An Approach to seco-Prezizaane Sesquiterpenoids: Enantioselective Total Synthesis of (+)-1S-Minwanenone

A strategy of general applicability toward seco-prezizaane sesquiterpenes, from a chiral, tricyclic synthon, readily available via an enzymatic resolution step from the Diels-Alder adduct of cyclopentadiene and p-benzoquinone, has been devised. Our approach enables harnessing of the stereochemical proclivities of the norbornyl system to install the desired stereochemistry at the key stereogenic centers. Recourse to an interesting stratagem to realign a stereochemical divergence into stereoreconvergence forms the cornerstone of our successful approach. The first total synthesis of (+)-1S-minwanenone, a prototypical member of seco-prezizaane subclass, has been accomplished.

Two orders of magnitude increase in metal piezoresistor sensitivity through nanoscale inhomogenization

Metal-based piezoresistive sensing devices could find a much wider applicability if their sensitivity to mechanical strain could be substantially improved. Here, we report a simple method to enhance the strain sensitivity of metal films by over two orders of magnitude and demonstrate it on specially designed microcantilevers. By locally inhomogenizing thin gold films using controlled electromigration, we have achieved a logarithmic divergence in the strain sensitivity with progressive microstructural modification. The enhancement in strain sensitivity could be explained using non-universal tunneling-percolation transport. We find that the Johnson noise limited signal-to-noise ratio is an order of magnitude better than silicon piezoresistors. This method creates a robust platform for engineering low resistance, high gauge factor metallic piezoresistors that may have profound impact on micro and nanoscale self-sensing technology. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4761817]

The origins of the evolutionary signal used to predict protein-protein interactions

Background: The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods), many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results: In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions: Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.

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.

Revision of the scolopendrid centipede digitipes Attems, 1930, from India (Chilopoda: Scolopendromorpha): reconciling molecular and morphological estimates of species diversity

Recent work on molecular phylogenetics of Scolopendridae from the Western Ghats, Peninsular India, has suggested the presence of six cryptic species of the otostigmine Digitipes Attems, 1930, together with three species described in previous taxonomic work by Jangi and Dass (1984). Digitipes is the correct generic attribution for a monophyletic group of Indian species, these being united with three species from tropical Africa (including the type) that share a distomedial process on the ultimate leg femur of males that is otherwise unknown in Otostigminae. Second maxillary characters previously used in the diagnosis of Digitipes are dismissed because Indian species do not possess the putatively diagnostic character states. Two new species from the Western Ghats that correspond to groupings identified based on monophyly, sequence divergence and coalescent analysis using molecular data are diagnosed based on distinct morphological characters. They are D. jangii and D. periyarensis n. spp. Three species named by Jangi and Dass (Digitipes barnabasi, D. coonoorensis and D. indicus) are revised based on new collections; D. indicus is a junior subjective synonym of Arthrorhabdus jonesii Verhoeff, 1938, the combination becoming Digitipes jonesii (Verhoeff, 1938) n. comb. The presence of Arthrorhabdus in India is accordingly refuted. Three putative species delimited by molecular and ecological data remain cryptic from the perspective of diagnostic morphological characters and are presently retained in D. barnabasi, D. jangii and D. jonesii. A molecularly-delimited species that resolved as sister group to a well-supported clade of Indian Digitipes is identified as Otostigmus ruficeps Pocock, 1890, originally described from a single specimen and revised herein. One Indian species originally assigned to Digitipes, D. gravelyi, deviates from confidently-assigned Digitipes with respect to several characters and is reassigned to Otostigmus, as O. gravelyi (Jangi and Dass, 1984) n. comb.

Predictability and chaotic nature of daily streamflow

The predictability of a chaotic series is limited to a few future time steps due to its sensitivity to initial conditions and the exponential divergence of the trajectories. Over the years, streamflow has been considered as a stochastic system in many approaches. In this study, the chaotic nature of daily streamflow is investigated using autocorrelation function, Fourier spectrum, correlation dimension method (Grassberger-Procaccia algorithm) and false nearest neighbor method. Embedding dimensions of 6-7 obtained indicates the possible presence of low-dimensional chaotic behavior. The predictability of the system is estimated by calculating the system’s Lyapunov exponent. A positive maximum Lyapunov exponent of 0.167 indicates that the system is chaotic and unstable with a maximum predictability of only 6 days. These results give a positive indication towards considering streamflow as a low dimensional chaotic system than as a stochastic system.

On the relation between K-means and PLSA

Non-negative matrix factorization [5](NMF) is a well known tool for unsupervised machine learning. It can be viewed as a generalization of the K-means clustering, Expectation Maximization based clustering and aspect modeling by Probabilistic Latent Semantic Analysis (PLSA). Specifically PLSA is related to NMF with KL-divergence objective function. Further it is shown that K-means clustering is a special case of NMF with matrix L2 norm based error function. In this paper our objective is to analyze the relation between K-means clustering and PLSA by examining the KL-divergence function and matrix L2 norm based error function.

