Energy funneling and macromolecular conformational dynamics: a 2D Raman correlation study of PEG melting

Cascading energy landscapes through funneling has been postulated as a mechanistic route for achieving the lowest energy configuration of a macromolecular system (such as proteins and polymers). In particular, understanding the molecular mechanism for the melting and crystallization of polymers is a challenging fundamental question. The structural modifications that lead to the melting of poly(ethylene glycol) (PEG) are investigated here. Specific Raman bands corresponding to different configurations of the PEG chain have been identified, and the molecular structural dynamics of PEG melting have been addressed using a combination of Raman spectroscopy, 2D Raman correlation and density functional theory (DFT) calculations. The melting dynamics of PEG have been unambiguously explained along the C-O bond rotation coordinate.

Loss of frugivore seed dispersal services under climate change

The capacity of species to track shifting climates into the future will strongly influence outcomes for biodiversity under a rapidly changing climate. However, we know remarkably little about the dispersal abilities of most species and how these may be influenced by climate change. Here we show that climate change is projected to substantially reduce the seed dispersal services provided by frugivorous vertebrates in rainforests across the Australian Wet Tropics. Our model projections show reductions in both median and long-distance seed dispersal, which may markedly reduce the capacity of many rainforest plant species to track shifts in suitable habitat under climate change. However, our analyses suggest that active management to maintain the abundances of a small set of important frugivores under climate change could markedly reduce the projected loss of seed dispersal services and facilitate shifting distributions of rainforest plant species.

Fienup Algorithm With Sparsity Constraints: Application to Frequency-Domain Optical-Coherence Tomography

We address the problem of reconstructing a sparse signal from its DFT magnitude. We refer to this problem as the sparse phase retrieval (SPR) problem, which finds applications in tomography, digital holography, electron microscopy, etc. We develop a Fienup-type iterative algorithm, referred to as the Max-K algorithm, to enforce sparsity and successively refine the estimate of phase. We show that the Max-K algorithm possesses Cauchy convergence properties under certain conditions, that is, the MSE of reconstruction does not increase with iterations. We also formulate the problem of SPR as a feasibility problem, where the goal is to find a signal that is sparse in a known basis and whose Fourier transform magnitude is consistent with the measurement. Subsequently, we interpret the Max-K algorithm as alternating projections onto the object-domain and measurement-domain constraint sets and generalize it to a parameterized relaxation, known as the relaxed averaged alternating reflections (RAAR) algorithm. On the application front, we work with measurements acquired using a frequency-domain optical-coherence tomography (FDOCT) experimental setup. Experimental results on measured data show that the proposed algorithms exhibit good reconstruction performance compared with the direct inversion technique, homomorphic technique, and the classical Fienup algorithm without sparsity constraint; specifically, the autocorrelation artifacts and background noise are suppressed to a significant extent. We also demonstrate that the RAAR algorithm offers a broader framework for FDOCT reconstruction, of which the direct inversion technique and the proposed Max-K algorithm become special instances corresponding to specific values of the relaxation parameter.

MolBridge: a program for identifying nonbonded interactions in small molecules and biomolecular structures

Identification and analysis of nonbonded interactions within a molecule and with the surrounding molecules are an essential part of structural studies, given the importance of these interactions in defining the structure and function of any supramolecular entity. MolBridge is an easy to use algorithm based purely on geometric criteria that can identify all possible nonbonded interactions, such as hydrogen bond, halogen bond, cation-pi, pi-pi and van der Waals, in small molecules as well as biomolecules. The user can either upload three-dimensional coordinate files or enter the molecular ID corresponding to the relevant database. The program is available in a standalone form and as an interactive web server with Jmol and JME incorporated into it. The program is freely downloadable and the web server version is also available at http://nucleix.mbu.iisc.ernet.in/molbridge/index.php.

Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

Capturability Analysis of a 3-D Retro-PN Guidance Law for Higher Speed Nonmaneuvering Targets

This brief presents the capturability analysis of a 3-D Retro-proportional navigation (Retro-PN) guidance law, which uses a negative navigation constant (as against the usual positive one), for intercepting targets having higher speeds than interceptors. This modification makes it possible to achieve collision conditions that were inaccessible to the standard PN law. A modified polar coordinate system, that makes the model more compact, is used in this brief for capturability analysis. In addition to the ratio of the target to interceptor speeds, the directional cosines of the interceptor, and target velocity vectors play a crucial role in the capturability. The existence of nontrivial capture zone of the Retro-PN guidance law and necessary and sufficient conditions, for capturing the target in finite time, are presented. A sufficient condition on the navigation constant is derived to ensure finiteness of the line-of-sight turn rate. The results are more extensive than those available for 2-D engagements, which can be obtained as special cases of this brief. Simulation results are given to support the analytical results.

ELLIPSE FITTING USING FINITE RATE OF INNOVATION PRINCIPLES

We address the problem of parameter estimation of an ellipse from a limited number of samples. We develop a new approach for solving the ellipse fitting problem by showing that the x and y coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals. Uniform samples of x and y coordinate functions of the ellipse are modeled as a sum of weighted complex exponentials, for which we propose an efficient annihilating filter technique to estimate the ellipse parameters from the samples. The FRI framework allows for estimating the ellipse parameters reliably from partial or incomplete measurements even in the presence of noise. The efficiency and robustness of the proposed method is compared with state-of-art direct method. The experimental results show that the estimated parameters have lesser bias compared with the direct method and the estimation error is reduced by 5-10 dB relative to the direct method.

Return levels of hydrologic droughts under climate change

Developments in the statistical extreme value theory, which allow non-stationary modeling of changes in the frequency and severity of extremes, are explored to analyze changes in return levels of droughts for the Colorado River. The transient future return levels (conditional quantiles) derived from regional drought projections using appropriate extreme value models, are compared with those from observed naturalized streamflows. The time of detection is computed as the time at which significant differences exist between the observed and future extreme drought levels, accounting for the uncertainties in their estimates. Projections from multiple climate model-scenario combinations are considered; no uniform pattern of changes in drought quantiles is observed across all the projections. While some projections indicate shifting to another stationary regime, for many projections which are found to be non-stationary, detection of change in tail quantiles of droughts occurs within the 21st century with no unanimity in the time of detection. Earlier detection is observed in droughts levels of higher probability of exceedance. (C) 2014 Elsevier Ltd. All rights reserved.

Space-Time Coded Spatial Modulated Physical Layer Network Coding for Two-Way Relaying

Using the spatial modulation approach, where only one transmit antenna is active at a time, we propose two transmission schemes for two-way relay channel using physical layer network coding with space time coding using coordinate interleaved orthogonal designs (CIODs). It is shown that using two uncorrelated transmit antennas at the nodes, but using only one RF transmit chain and space-time coding across these antennas can give a better performance without using any extra resources and without increasing the hardware implementation cost and complexity. In the first transmission scheme, two antennas are used only at the relay, adaptive network coding (ANC) is employed at the relay and the relay transmits a CIOD space time block code (STBC). This gives a better performance compared to an existing ANC scheme for two-way relay channel which uses one antenna each at all the three nodes. It is shown that for this scheme at high SNR the average end-to-end symbol error probability (SEP) is upper bounded by twice the SEP of a point-to-point fading channel. In the second transmission scheme, two transmit antennas are used at all the three nodes, CIOD STBCs are transmitted in multiple access and broadcast phases. This scheme provides a diversity order of two for the average end-to-end SEP with an increased decoding complexity of O(M-3) for an arbitrary signal set and O(M-2 root M) for square QAM signal set. Simulation results show that the proposed schemes performs better than the existing ANC schemes under perfect and imperfect channel state information.

A trade-off between maxima in efficiency and specific work output of super- and trans-critical CO2 Brayton cycles

Several operational aspects for thermal power plants in general are non-intuitive and involve simultaneous optimization of a number of operational parameters. In the case of solar operated power plants, it is even more difficult due to varying heat source temperatures induced by variability in insolation levels. This paper introduces a quantitative methodology for load regulation of a CO2 based Brayton cycle power plant using the `thermal efficiency and specific work output' coordinate system. The analysis shows that a transcritical CO2 cycle offers more flexibility under part load performance than the supercritical cycle in case of non-solar power plants. However, for concentrated solar power, where efficiency is important, supercritical CO2 cycle fares better than transcritical CO2 cycle. A number of empirical equations relating heat source temperature, high side pressure with efficiency and specific work output are proposed which could assist in generating control algorithms. (C) 2015 Elsevier B.V. All rights reserved.

