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.

A game theoretic approach for feature clustering and its application to feature selection

In this paper, we develop a game theoretic approach for clustering features in a learning problem. Feature clustering can serve as an important preprocessing step in many problems such as feature selection, dimensionality reduction, etc. In this approach, we view features as rational players of a coalitional game where they form coalitions (or clusters) among themselves in order to maximize their individual payoffs. We show how Nash Stable Partition (NSP), a well known concept in the coalitional game theory, provides a natural way of clustering features. Through this approach, one can obtain some desirable properties of the clusters by choosing appropriate payoff functions. For a small number of features, the NSP based clustering can be found by solving an integer linear program (ILP). However, for large number of features, the ILP based approach does not scale well and hence we propose a hierarchical approach. Interestingly, a key result that we prove on the equivalence between a k-size NSP of a coalitional game and minimum k-cut of an appropriately constructed graph comes in handy for large scale problems. In this paper, we use feature selection problem (in a classification setting) as a running example to illustrate our approach. We conduct experiments to illustrate the efficacy of our approach.

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.

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.

Rice LHS1/OsMADS1 Controls Floret Meristem Specification by Coordinated Regulation of Transcription Factors and Hormone Signaling Pathways

SEPALLATA (SEP) MADS box transcription factors mediate floral development in association with other regulators. Mutants in five rice (Oryza sativa) SEP genes suggest both redundant and unique functions in panicle branching and floret development. LEAFY HULL STERILE1/OsMADS1, from a grass-specific subgroup of LOFSEP genes, is required for specifying a single floret on the spikelet meristem and for floret organ development, but its downstream mechanisms are unknown. Here, key pathways and directly modulated targets of OsMADS1 were deduced from expression analysis after its knockdown and induction in developing florets and by studying its chromatin occupancy at downstream genes. The negative regulation of OsMADS34, another LOFSEP gene, and activation of OsMADS55, a SHORT VEGETATIVE PHASE-like floret meristem identity gene, show its role in facilitating the spikelet-to-floret meristem transition. Direct regulation of other transcription factor genes like OsHB4 (a class III homeodomain Leu zipper member), OsBLH1 (a BEL1-like homeodomain member), OsKANADI2, OsKANADI4, and OsETTIN2 show its role in meristem maintenance, determinacy, and lateral organ development. We found that the OsMADS1 targets OsETTIN1 and OsETTIN2 redundantly ensure carpel differentiation. The multiple effects of OsMADS1 in promoting auxin transport, signaling, and auxin-dependent expression and its direct repression of three cytokinin A-type response regulators show its role in balancing meristem growth, lateral organ differentiation, and determinacy. Overall, we show that OsMADS1 integrates transcriptional and signaling pathways to promote rice floret specification and development.

Cytochrome P450-mediated metabolism in brain: functional roles and their implications

Introduction: Cytochromes P450 (P450) and associated monooxygenases are a family of heme proteins involved in metabolism of endogenous compounds (arachidonic acid, eicosanoids and prostaglandins) as also xenobiotics including drugs and environmental chemicals. Liver is the major organ involved in P450-mediated metabolism and hepatic enzymes have been characterized. Extrahepatic organs, such as lung, kidney and brain have the capability for biotransformation through P450 enzymes. Brain, including human brain, expresses P450 enzymes that metabolize xenobiotics and endogenous compounds. Areas covered: An overview of P450-mediated metabolism in brain is presented focusing on distinct differences seen in expression of P450 enzymes, generation of unique P450 enzymes in brain through alternate splicing and their consequences in terms of metabolism of psychoactive drugs and inflammatory prompts, such as leukotrienes, thus modulating inflammatory response. Expert opinion: The brain possesses unique P450s that metabolize drugs and endogenous compounds through pathways that are markedly different from that seen in liver indicating that extrapolation directly from liver to brain is not appropriate. It is therefore necessary to characterize the unique brain P450s and their ability to metabolize xenobiotics and endogenous compounds to better understand the functions of this important class of enzymes in brain, especially human brain.