Phylogenetic analysis and molecular dating suggest that hemidactylus anamallensis is not a member of the hemidactylus radiation and has an ancient late cretaceous origin

Background of the Work: The phylogenetic position and evolution of Hemidactylus anamallensis (family Gekkonidae) has been much debated in recent times. In the past it has been variously assigned to genus Hoplodactylus (Diplodactylidae) as well as a monotypic genus `Dravidogecko' (Gekkonidae). Since 1995, this species has been assigned to Hemidactylus, but there is much disagreement between authors regarding its phylogenetic position within this genus. In a recent molecular study H. anamallensis was sister to Hemidactylus but appeared distinct from it in both mitochondrial and nuclear markers. However, this study did not include genera closely allied to Hemidactylus, thus a robust evaluation of this hypothesis was not undertaken. Methods: The objective of this study was to investigate the phylogenetic position of H. anamallensis within the gekkonid radiation. To this end, several nuclear and mitochondrial markers were sequenced from H. anamallensis, selected members of the Hemidactylus radiation and genera closely allied to Hemidactylus. These sequences in conjunction with published sequences were subjected to multiple phylogenetic analyses. Furthermore the nuclear dataset was also subjected to molecular dating analysis to ascertain the divergence between H. anamallensis and related genera. Results and Conclusion: Results showed that H. anamallensis lineage was indeed sister to Hemidactylus group but was separated from the rest of the Hemidactylus by a long branch. The divergence estimates supported a scenario wherein H. anamallensis dispersed across a marine barrier to the drifting peninsular Indian plate in the late Cretaceous whereas Hemidactylus arrived on the peninsular India after the Indian plate collided with the Eurasian plate. Based on these molecular evidence and biogeographical scenario we suggest that the genus Dravidogecko should be resurrected.

State estimation in power systems using linear model infinity norm-based trust region approach

State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

Predictability and chaotic nature of daily streamflow

The predictability of a chaotic series is limited to a few future time steps due to its sensitivity to initial conditions and the exponential divergence of the trajectories. Over the years, streamflow has been considered as a stochastic system in many approaches. In this study, the chaotic nature of daily streamflow is investigated using autocorrelation function, Fourier spectrum, correlation dimension method (Grassberger-Procaccia algorithm) and false nearest neighbor method. Embedding dimensions of 6-7 obtained indicates the possible presence of low-dimensional chaotic behavior. The predictability of the system is estimated by calculating the system's Lyapunov exponent. A positive maximum Lyapunov exponent of 0.167 indicates that the system is chaotic and unstable with a maximum predictability of only 6 days. These results give a positive indication towards considering streamflow as a low dimensional chaotic system than as a stochastic system.

Did southern Western Ghats of peninsular India serve as refugia for its endemic biota during the Cretaceous volcanism?

The Western Ghats (WG) of south India, a global biodiversity hotspot, has experienced complex geological history being part of Gondwana landmass and encountered extensive volcanic activity at the end of Cretaceous epoch. It also has a climatically and topographically heterogeneous landscape. Thus, the WG offer a unique setting to explore the influence of ecological and geological processes on the current diversity and distribution of its biota. To this end, three explicit biogeographical scenarios were hypothesized to evaluate the distribution and diversification of wet evergreen species of the WG - (1) southern WG was a refuge for the wet evergreen species during the Cretaceous volcanism, (2) phylogenetic breaks in the species phylogeny would correspond to geographic breaks (i.e., the Palghat gap) in the WG, and (3) species from each of the biogeographic subdivisions within the WG would form distinct clades. These hypotheses were tested on the centipede genus Digitipes from the WG which is known to be an ancient, endemic, and monophyletic group. The Digitipes molecular phylogeny was subjected to divergence date estimation using Bayesian approach, and ancestral areas were reconstructed using parsimony approach for each node in the phylogeny. Ancestral-area reconstruction suggested 13 independent dispersal events to explain the current distribution of the Digitipes species in the WG. Among these 13 dispersals, two dispersal events were at higher level in the Digitipes phylogeny and were from the southern WG to the central and northern WG independently in the Early Paleocene, after the Cretaceous Volcanism. The remaining 11 dispersal events explained the species' range expansions of which nine dispersals were from the southern WG to other biogeographic subdivisions in the Eocene-Miocene in the post-volcanic periods where species-level diversifications occurred. Taken together, these results suggest that southern WG might have served as a refuge for Digitipes species during Cretaceous volcanism.