GLOBAL REGISTRATION OF MULTIPLE POINT CLOUDS USING SEMIDEFINITE PROGRAMMING

Consider N points in R-d and M local coordinate systems that are related through unknown rigid transforms. For each point, we are given (possibly noisy) measurements of its local coordinates in some of the coordinate systems. Alternatively, for each coordinate system, we observe the coordinates of a subset of the points. The problem of estimating the global coordinates of the N points (up to a rigid transform) from such measurements comes up in distributed approaches to molecular conformation and sensor network localization, and also in computer vision and graphics. The least-squares formulation of this problem, although nonconvex, has a well-known closed-form solution when M = 2 (based on the singular value decomposition (SVD)). However, no closed-form solution is known for M >= 3. In this paper, we demonstrate how the least-squares formulation can be relaxed into a convex program, namely, a semidefinite program (SDP). By setting up connections between the uniqueness of this SDP and results from rigidity theory, we prove conditions for exact and stable recovery for the SDP relaxation. In particular, we prove that the SDP relaxation can guarantee recovery under more adversarial conditions compared to earlier proposed spectral relaxations, and we derive error bounds for the registration error incurred by the SDP relaxation. We also present results of numerical experiments on simulated data to confirm the theoretical findings. We empirically demonstrate that (a) unlike the spectral relaxation, the relaxation gap is mostly zero for the SDP (i.e., we are able to solve the original nonconvex least-squares problem) up to a certain noise threshold, and (b) the SDP performs significantly better than spectral and manifold-optimization methods, particularly at large noise levels.

Implication of a sigma-Methane Complex en Route to Elimination of Methane from a Ruthenium Complex: An Experimental and Theoretical Investigation

The five-coordinated 16-electron complex Ru(Me)(dppe)(2)]OTf] (3) undergoes methane elimination at room temperature to afford the ortho-metalated species (dppe){(C6H5)(C6H4)PCH2CH2P(C6H5)(2)}Ru]OTf] (7). Methane elimination, monitored using NMR spectroscopy, revealed no intermediate throughout the reaction. The NOE between Ru-Me protons and ortho phenyl protons and an agostic interaction trans to the methyl group were found in complex 3 by NMR spectroscopy, which form the basis for three plausible pathways for methane elimination and ortho metalation: pathway I (through spatial interaction), pathway II (through oxidative addition and reductive elimination), and pathway III (through agostic interaction). Methane elimination from complex 3 via pathway I was discounted, since it involves interactions through space and not through bonds. Moreover, the calculated energy barrier for the pathway I transition state was quite high (71.3 kcal/mol), which also indicates that this pathway is very unlikely. Furthermore, no spectroscopic evidence for oxidatively added seven-coordinated Ru(IV) species was found and the computed energy barrier of the transition state for pathway II was moderately high (41.1 kcal/mol), which suggests that this cannot be the right pathway for methane elimination and ortho-metalation of complex 3. On the other hand, indirect evidence in the form of chemical reactions point to the most plausible pathway for methane elimination, pathway III, via the intermediacy of a sigma-CH4 complex that could not be found spectroscopically. DFT calculations at several levels on this pathway showed an initial low-barrier rearrangement through TS1 to a square-pyramidal intermediate wherein methyl and agostic C-H are cis to each other. Migration of hydrogen from agostic C-H and elimination of methane proceed through the transition state TS2, which retains a weak metal-H bonding through most parts of the reaction coordinate. Upon comparison of all three pathways, pathway III was found to be the most likely for methane elimination and ortho-metalation of complex 3.

