Further results on geometric properties of a family of relative entropies

This paper extends some geometric properties of a one-parameter family of relative entropies. These arise as redundancies when cumulants of compressed lengths are considered instead of expected compressed lengths. These parametric relative entropies are a generalization of the Kullback-Leibler divergence. They satisfy the Pythagorean property and behave like squared distances. This property, which was known for finite alphabet spaces, is now extended for general measure spaces. Existence of projections onto convex and certain closed sets is also established. Our results may have applications in the Rényi entropy maximization rule of statistical physics.

Minimization Problems Based on Relative alpha-Entropy I: Forward Projection

Minimization problems with respect to a one-parameter family of generalized relative entropies are studied. These relative entropies, which we term relative alpha-entropies (denoted I-alpha), arise as redundancies under mismatched compression when cumulants of compressed lengths are considered instead of expected compressed lengths. These parametric relative entropies are a generalization of the usual relative entropy (Kullback-Leibler divergence). Just like relative entropy, these relative alpha-entropies behave like squared Euclidean distance and satisfy the Pythagorean property. Minimizers of these relative alpha-entropies on closed and convex sets are shown to exist. Such minimizations generalize the maximum Renyi or Tsallis entropy principle. The minimizing probability distribution (termed forward I-alpha-projection) for a linear family is shown to obey a power-law. Other results in connection with statistical inference, namely subspace transitivity and iterated projections, are also established. In a companion paper, a related minimization problem of interest in robust statistics that leads to a reverse I-alpha-projection is studied.

Global response sensitivity analysis using probability distance measures and generalization of Sobol's analysis

The study introduces two new alternatives for global response sensitivity analysis based on the application of the L-2-norm and Hellinger's metric for measuring distance between two probabilistic models. Both the procedures are shown to be capable of treating dependent non-Gaussian random variable models for the input variables. The sensitivity indices obtained based on the L2-norm involve second order moments of the response, and, when applied for the case of independent and identically distributed sequence of input random variables, it is shown to be related to the classical Sobol's response sensitivity indices. The analysis based on Hellinger's metric addresses variability across entire range or segments of the response probability density function. The measure is shown to be conceptually a more satisfying alternative to the Kullback-Leibler divergence based analysis which has been reported in the existing literature. Other issues addressed in the study cover Monte Carlo simulation based methods for computing the sensitivity indices and sensitivity analysis with respect to grouped variables. Illustrative examples consist of studies on global sensitivity analysis of natural frequencies of a random multi-degree of freedom system, response of a nonlinear frame, and safety margin associated with a nonlinear performance function. (C) 2015 Elsevier Ltd. All rights reserved.

Global response sensitivity analysis of uncertain structures

The problem of characterizing global sensitivity indices of structural response when system uncertainties are represented using probabilistic and (or) non-probabilistic modeling frameworks (which include intervals, convex functions, and fuzzy variables) is considered. These indices are characterized in terms of distance measures between a fiducial model in which uncertainties in all the pertinent variables are taken into account and a family of hypothetical models in which uncertainty in one or more selected variables are suppressed. The distance measures considered include various probability distance measures (Hellinger,l(2), and the Kantorovich metrics, and the Kullback-Leibler divergence) and Hausdorff distance measure as applied to intervals and fuzzy variables. Illustrations include studies on an uncertainly parametered building frame carrying uncertain loads. (C) 2015 Elsevier Ltd. All rights reserved.

An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models

In this paper we study representation of KL-divergence minimization, in the cases where integer sufficient statistics exists, using tools from polynomial algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. In particular, we also study the case of Kullback-Csiszar iteration scheme. We present implicit descriptions of these models and show that implicitization preserves specialization of prior distribution. This result leads us to a Grobner bases method to compute an implicit representation of minimum KL-divergence models.

Occurrence, divergence and evolution of intrinsic terminators across Eubacteria

In Escherichia coli, the canonical intrinsic terminator of transcription includes a palindrome followed by a U-trail on the transcript. The apparent underrepresentation of such terminators in eubacterial genomes led us to develop a rapid and accurate algorithm, GeSTer, to predict putative intrinsic terminators. Now, we have analyzed 378 genome sequences with an improved version of GeSTer. Our results indicate that the canonical E. coli type terminators are not overwhelmingly abundant in eubacteria. The atypical structures, having stem-loop structures but lacking ‘U’ trail, occur downstream of genes in all the analyzed genomes but different phyla show conserved preference for different types of terminators. This propensity correlates with genomic GC content and presence of the factor, Rho. 60–70% of identified terminators in all the genomes show “optimized” stem-length and ΔG. These results provide evidence that eubacteria extensively rely on the mechanism of intrinsic termination, with a considerable divergence in their structure, positioning and prevalence. The software and detailed results for individual genomes are freely available on request