Rotating beams isospectral to axially loaded nonrotating uniform beams

In this paper, the stiffness and mass per unit length distributions of a rotating beam, which is isospectral to a given uniform axially loaded nonrotating beam, are determined analytically. The Barcilon-Gottlieb transformation is extended so that it transforms the governing equation of a rotating beam into the governing equation of a uniform, axially loaded nonrotating beam. Analysis is limited to a certain class of Euler-Bernoulli cantilever beams, where the product between the stiffness and the cube of mass per unit length is a constant. The derived mass and stiffness distributions of the rotating beam are used in a finite element analysis to confirm the frequency equivalence of the given and derived beams. Examples of physically realizable beams that have a rectangular cross section are shown as a practical application of the analysis.

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.

Diverse functions of restriction-modification systems in addition to cellular defense

Restriction-modification (R-M) systems are ubiquitous and are often considered primitive immune systems in bacteria. Their diversity and prevalence across the prokaryotic kingdom are an indication of their success as a defense mechanism against invading genomes. However, their cellular defense function does not adequately explain the basis for their immaculate specificity in sequence recognition and nonuniform distribution, ranging from none to too many, in diverse species. The present review deals with new developments which provide insights into the roles of these enzymes in other aspects of cellular function. In this review, emphasis is placed on novel hypotheses and various findings that have not yet been dealt with in a critical review. Emerging studies indicate their role in various cellular processes other than host defense, virulence, and even controlling the rate of evolution of the organism. We also discuss how R-M systems could have successfully evolved and be involved in additional cellular portfolios, thereby increasing the relative fitness of their hosts in the population.

Bactericidal/permeability increasing protein: A multifaceted protein with functions beyond LPS neutralization

Bactericidal permeability increasing protein (BPI), a 55-60kDa protein, first reported in 1975, has gone a long way as a protein with multifunctional roles. Its classical role in neutralizing endotoxin (LPS) raised high hopes among septic shock patients. Today, BPI is not just a LPS-neutralizing protein, but a protein with diverse functions. These functions can be as varied as inhibition of endothelial cell growth and inhibition of dendritic cell maturation, or as an anti-angiogenic, chemoattractant or opsonization agent. Though the literature available is extremely limited, it is fascinating to look into how BPI is gaining major importance as a signalling molecule. In this review, we briefly summarize the recent research focused on the multiple roles of BPI and its use as a therapeutic.

Probing p300/CBP associated Factor (PCAF)-dependent pathways with a small molecule inhibitor

PCAF (KAT2B) belongs to the GNAT family of lysine acetyltransferases (KAT) and specifically acetylates the histone H3K9 residue and several nonhistone proteins. PCAF is also a transcriptional coactivator. Due to the lack of a PCAF KAT-specific small molecule inhibitor, the exclusive role of the acetyltransferase activity of PCAF is not well understood. Here, we report that a natural compound of the hydroxybenzoquinone class, embelin, specifically inhibits H3Lys9 acetylation in mice and inhibits recombinant PCAF-mediated acetylation with near complete specificity in vitro. Furthermore, using embelin, we have identified the gene networks that are regulated by PCAF during muscle differentiation, further highlighting the broader regulatory functions of PCAF in muscle differentiation in addition to the regulation via MyoD acetylation.

