An O(mn) Gomory-Hu Tree Construction Algorithm for Unweighted Graphs

We present a fast algorithm for computing a Gomory-Hu tree or cut tree for an unweighted undirected graph G = (V,E). The expected running time of our algorithm is Õ(mc) where |E| = m and c is the maximum u-vedge connectivity, where u,v ∈ V. When the input graph is also simple (i.e., it has no parallel edges), then the u-v edge connectivity for each pair of vertices u and v is at most n-1; so the expected running time of our algorithm for simple unweighted graphs is Õ(mn).All the algorithms currently known for constructing a Gomory-Hu tree [8,9] use n-1 minimum s-t cut (i.e., max flow) subroutines. This in conjunction with the current fastest Õ(n20/9) max flow algorithm due to Karger and Levine [11] yields the current best running time of Õ(n20/9n) for Gomory-Hu tree construction on simpleunweighted graphs with m edges and n vertices. Thus we present the first Õ(mn) algorithm for constructing a Gomory-Hu tree for simple unweighted graphs.We do not use a max flow subroutine here; we present an efficient tree packing algorithm for computing Steiner edge connectivity and use this algorithm as our main subroutine. The advantage in using a tree packing algorithm for constructing a Gomory-Hu tree is that the work done in computing a minimum Steiner cut for a Steiner set S ⊆ V can be reused for computing a minimum Steiner cut for certain Steiner sets S' ⊆ S.

Effectors of Salmonella pathogenicity island 2: An island crucial to the life of Salmonella

The tug of war between a pathogen and its host has been one of the most amazing stories in the field of microbial pathogenesis for ages. The strongest known species of all living organisms is the Homo sapiens and yet it is incredible how a pathogen of the size of few microns is smart enough to defeat this mightiest group of survivors. It is of utmost interest to understand the mechanisms behind the successful habitation of a pathogen inside the ever-resisting and complicate human body. Numerous examples of diseases caused by such pathogens exist which intrigues us to venture in the world of host-pathogen interactions.

Decision tree design and applications in speech processing

The design and operation of the minimum cost classifier, where the total cost is the sum of the measurement cost and the classification cost, is computationally complex. Noting the difficulties associated with this approach, decision tree design directly from a set of labelled samples is proposed in this paper. The feature space is first partitioned to transform the problem to one of discrete features. The resulting problem is solved by a dynamic programming algorithm over an explicitly ordered state space of all outcomes of all feature subsets. The solution procedure is very general and is applicable to any minimum cost pattern classification problem in which each feature has a finite number of outcomes. These techniques are applied to (i) voiced, unvoiced, and silence classification of speech, and (ii) spoken vowel recognition. The resulting decision trees are operationally very efficient and yield attractive classification accuracies.

Geometric Decision Tree

In this paper, we present a new algorithm for learning oblique decision trees. Most of the current decision tree algorithms rely on impurity measures to assess the goodness of hyperplanes at each node while learning a decision tree in top-down fashion. These impurity measures do not properly capture the geometric structures in the data. Motivated by this, our algorithm uses a strategy for assessing the hyperplanes in such a way that the geometric structure in the data is taken into account. At each node of the decision tree, we find the clustering hyperplanes for both the classes and use their angle bisectors as the split rule at that node. We show through empirical studies that this idea leads to small decision trees and better performance. We also present some analysis to show that the angle bisectors of clustering hyperplanes that we use as the split rules at each node are solutions of an interesting optimization problem and hence argue that this is a principled method of learning a decision tree.

Females of a tree cricket prefer larger males but not the lower frequency male calls that indicate large body size

In the tree cricket Oecanthus henryi, females are attracted by male calls and can choose between males. To make a case for female choice based on male calls, it is necessary to examine male call variation in the field and identify repeatable call features that are reliable indicators of male size or symmetry. Female preference for these reliable call features and the underlying assumption behind this choice, female preference for larger males, also need to be examined. We found that females did prefer larger males during mating, as revealed by the longer mating durations and longer spermatophore retention times. We then examined the correlation between acoustic and morphological features and the repeatability of male calls in the field across two temporal scales, within and across nights. We found that carrier frequency was a reliable indicator of male size, with larger males calling at lower frequencies at a given temperature. Simultaneous playback of male calls differing in frequency, spanning the entire range of natural variation at a given temperature, revealed a lack of female preference for low carrier frequencies. The contrasting results between the phonotaxis and mating experiments may be because females are incapable of discriminating small differences in frequency or because the change in call carrier frequency with temperature renders this cue unreliable in tree crickets. (C) 2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Scalable multi-dimensional user intent identification using tree structured distributions

The problem of identifying user intent has received considerable attention in recent years, particularly in the context of improving the search experience via query contextualization. Intent can be characterized by multiple dimensions, which are often not observed from query words alone. Accurate identification of Intent from query words remains a challenging problem primarily because it is extremely difficult to discover these dimensions. The problem is often significantly compounded due to lack of representative training sample. We present a generic, extensible framework for learning the multi-dimensional representation of user intent from the query words. The approach models the latent relationships between facets using tree structured distribution which leads to an efficient and convergent algorithm, FastQ, for identifying the multi-faceted intent of users based on just the query words. We also incorporated WordNet to extend the system capabilities to queries which contain words that do not appear in the training data. Empirical results show that FastQ yields accurate identification of intent when compared to a gold standard.