Immunological cross-reactivity of mycobacterial topoisomerase I and divergence from other bacteria

Mycobacterium smegmatis topoisomerase I exhibits several distinctive characteristics among all topoisomerases. The enzyme is devoid of Zn2+fingers found typically in other bacterial type I topoisomerases and binds DNA in a site-specific manner. Using polyclonal antibodies, we demonstrate the high degree of relatedness of the enzyme across mycobacteria but not other bacteria. This absence of cross-reactivity from other bacteria indicates that mycobacterial topoisomerase I has diverged from Escherichia coli and other bacteria. We have investigated further the immunological properties of the enzyme by raising a panel of monoclonal antibodies that recognises different antigenically active regions of the enzyme and binds it with widely varied affinity. Inhibition of a C-terminal domain-specific antibody binding by enzyme-specific and non-specific oligonucleotides suggests the possibility of using these monoclonal antibodies to probe the structure, function and in vivo role of the enzyme.

The beta-glucoside genes of Klebsiella aerogenes: conservation and divergence in relation to the cryptic bgl genes of Escherichia coli

The ability to metabolize aromatic beta-glucosides such as salicin and arbutin varies among members of the Enterobacteriaceae. The ability of Escherichia coli to degrade salicin and arbutin appears to be cryptic, subject to activation of the bgl genes, whereas many members of the Klebsiella genus can metabolize these sugars. We have examined the genetic basis for beta-glucoside utilization in Klebsiella aerogenes. The Klebsiella equivalents of bglG, bglB and bglR have been cloned using the genome sequence database of Klebsiella pneumoniae. Nucleotide sequencing shows that the K. aerogenes bgl genes show substantial similarities to the E. coli counterparts. The K. aerogenes bgl genes in multiple copies can also complement E. coli mutants deficient in bglG encoding the antiterminator and bglB encoding the phospho-beta-glucosidase, suggesting that they are functional homologues. The regulatory region bglR of K aerogenes shows a high degree of similarity of the sequences involved in BglG-mediated regulation. Interestingly, the regions corresponding to the negative elements present in the E. coli regulatory region show substantial divergence in K aerogenes. The possible evolutionary implications of the results are discussed. (C) 2003 Federation of European Microbiological Societies. Published by Elsevier Science B.v. All rights reserved.

On maximum entropy and minimum KL-divergence optimization by Grobner basis methods

In this paper we study constrained maximum entropy and minimum divergence optimization problems, in the cases where integer valued sufficient statistics exists, using tools from computational commutative algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. We give an implicit description of maximum entropy models by embedding them in algebraic varieties for which we give a Grobner basis method to compute it. In the cases of minimum KL-divergence models we show that implicitization preserves specialization of prior distribution. This result leads us to a Grobner basis method to embed minimum KL-divergence models in algebraic varieties. (C) 2012 Elsevier Inc. All rights reserved.

Fluctuating micro-heterogeneity in water-tert-butyl alcohol mixtures and lambda-type divergence of the mean cluster size with phase transition-like multiple anomalies

Water-tert-butyl alcohol (TBA) binary mixture exhibits a large number of thermodynamic and dynamic anomalies. These anomalies are observed at surprisingly low TBA mole fraction, with x(TBA) approximate to 0.03-0.07. We demonstrate here that the origin of the anomalies lies in the local structural changes that occur due to self-aggregation of TBA molecules. We observe a percolation transition of the TBA molecules at x(TBA) approximate to 0.05. We note that ``islands'' of TBA clusters form even below this mole fraction, while a large spanning cluster emerges above that mole fraction. At this percolation threshold, we observe a lambda-type divergence in the fluctuation of the size of the largest TBA cluster, reminiscent of a critical point. Alongside, the structure of water is also perturbed, albeit weakly, by the aggregation of TBA molecules. There is a monotonic decrease in the tetrahedral order parameter of water, while the dipole moment correlation shows a weak nonlinearity. Interestingly, water molecules themselves exhibit a reverse percolation transition at higher TBA concentration, x(TBA) approximate to 0.45, where large spanning water clusters now break-up into small clusters. This is accompanied by significant divergence of the fluctuations in the size of largest water cluster. This second transition gives rise to another set of anomalies around. Both the percolation transitions can be regarded as manifestations of Janus effect at small molecular level. (C) 2014 AIP Publishing LLC.

