NON-GLYCINE RESIDUES IN THE DISALLOWED REGIONS OF THE RAMACHANDRAN MAP AND THEIR NEIGHBORHOOD PREFERENCES

The allowed and the ``disallowed'' regions in the celebrated Ramachandran map (phi-psi] map) was elegantly deduced by Ramachandran, Ramakrishnan and Sasisekharan even before the protein crystal structures became available. This powerful map was derived based on rigid geometry of the peptide group and later several investigations on protein crystal structures reported the occurrence of a small fraction of the phi-psi] torsion angles in the disallowed region. The question is what factors make these residues adopt disallowed conformations? Is it driven by the necessity to maintain the overall topology or is it associated with function or is it just that the disallowed conformations are extreme limits of the allowed conformations? Today, with the availability of a large number of high resolution crystal structures, we have revisited this problem. Apart from validating some of the earlier findings such as residue propensities, preferred location in the secondary structure, we have explored their spatial neighborhood preferences using the protein structure network PSN] approach developed in our lab. Finally, the structural and functional implications of the disallowed conformations are examined.

PROPENSITIES OF AMINO ACID RESIDUES IN PROTEINS FOR DIFFERENT REGIONS OF THE RAMACHANDRAN MAP

Using a dataset of 1164 crystal structures of largely non-homologous proteins defined at a resolution of 1.5 angstrom or better, we have investigated the (phi,psi) preferences of 20 residue types by considering the residues which occur in loops. Propensities of residue types to occur in the loops with (phi,psi) values in the aa region of the Ramachandran map has a poor correlation coefficient of 0.48 to the Chou-Fasman propensities of the residue types to occur in the a-helical segments. However the correlation coefficient between propensities of residues in loops to adopt beta conformations and those in beta-sheet is much higher (0.95). These observations suggest that a-helix formation is well influenced by the local amino acid sequence while intrinsic preference of residue types for beta-sheet plays a major role in the formation of beta-sheet. The main chain polar groups of residues in loops, that can affect the (phi,psi) values, can be involved in intra-molecular hydrogen bonding. Therefore we investigated further by considering subset of residues in loops with low (0 to 2) number of intra-molecular hydrogen bonds per residue involving main chain polar atoms. For this subset, the correlation coefficients between propensities for alpha-helix and alpha(R) region and between beta-sheet and beta-region are 0.26 and 0.64 respectively. This reiterates higher intrinsic tendency of beta-region favouring residues to adopt beta-sheet than alpha(R) region favouring residues to adopt alpha-helical structure.

Hot deformation behavior of Ni-Fe-Ga-based ferromagnetic shape memory alloy - A study using processing map

Ni-Fe-Ga-based alloys form a new class of ferromagnetic shape memory alloys (FSMAs) that show considerable formability because of the presence of a disordered fcc gamma-phase. The current study explores the deformation processing of this alloy using an off-stoichiometric Ni55Fe59Ga26 alloy that contains the ductile gamma-phase. The hot deformation behavior of this alloy has been characterized on the basis of its flow stress variation obtained by isothermal constant true strain rate compression tests in the 1123-1323 K temperature range and strain rate range of 10(-3)-10 s(-1) and using a combination of constitutive modeling and processing map. The dynamic recrystallization (DRX) regime for thermomechanical processing has been identified for this Heusler alloy on the basis of the processing maps and the deformed microstructures. This alloy also shows evidence of dynamic strain-aging (DSA) effect which has not been reported so far for any Heusler FSMAs. Similar effect is also noticed in a Ni-Mn-Ga-based Heusler alloy which is devoid of any gamma-phase. (C) 2014 Elsevier Ltd. All rights reserved.

An Unusual Ring-Contraction/Rearrangement Sequence for Making Functionalized Di- and Triquinanes

A novel ring contraction/rearrangement sequence leading to functionalized 2,8-oxymethano-bridged di- and triquinane compounds is observed in the reaction of various substituted 1-methyl-4-isopropenyl-6-oxabicylo3.2.1]octan-8-ones with Lewis acids. The reaction is novel and is unprecedented for the synthesis of di- and triquinane frameworks.

An Unusual Ring-Contraction/Rearrangement Sequence for Making Functionalized Di- and Triquinanes

A novel ring contraction/rearrangement sequence leading to functionalized 2,8-oxymethano-bridged di- and triquinane compounds is observed in the reaction of various substituted 1-methyl-4-isopropenyl-6-oxabicylo3.2.1]octan-8-ones with Lewis acids. The reaction is novel and is unprecedented for the synthesis of di- and triquinane frameworks.