Iron(III) Complexes of a Pyridoxal Schiff Base for Enhanced Cellular Uptake with Selectivity and Remarkable Photocytotoxicity

Iron(III) complexes of pyridoxal (vitamin B6, VB6) or salicylaldehyde Schiff bases and modified dipicolylamines, namely, Fe(B)(L)](NO3) (15), where B is phenyl-N,N-bis((pyridin-2-yl)methyl)methanamine (phbpa in 1), (anthracen-9-yl)-N,N-bis((pyridin-2-yl)methyl)methanamine (anbpa in 2, 4) and (pyren-1-yl)-N,N-bis((pyridin-2-yl)methyl)methanamine (pybpa in 3, 5) (H2L1 is 3-hydroxy-5-(hydroxymethyl)-4-(((2-hydroxyphenyl)imino)methyl)-2-methylp yridine (13) and H2L2 is 2-(2-hydroxyphenyl-imino)methyl]phenol), were prepared and their uptake in cancer cells and photocytotoxicity were studied. Complexes 4 and 5, having a non-pyridoxal Schiff base, were prepared to probe the role of the pyridoxal group in tumor targeting and cellular uptake. The PF6 salt (1a) of complex 1 is structurally characterized. The complexes have a distorted six-coordinate FeN4O2 core where the metal is in the +3 oxidation state with five unpaired electrons. The complexes display a ligand to metal charge transfer band near 520 and 420 nm from phenolate to the iron(III) center. The photophysical properties of the complexes are explained from the time dependent density functional theory calculations. The redox active complexes show a quasi-reversible Fe(III)/Fe(II) response near -0.3 V vs saturated calomel electrode. Complexes 2 and 3 exhibit remarkable photocytotoxicity in various cancer cells with IC50 values ranging from 0.4 to 5 mu M with 10-fold lower dark toxicity. The cell death proceeded by the apoptotic pathway due to generation of reactive oxygen species upon light exposure. The nonvitamin complexes 4 and 5 display 3-fold lower photocytotoxicity compared to their VB6 analogues, possibly due to preferential and faster uptake of the vitamin complexes in the cancer cells. Complexes 2 and 3 show significant uptake in the endoplasmic reticulum, while complexes 4 and 5 are distributed throughout the cells without any specific localization pattern.

Online_DPI: a web server to calculate the diffraction precision index for a protein structure

An online computing server, Online_DPI (where DPI denotes the diffraction precision index), has been created to calculate the `Cruickshank DPI' value for a given three-dimensional protein or macromolecular structure. It also estimates the atomic coordinate error for all the atoms available in the structure. It is an easy-to-use web server that enables users to visualize the computed values dynamically on the client machine. Users can provide the Protein Data Bank (PDB) identification code or upload the three-dimensional atomic coordinates from the client machine. The computed DPI value for the structure and the atomic coordinate errors for all the atoms are included in the revised PDB file. Further, users can graphically view the atomic coordinate error along with `temperature factors' (i.e. atomic displacement parameters). In addition, the computing engine is interfaced with an up-to-date local copy of the Protein Data Bank. New entries are updated every week, and thus users can access all the structures available in the Protein Data Bank. The computing engine is freely accessible online at http://cluster.physics.iisc.ernet.in/dpi/.

Detection of a quantum particle on a lattice under repeated projective measurements

We consider a quantum particle, moving on a lattice with a tight-binding Hamiltonian, which is subjected to measurements to detect its arrival at a particular chosen set of sites. The projective measurements are made at regular time intervals tau, and we consider the evolution of the wave function until the time a detection occurs. We study the probabilities of its first detection at some time and, conversely, the probability of it not being detected (i.e., surviving) up to that time. We propose a general perturbative approach for understanding the dynamics which maps the evolution operator, which consists of unitary transformations followed by projections, to one described by a non-Hermitian Hamiltonian. For some examples of a particle moving on one-and two-dimensional lattices with one or more detection sites, we use this approach to find exact expressions for the survival probability and find excellent agreement with direct numerical results. A mean-field model with hopping between all pairs of sites and detection at one site is solved exactly. For the one-and two-dimensional systems, the survival probability is shown to have a power-law decay with time, where the power depends on the initial position of the particle. Finally, we show an interesting and nontrivial connection between the dynamics of the particle in our model and the evolution of a particle under a non-Hermitian Hamiltonian with a large absorbing potential at some sites.