Rapid divergence of ecotypes of an invasive plant

Invasive species demonstrate rapid evolution within a very short period of time allowing one to understand the underlying mechanism(s). Lantana camara, a highly invasive plant of the tropics and subtropics, has expanded its range and successfully established itself almost throughout India. In order to uncover the processes governing the invasion dynamics, 218 individuals from various locations across India were characterized with six microsatellites. By integrating genetic data with niche modelling, we examined the effect of drift and environmental selection on genetic divergence. We found multiple genetic clusters that were non-randomly distributed across space. Spatial autocorrelation revealed a strong fine-scale structure, i.e. isolation by distance. In addition, we obtained evidence of inhibitory effects of selection on gene flow, i.e. isolation by environmental distance. Perhaps, local adaptation in response to selection is offsetting gene flow and causing the populations to diverge. Niche models suggested that temperature and precipitation play a major role in the observed spatial distribution of this plant. Based on a non-random distribution of clusters, unequal gene flow among them and different bioclimatic niche requirements, we concluded that the emergence of ecotypes represented by two genetic clusters is underway. They may be locally adapted to specific climatic conditions, and perhaps at the very early stages of ecological divergence.

Paralogous cAMP Receptor Proteins in Mycobacterium smegmatis Show Biochemical and Functional Divergence

The cyclic AMP receptor protein (CRP) family of transcription factors consists of global regulators of bacterial gene expression. Here, we identify two paralogous CRPs in the genome of Mycobacterium smegmatis that have 78% identical sequences and characterize them biochemically and functionally. The two proteins (MSMEG_0539 and MSMEG_6189) show differences in cAMP binding affinity, trypsin sensitivity, and binding to a CRP site that we have identified upstream of the msmeg_3781 gene. MSMEG_6189 binds to the CRP site readily in the absence of cAMP, while MSMEG_0539 binds in the presence of cAMP, albeit weakly. msmeg_6189 appears to be an essential gene, while the ?msmeg_0539 strain was readily obtained. Using promoter-reporter constructs, we show that msmeg_3781 is regulated by CRP binding, and its transcription is repressed by MSMEG_6189. Our results are the first to characterize two paralogous and functional CRPs in a single bacterial genome. This gene duplication event has subsequently led to the evolution of two proteins whose biochemical differences translate to differential gene regulation, thus catering to the specific needs of the organism.

Taming Control Divergence in GPUs through Control Flow Linearization

Branch divergence is a very commonly occurring performance problem in GPGPU in which the execution of diverging branches is serialized to execute only one control flow path at a time. Existing hardware mechanism to reconverge threads using a stack causes duplicate execution of code for unstructured control flow graphs. Also the stack mechanism cannot effectively utilize the available parallelism among diverging branches. Further, the amount of nested divergence allowed is also limited by depth of the branch divergence stack. In this paper we propose a simple and elegant transformation to handle all of the above mentioned problems. The transformation converts an unstructured CFG to a structured CFG without duplicating user code. It incurs only a linear increase in the number of basic blocks and also the number of instructions. Our solution linearizes the CFG using a predicate variable. This mechanism reconverges the divergent threads as early as possible. It also reduces the depth of the reconvergence stack. The available parallelism in nested branches can be effectively extracted by scheduling the basic blocks to reduce the effect of stalls due to memory accesses. It can also increase execution efficiency of nested loops with different trip counts for different threads. We implemented the proposed transformation at PTX level using the Ocelot compiler infrastructure. We evaluated the technique using various benchmarks to show that it can be effective in handling the performance problem due to divergence in unstructured CFGs.

Divergence in Patterns of Leaf Growth Polarity Is Associated with the Expression Divergence of miR396

Lateral appendages often show allometric growth with a specific growth polarity along the proximo-distal axis. Studies on leaf growth in model plants have identified a basipetal growth direction with the highest growth rate at the proximal end and progressively lower rates toward the distal end. Although the molecular mechanisms governing such a growth pattern have been studied recently, variation in leaf growth polarity and, therefore, its evolutionary origin remain unknown. By surveying 75 eudicot species, here we report that leaf growth polarity is divergent. Leaf growth in the proximo-distal axis is polar, with more growth arising from either the proximal or the distal end; dispersed with no apparent polarity; or bidirectional, with more growth contributed by the central region and less growth at either end. We further demonstrate that the expression gradient of the miR396-GROWTH-REGULATING FACTOR module strongly correlates with the polarity of leaf growth. Altering the endogenous pattern of miR396 expression in transgenic Arabidopsis thaliana leaves only partially modified the spatial pattern of cell expansion, suggesting that the diverse growth polarities might have evolved via concerted changes in multiple gene regulatory networks.

Screened and unscreened phases in sedimenting suspensions

A coarse-grained stochastic hydrodynamical description of velocity and concentration fluctuations in steadily sedimenting suspensions is constructed and analyzed using self-consistent and renormalization-group methods. We find a nonequilibrium phase transition from an "unscreened" phase in which we recover the Caflisch-Luke [Phys. Fluids 28, 759 (1985)] divergence of the velocity variance to a "screened" phase where the fluctuations have a finite correlation length depending on the volume fraction phi as phi(-1/3), in agreement with Segre et al. [Phys. Rev. Lett. 79, 2574 (1997)] (if their observation of a phi-independent diffusivity is used), and the velocity variance is independent of system size.