An Unusual Ring-Contraction/Rearrangement Sequence for Making Functionalized Di- and Triquinanes

A novel ring contraction/rearrangement sequence leading to functionalized 2,8-oxymethano-bridged di- and triquinane compounds is observed in the reaction of various substituted 1-methyl-4-isopropenyl-6-oxabicylo3.2.1]octan-8-ones with Lewis acids. The reaction is novel and is unprecedented for the synthesis of di- and triquinane frameworks.

Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data

Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged derision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 x 10(6) km(2)), mean annual maximum (12.1 x 10(6) km(2)), and long-term maximum (173 x 10(6) km(2)); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations. (C) 2014 Elsevier Inc All rights reserved.

Optical Flow based on Approximate Nearest Neighbor Field

In this work, we propose an algorithm for optical flow estimation using Approximate Nearest Neighbor Fields (ANNF). Proposed optical flow estimation algorithm consists of two steps, flow initialization using ANNF maps and cost filtering. Flow initialization is done by computing the ANNF map using FeatureMatch between two consecutive frames. The ANNF map obtained represents a noisy optical flow, which is refined by making use of superpixels. The best flow associated with each superpixel is computed by optimizing a cost function. The proposed approach is evaluated on Middlebury and MPI-Sintel optical flow dataset and is found to be comparable with the state of the art methods for optical flow estimation.

High-Temperature Deformation Processing Map Approach for Obtaining the Desired Microstructure in a Multi-component (Ni-Ti-Cu-Fe) Alloy

An equiatomic NiTiCuFe multi-component alloy with simple body-centered cubic (bcc) and face-centered cubic solid-solution phases in the microstructure was processed by vacuum induction melting furnace under dynamic Ar atmosphere. High-temperature uniaxial compression experiments were conducted on it in the temperature range of 1073 K to 1303 K (800 degrees C to 1030 degrees C) and strain rate range of 10(-3) to 10(-1) s(-1). The data generated were analyzed with the aid of the dynamic materials model through which power dissipation efficiency and instability maps were generated so as to identify the governing deformation mechanisms that are operative in different temperature-strain rate regimes with the aid of complementary microstructural analysis of the deformed specimens. Results indicate that the stable domain for the high temperature deformation of the multi-component alloy occurs in the temperature range of 1173 K to 1303 K (900 degrees C to 1030 degrees C) and (epsilon) over dot range of 10(-3) to 10(-1.2) s(-1), and the deformation is unstable at T = 1073 K to 1153 K (800 degrees C to 880 degrees C) and (epsilon) over dot = 10(-3) to 10(-1.4) s(-1) as well as T = 1223 K to 1293 K (950 degrees C to 1020 degrees C) and (epsilon) over dot = 10(-1.4) to 10(-1) s(-1), with adiabatic shear banding, localized plastic flow, or cracking being the unstable mechanisms. A constitutive equation that describes the flow stress of NiTiCuFe multi-component alloy as a function of strain rate and deformation temperature was also determined. (C) The Minerals, Metals & Materials Society and ASM International 2015

Making risk minimization tolerant to label noise

In many applications, the training data, from which one needs to learn a classifier, is corrupted with label noise. Many standard algorithms such as SVM perform poorly in the presence of label noise. In this paper we investigate the robustness of risk minimization to label noise. We prove a sufficient condition on a loss function for the risk minimization under that loss to be tolerant to uniform label noise. We show that the 0-1 loss, sigmoid loss, ramp loss and probit loss satisfy this condition though none of the standard convex loss functions satisfy it. We also prove that, by choosing a sufficiently large value of a parameter in the loss function, the sigmoid loss, ramp loss and probit loss can be made tolerant to nonuniform label noise also if we can assume the classes to be separable under noise-free data distribution. Through extensive empirical studies, we show that risk minimization under the 0-1 loss, the sigmoid loss and the ramp loss has much better robustness to label noise when compared to the SVM algorithm. (C) 2015 Elsevier B.V. All rights reserved.

