve upon SW. Additionally, a class of source distributions and subspaces are identified, for which the nested-code approach is sum-rate optimal.

A novel Q-learning algorithm with function approximation for constrained Markov decision processes

We present a novel multi-timescale Q-learning algorithm for average cost control in a Markov decision process subject to multiple inequality constraints. We formulate a relaxed version of this problem through the Lagrange multiplier method. Our algorithm is different from Q-learning in that it updates two parameters - a Q-value parameter and a policy parameter. The Q-value parameter is updated on a slower time scale as compared to the policy parameter. Whereas Q-learning with function approximation can diverge in some cases, our algorithm is seen to be convergent as a result of the aforementioned timescale separation. We show the results of experiments on a problem of constrained routing in a multistage queueing network. Our algorithm is seen to exhibit good performance and the various inequality constraints are seen to be satisfied upon convergence of the algorithm.

Noise tolerance under risk minimization

In this paper, we explore noise-tolerant learning of classifiers. We formulate the problem as follows. We assume that there is an unobservable training set that is noise free. The actual training set given to the learning algorithm is obtained from this ideal data set by corrupting the class label of each example. The probability that the class label of an example is corrupted is a function of the feature vector of the example. This would account for most kinds of noisy data one encounters in practice. We say that a learning method is noise tolerant if the classifiers learnt with noise-free data and with noisy data, both have the same classification accuracy on the noise-free data. In this paper, we analyze the noise-tolerance properties of risk minimization (under different loss functions). We show that risk minimization under 0-1 loss function has impressive noise-tolerance properties and that under squared error loss is tolerant only to uniform noise; risk minimization under other loss functions is not noise tolerant. We conclude this paper with some discussion on the implications of these theoretical results.

Cl-35 NQR frequency and spin lattice relaxation time in 3,4-dichlorophenol as a function of pressure and temperature

The pressure dependences of Cl-35 nuclear quadrupole resonance (NQR) frequency, temperature and pressure variation of spin lattice relaxation time (T-1) were investigated in 3,4-dichlorophenol. T-1 was measured in the temperature range 77-300 K. Furthermore, the NQR frequency and T-1 for these compounds were measured as a function of pressure up to 5 kbar at 300 K. The temperature dependence of the average torsional lifetimes of the molecules and the transition probabilities W-1 and W-2 for the Delta m = +/- 1 and Delta m = +/- 2 transitions were also obtained. A nonlinear variation of NQR frequency with pressure has been observed and the pressure coefficients were observed to be positive. A thermodynamic analysis of the data was carried out to determine the constant volume temperature coefficients of the NQR frequency. An attempt is made to compare the torsional frequencies evaluated from NQR data with those obtained by IR spectra. On selecting the appropriate mode from IR spectra, a good agreement with torsional frequency obtained from NQR data is observed. The previously mentioned approach is a good illustration of the supplementary nature of the data from IR studies, in relation to NQR studies of compounds in solid state.