Dynamics of edge dislocations in a sheared lamellar mesophase

The dynamics and interactions of edge dislocations in a nearly aligned sheared lamellar mesophase is analysed to provide insights into the relationship between disorder and rheology. First, the mesoscale permeation and momentum equations for the displacement field in the presence of external forces are derived from the model H equations for the concentration and momentum field. The secondary flow generated due to the mean shear around an isolated defect is calculated, and the excess viscosity due to the presence of the defect is determined from the excess energy dissipation due to the secondary flow. The excess viscosity for an isolated defect is found to increase with system size in the cross-stream direction as L-3/2 for an isolated defect, though this divergence is cut-off due to interactions in a defect suspension. As the defects are sheared past each other due to the mean flow, the Peach-Koehler force due to elastic interaction between pairs of defects is found to cause no net displacement relative to each other as they approach from large separation to the distance of closest approach. The equivalent force due to viscous interactions is found to increase the separation for defects of opposite sign, and decrease the separation for defects of same sign. During defect interactions, we find that there is no buckling instability due to dilation of layers for systems of realistic size. However, there is another mechanism, which is the velocity difference generated across a slightly deformed bilayer due to the mean shear, which could result in the creation of new defects. (C) 2013 AIP Publishing LLC.

Filling-in Void and Sparse Regions in Protein Sequence Space by Protein-Like Artificial Sequences Enables Remarkable Enhancement in Remote Homology Detection Capability

Protein functional annotation relies on the identification of accurate relationships, sequence divergence being a key factor. This is especially evident when distant protein relationships are demonstrated only with three-dimensional structures. To address this challenge, we describe a computational approach to purposefully bridge gaps between related protein families through directed design of protein-like ``linker'' sequences. For this, we represented SCOP domain families, integrated with sequence homologues, as multiple profiles and performed HMM-HMM alignments between related domain families. Where convincing alignments were achieved, we applied a roulette wheel-based method to design 3,611,010 protein-like sequences corresponding to 374 SCOP folds. To analyze their ability to link proteins in homology searches, we used 3024 queries to search two databases, one containing only natural sequences and another one additionally containing designed sequences. Our results showed that augmented database searches showed up to 30% improvement in fold coverage for over 74% of the folds, with 52 folds achieving all theoretically possible connections. Although sequences could not be designed between some families, the availability of designed sequences between other families within the fold established the sequence continuum to demonstrate 373 difficult relationships. Ultimately, as a practical and realistic extension, we demonstrate that such protein-like sequences can be ``plugged-into'' routine and generic sequence database searches to empower not only remote homology detection but also fold recognition. Our richly statistically supported findings show that complementary searches in both databases will increase the effectiveness of sequence-based searches in recognizing all homologues sharing a common fold. (C) 2013 Elsevier Ltd. All rights reserved.

Generative Maximum Entropy Learning for Multiclass Classification

Maximum entropy approach to classification is very well studied in applied statistics and machine learning and almost all the methods that exists in literature are discriminative in nature. In this paper, we introduce a maximum entropy classification method with feature selection for large dimensional data such as text datasets that is generative in nature. To tackle the curse of dimensionality of large data sets, we employ conditional independence assumption (Naive Bayes) and we perform feature selection simultaneously, by enforcing a `maximum discrimination' between estimated class conditional densities. For two class problems, in the proposed method, we use Jeffreys (J) divergence to discriminate the class conditional densities. To extend our method to the multi-class case, we propose a completely new approach by considering a multi-distribution divergence: we replace Jeffreys divergence by Jensen-Shannon (JS) divergence to discriminate conditional densities of multiple classes. In order to reduce computational complexity, we employ a modified Jensen-Shannon divergence (JS(GM)), based on AM-GM inequality. We show that the resulting divergence is a natural generalization of Jeffreys divergence to a multiple distributions case. As far as the theoretical justifications are concerned we show that when one intends to select the best features in a generative maximum entropy approach, maximum discrimination using J-divergence emerges naturally in binary classification. Performance and comparative study of the proposed algorithms have been demonstrated on large dimensional text and gene expression datasets that show our methods scale up very well with large dimensional datasets.

Fermi-Edge Transmission Resonance in Graphene Driven by a Single Coulomb Impurity

The interaction between the Fermi sea of conduction electrons and a nonadiabatic attractive impurity potential can lead to a power-law divergence in the tunneling probability of charge through the impurity. The resulting effect, known as the Fermi edge singularity (FES), constitutes one of the most fundamental many-body phenomena in quantum solid state physics. Here we report the first observation of FES for Dirac fermions in graphene driven by isolated Coulomb impurities in the conduction channel. In high-mobility graphene devices on hexagonal boron nitride substrates, the FES manifests in abrupt changes in conductance with a large magnitude approximate to e(2)/h at resonance, indicating total many-body screening of a local Coulomb impurity with fluctuating charge occupancy. Furthermore, we exploit the extreme sensitivity of graphene to individual Coulomb impurities and demonstrate a new defect-spectroscopy tool to investigate strongly correlated phases in graphene in the quantum Hall regime.