Imaging cellular signalling: many `moving tales' in MAP kinase odyssey

Cellular signalling events are at the core of every adaptive response. Signalling events link environmental changes to physiological responses, consequently allowing cellular and organismal sustenance and survival. Classical approaches to study cellular signalling have relied on a variety of cell disruptive techniques which yield limited kinetic information, while the underlying events are much more complex. In this article, we discuss how modern live cell imaging microscopy has found increasing utilization in revealing spatio temporal dynamics of various signalling pathways. Utilizing the well studied mitogen-activated protein kinase (MAPK) signalling cascade as a template, the design, construction and utilization of `mobile' (translocation proficient) biosensors, suitable for studying MAPK signalling in living cells are described in detail. Experimental setup and results obtained from these biosensors, based on different proteins involved in the MAPK signalling cascade, have been described along with the setup of a microscope optimal for live cell imaging applications. Utilizing the ability to activate or deactivate signalling pathways using defined activators and specific pharmacological inhibitors, we also show how these sensors can yield unique spatial and temporal kinetic information of signalling in living cells.

Seismic intensity map of South India for estimated future earthquakes

In this study, an attempt has been made to prepare the seismic intensity map for south India considering the probable earthquakes in the region. Anbazhagan et al. (Nat Hazards 60:1325-1345, 2012) have identified eight probable future earthquake zones in south India based on rupture-based seismic hazard analysis. Anbazhagan et al. (Eng Geol 171:81-95, 2014) has estimated the maximum future earthquake magnitude at these eight zones using regional rupture character. In this study, the whole south India is divided into several grids of size 1(o) x 1(o) and the intensity at each grid point is calculated using the regional intensity model for the maximum earthquake magnitude at each of the eight zones. The intensity due to earthquakes at these zones is mapped and thus eight seismic intensity maps are prepared. The final seismic intensity map of south India is obtained by considering the maximum intensity at each grid point due to the estimated earthquakes. By looking at the seismic intensity map, one can expect slight to heavy damage due to the probable earthquake magnitudes. Heavy damage may happen close to the probable earthquake zones.

Photometric metallicity map of the Large Magellanic Cloud

We have estimated a metallicity map of the Large Magellanic Cloud (LMC) using the Magellanic Cloud Photometric Survey (MCPS) and Optical Gravitational Lensing Experiment (OGLE III) photometric data. This is a first of its kind map of metallicity up to a radius of 4 degrees-5 degrees, derived using photometric data and calibrated using spectroscopic data of Red Giant Branch (RGB) stars. We identify the RGB in the V, (V - I) colour-magnitude diagrams of small subregions of varying sizes in both data sets. We use the slope of the RGB as an indicator of the average metallicity of a subregion, and calibrate the RGB slope to metallicity using spectroscopic data for field and cluster red giants in selected subregions. The average metallicity of the LMC is found to be Fe/H] = -0.37 dex (sigmaFe/H] = 0.12) from MCPS data, and Fe/H] = -0.39 dex (sigmaFe/H] = 0.10) from OGLE III data. The bar is found to be the most metal-rich region of the LMC. Both the data sets suggest a shallow radial metallicity gradient up to a radius of 4 kpc (-0.049 +/- 0.002 dex kpc(-1) to -0.066 +/- 0.006 dex kpc(-1)). Subregions in which the mean metallicity differs from the surrounding areas do not appear to correlate with previously known features; spectroscopic studies are required in order to assess their physical significance.

Spatio-temporal Map Formation Based on a Potential Function

We revisit the problem of temporal self organization using activity diffusion based on the neural gas (NGAS) algorithm. Using a potential function formulation motivated by a spatio-temporal metric, we derive an adaptation rule for dynamic vector quantization of data. Simulations results show that our algorithm learns the input distribution and time correlation much faster compared to the static neural gas method over the same data sequence under similar training conditions.

Wild Ungulate Decision-Making and the Role of Tiny Refuges in Human-Dominated Landscapes

Wildlife conservation in human-dominated landscapes requires that we understand how animals, when making habitat-use decisions, obtain diverse and dynamically occurring resources while avoiding risks, induced by both natural predators and anthropogenic threats. Little is known about the underlying processes that enable wild animals to persist in densely populated human-dominated landscapes, particularly in developing countries. In a complex, semi-arid, fragmented, human-dominated agricultural landscape, we analyzed the habitat-use of blackbuck, a large herbivore endemic to the Indian sub-continent. We hypothesized that blackbuck would show flexible habitat-use behaviour and be risk averse when resource quality in the landscape is high, and less sensitive to risk otherwise. Overall, blackbuck appeared to be strongly influenced by human activity and they offset risks by using small protected patches (similar to 3 km(2)) when they could afford to do so. Blackbuck habitat use varied dynamically corresponding with seasonally-changing levels of resources and risks, with protected habitats registering maximum use. The findings show that human activities can strongly influence and perhaps limit ungulate habitat-use and behaviour, but spatial heterogeneity in risk, particularly the presence of refuges, can allow ungulates to persist in landscapes with high human and livestock densities.