OTCYMIST: Otsu-Canny minimal spanning tree for born-digital images

Text segmentation and localization algorithms are proposed for the born-digital image dataset. Binarization and edge detection are separately carried out on the three colour planes of the image. Connected components (CC's) obtained from the binarized image are thresholded based on their area and aspect ratio. CC's which contain sufficient edge pixels are retained. A novel approach is presented, where the text components are represented as nodes of a graph. Nodes correspond to the centroids of the individual CC's. Long edges are broken from the minimum spanning tree of the graph. Pair wise height ratio is also used to remove likely non-text components. A new minimum spanning tree is created from the remaining nodes. Horizontal grouping is performed on the CC's to generate bounding boxes of text strings. Overlapping bounding boxes are removed using an overlap area threshold. Non-overlapping and minimally overlapping bounding boxes are used for text segmentation. Vertical splitting is applied to generate bounding boxes at the word level. The proposed method is applied on all the images of the test dataset and values of precision, recall and H-mean are obtained using different approaches.

Delineation of seismic source zones based on seismicity parameters and probabilistic evaluation of seismic hazard using logic tree approach

The delineation of seismic source zones plays an important role in the evaluation of seismic hazard. In most of the studies the seismic source delineation is done based on geological features. In the present study, an attempt has been made to delineate seismic source zones in the study area (south India) based on the seismicity parameters. Seismicity parameters and the maximum probable earthquake for these source zones were evaluated and were used in the hazard evaluation. The probabilistic evaluation of seismic hazard for south India was carried out using a logic tree approach. Two different types of seismic sources, linear and areal, were considered in the present study to model the seismic sources in the region more precisely. In order to properly account for the attenuation characteristics of the region, three different attenuation relations were used with different weightage factors. Seismic hazard evaluation was done for the probability of exceedance (PE) of 10% and 2% in 50 years. The spatial variation of rock level peak horizontal acceleration (PHA) and spectral acceleration (Sa) values corresponding to return periods of 475 and 2500 years for the entire study area are presented in this work. The peak ground acceleration (PGA) values at ground surface level were estimated based on different NEHRP site classes by considering local site effects.

Scale-dependent relationships between tree species richness and ecosystem function in forests

1. The relationship between species richness and ecosystem function, as measured by productivity or biomass, is of long-standing theoretical and practical interest in ecology. This is especially true for forests, which represent a majority of global biomass, productivity and biodiversity. 2. Here, we conduct an analysis of relationships between tree species richness, biomass and productivity in 25 forest plots of area 8-50ha from across the world. The data were collected using standardized protocols, obviating the need to correct for methodological differences that plague many studies on this topic. 3. We found that at very small spatial grains (0.04ha) species richness was generally positively related to productivity and biomass within plots, with a doubling of species richness corresponding to an average 48% increase in productivity and 53% increase in biomass. At larger spatial grains (0.25ha, 1ha), results were mixed, with negative relationships becoming more common. The results were qualitatively similar but much weaker when we controlled for stem density: at the 0.04ha spatial grain, a doubling of species richness corresponded to a 5% increase in productivity and 7% increase in biomass. Productivity and biomass were themselves almost always positively related at all spatial grains. 4. Synthesis. This is the first cross-site study of the effect of tree species richness on forest biomass and productivity that systematically varies spatial grain within a controlled methodology. The scale-dependent results are consistent with theoretical models in which sampling effects and niche complementarity dominate at small scales, while environmental gradients drive patterns at large scales. Our study shows that the relationship of tree species richness with biomass and productivity changes qualitatively when moving from scales typical of forest surveys (0.04ha) to slightly larger scales (0.25 and 1ha). This needs to be recognized in forest conservation policy and management.