Splicing Functions and Global Dependency on Fission Yeast Slu7 Reveal Diversity in Spliceosome Assembly

The multiple short introns in Schizosaccharomyces pombe genes with degenerate cis sequences and atypically positioned polypyrimidine tracts make an interesting model to investigate canonical and alternative roles for conserved splicing factors. Here we report functions and interactions of the S. pombe slu7(+) (spslu7(+)) gene product, known from Saccharomyces cerevisiae and human in vitro reactions to assemble into spliceosomes after the first catalytic reaction and to dictate 3' splice site choice during the second reaction. By using a missense mutant of this essential S. pombe factor, we detected a range of global splicing derangements that were validated in assays for the splicing status of diverse candidate introns. We ascribe widespread, intron-specific SpSlu7 functions and have deduced several features, including the branch nucleotide-to-3' splice site distance, intron length, and the impact of its A/U content at the 5' end on the intron's dependence on SpSlu7. The data imply dynamic substrate-splicing factor relationships in multiintron transcripts. Interestingly, the unexpected early splicing arrest in spslu7-2 revealed a role before catalysis. We detected a salt-stable association with U5 snRNP and observed genetic interactions with spprp1(+), a homolog of human U5-102k factor. These observations together point to an altered recruitment and dependence on SpSlu7, suggesting its role in facilitating transitions that promote catalysis, and highlight the diversity in spliceosome assembly.

Expansions of tau hadronic spectral function moments in a nonpower QCD perturbation theory with tamed large order behavior

The moments of the hadronic spectral functions are of interest for the extraction of the strong coupling alpha(s) and other QCD parameters from the hadronic decays of the tau lepton. Motivated by the recent analyses of a large class of moments in the standard fixed-order and contour-improved perturbation theories, we consider the perturbative behavior of these moments in the framework of a QCD nonpower perturbation theory, defined by the technique of series acceleration by conformal mappings, which simultaneously implements renormalization-group summation and has a tame large-order behavior. Two recently proposed models of the Adler function are employed to generate the higher-order coefficients of the perturbation series and to predict the exact values of the moments, required for testing the properties of the perturbative expansions. We show that the contour-improved nonpower perturbation theories and the renormalization-group-summed nonpower perturbation theories have very good convergence properties for a large class of moments of the so-called ``reference model,'' including moments that are poorly described by the standard expansions. The results provide additional support for the plausibility of the description of the Adler function in terms of a small number of dominant renormalons.

Scalar transport in diffusion flame wrapped up by an air and fuel side vortex

The present work involves a computational study of soot (chosen as a scalar which is a primary pollutant source) formation and transport in a laminar acetylene diffusion flame perturbed by a convecting line vortex. The topology of soot contours resulting from flame vortex interactions has been investigated. More soot was produced when vortex was introduced from the air side in comparison to the fuel side. Also, the soot topography was spatially more diffuse in the case of air side vortex. The computational model was found to be in good agreement with the experimental work previously reported in the literature. The computational simulation enabled a study of various parameters like temperature, equivalence ratio and temperature gradient affecting the soot production and transport. Temperatures were found to be higher in the case of air side vortex in contrast to the fuel side one. In case of fuel side vortex, abundance of fuel in the vortex core resulted in fuel-rich combustion zone in the core and a more discrete soot topography. Besides, the overall soot production was observed to be low in the fuel side vortex. However, for the air side vortex, air abundance in the core resulted in higher temperatures and greater soot production. Probability density functions (PDFs) have been introduced to investigate the spatiotemporal variation of soot yield and transport and their dependence on temperature and acetylene concentration from statistical view point. In addition, the effect of flame curvature on soot production is also studied. The regions convex to fuel stream side witnessed thicker soot layer. All numerical simulations have been carried out on Fluent 6.3.26. (C) 2013 Elsevier Ltd. All rights reserved.

Infinitely divisible metrics and curvature inequalities for operators in the Cowen-Douglas class

The curvature (T)(w) of a contraction T in the Cowen-Douglas class B-1() is bounded above by the curvature (S*)(w) of the backward shift operator. However, in general, an operator satisfying the curvature inequality need not be contractive. In this paper, we characterize a slightly smaller class of contractions using a stronger form of the curvature inequality. Along the way, we find conditions on the metric of the holomorphic Hermitian vector bundle E-T corresponding to the operator T in the Cowen-Douglas class B-1() which ensures negative definiteness of the curvature function. We obtain a generalization for commuting tuples of operators in the class B-1() for a bounded domain in C-m.