Coral diseases are major contributors to coral mortality in Shingle Island, Gulf of Mannar, southeastern India

The present study reports coral mortality, driven primarily by coral diseases, around Shingle Island, Gulf of Mannar (GOM), Indian Ocean. In total, 2910 colonies were permanently monitored to assess the incidence of coral diseases and consequent mortality for 2 yr. Four types of lesions consistent with white band disease (WBD), black disease (BD), white plaque disease (WPD), and pink spot disease (PSD) were recorded from 4 coral genera: Montipora, Pocillopora, Acropora, and Porites. Porites were affected by 2 disease types, while the other 3 genera were affected by only 1 disease type. Overall disease prevalence increased from 8% (n = 233 colonies) to 41.9% (n = 1219) over the 2 yr study period. BD caused an unprecedented 100% mortality in Pocillopora, followed by 20.4 and 13.1% mortality from WBD in Montipora and Acropora, respectively. Mean disease progression rates of 0.8 +/- 1.0 and 0.6 +/- 0.5 cm mo(-1) over live coral colonies were observed for BD and WBD. Significant correlations between temperature and disease progression were observed for BD (r = 0.86, R-2 = 0.75, p < 0.001) and WBD (R-2 = 0.76, p < 0.001). This study revealed the increasing trend of disease prevalence and progression of disease over live coral in a relatively limited study area; further study should investigate the status of the entire coral reef in the GOM and the role of diseases in reef dynamics.

Temporal variability of forest communities: empirical estimates of population change in 4000 tree species

Long-term surveys of entire communities of species are needed to measure fluctuations in natural populations and elucidate the mechanisms driving population dynamics and community assembly. We analysed changes in abundance of over 4000 tree species in 12 forests across the world over periods of 6-28years. Abundance fluctuations in all forests are large and consistent with population dynamics models in which temporal environmental variance plays a central role. At some sites we identify clear environmental drivers, such as fire and drought, that could underlie these patterns, but at other sites there is a need for further research to identify drivers. In addition, cross-site comparisons showed that abundance fluctuations were smaller at species-rich sites, consistent with the idea that stable environmental conditions promote higher diversity. Much community ecology theory emphasises demographic variance and niche stabilisation; we encourage the development of theory in which temporal environmental variance plays a central role.

A shortest path tree based algorithm for relay placement in a wireless sensor network and its performance analysis

In this paper, we study a problem of designing a multi-hop wireless network for interconnecting sensors (hereafter called source nodes) to a Base Station (BS), by deploying a minimum number of relay nodes at a subset of given potential locations, while meeting a quality of service (QoS) objective specified as a hop count bound for paths from the sources to the BS. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard. For this problem, we propose a polynomial time approximation algorithm based on iteratively constructing shortest path trees and heuristically pruning away the relay nodes used until the hop count bound is violated. Results show that the algorithm performs efficiently in various randomly generated network scenarios; in over 90% of the tested scenarios, it gave solutions that were either optimal or were worse than optimal by just one relay. We then use random graph techniques to obtain, under a certain stochastic setting, an upper bound on the average case approximation ratio of a class of algorithms (including the proposed algorithm) for this problem as a function of the number of source nodes, and the hop count bound. To the best of our knowledge, the average case analysis is the first of its kind in the relay placement literature. Since the design is based on a light traffic model, we also provide simulation results (using models for the IEEE 802.15.4 physical layer and medium access control) to assess the traffic levels up to which the QoS objectives continue to be met. (C) 2014 Elsevier B.V. All rights reserved.

Salmonella methylglyoxal detoxification by STM3117-encoded lactoylglutathione lyase affects virulence in coordination with Salmonella pathogenicity island 2 and phagosomal acidification

Intracellular pathogens such as Salmonella enterica serovar Typhimurium (S. Typhimurium) manipulate their host cells through the interplay of various virulence factors. A multitude of such virulence factors are encoded on the genome of S. Typhimurium and are usually organized in pathogenicity islands. The virulence-associated genomic stretch of STM3117-3120 has structural features of pathogenicity islands and is present exclusively in non-typhoidal serovars of Salmonella. It encodes metabolic enzymes predicted to be involved in methylglyoxal metabolism. STM3117-encoded lactoylglutathione lyase significantly impacts the proliferation of intracellular Salmonella. The deletion mutant of STM3117 (Delta lgl) fails to grow in epithelial cells but hyper-replicates in macrophages. This difference in proliferation outcome was the consequence of failure to detoxify methylglyoxal by Delta lgl, which was also reflected in the form of oxidative DNA damage and upregulation of kefB in the mutant. Within macrophages, the toxicity of methylglyoxal adducts elicits the potassium efflux channel (KefB) in the mutant which subsequently modulates the acidification of mutant-containing vacuoles (MCVs). The perturbation in the pH of the MCV milieu and bacterial cytosol enhances the Salmonella pathogenicity island 2 translocation in Delta lgl, increasing its net growth within macrophages. In epithelial cells, however, the maturation of Delta lgl-containing vacuoles were affected as these non-phagocytic cells maintain less acidic vacuoles compared to those in macrophages. Remarkably, ectopic expression of Toll-like receptors 2 and 4 on epithelial cells partially restored the survival of Delta lgl. This study identified a novel metabolic enzyme in S. Typhimurium whose activity during intracellular infection within a given host cell type differentially affected the virulence of the bacteria.