Learning-Based Fast Iterative Convergence of 3-D MoM via Eigen-AGMRES Method

Three-dimensional (3-D) full-wave electromagnetic simulation using method of moments (MoM) under the framework of fast solver algorithms like fast multipole method (FMM) is often bottlenecked by the speed of convergence of the Krylov-subspace-based iterative process. This is primarily because the electric field integral equation (EFIE) matrix, even with cutting-edge preconditioning techniques, often exhibits bad spectral properties arising from frequency or geometry-based ill-conditioning, which render iterative solvers slow to converge or stagnate occasionally. In this communication, a novel technique to expedite the convergence of MoMmatrix solution at a specific frequency is proposed, by extracting and applying Eigen-vectors from a previously solved neighboring frequency in an augmented generalized minimum residual (AGMRES) iterative framework. This technique can be applied in unison with any preconditioner. Numerical results demonstrate up to 40% speed-up in convergence using the proposed Eigen-AGMRES method.

Fast and slow climate responses to CO2 and solar forcing: A linear multivariate regression model characterizing transient climate change

Climate change in response to a change in external forcing can be understood in terms of fast response to the imposed forcing and slow feedback associated with surface temperature change. Previous studies have investigated the characteristics of fast response and slow feedback for different forcing agents. Here we examine to what extent that fast response and slow feedback derived from time-mean results of climate model simulations can be used to infer total climate change. To achieve this goal, we develop a multivariate regression model of climate change, in which the change in a climate variable is represented by a linear combination of its sensitivity to CO2 forcing, solar forcing, and change in global mean surface temperature. We derive the parameters of the regression model using time-mean results from a set of HadCM3L climate model step-forcing simulations, and then use the regression model to emulate HadCM3L-simulated transient climate change. Our results show that the regression model emulates well HadCM3L-simulated temporal evolution and spatial distribution of climate change, including surface temperature, precipitation, runoff, soil moisture, cloudiness, and radiative fluxes under transient CO2 and/or solar forcing scenarios. Our findings suggest that temporal and spatial patterns of total change for the climate variables considered here can be represented well by the sum of fast response and slow feedback. Furthermore, by using a simple 1-D heat-diffusion climate model, we show that the temporal and spatial characteristics of climate change under transient forcing scenarios can be emulated well using information from step-forcing simulations alone.

Anodization of Aluminium using a fast two-step process

Ultra-fast two-step anodization method is developed for obtaining ordered nano-pores on aluminium (Al) foil. First anodization was carried out for 10 min, followed by 3 min of second anodization at high voltage (150 V) compared to previous reports of anodization times of 12 h (40-60 V). The pore dimensions on anodized alumina are 180 nm for pore diameter and 130 nm for inter-pore distance. It was evident that by increasing the anodization voltage to 150 V, the diameter of the pores formed was above 150 nm. The electrolyte and its temperature affect the shape and size of the pore formation. At lower anodization temperature, controlled pore formation was observed. The anodized samples were characterized using the field emission scanning electron microscope (FE-SEM) to determine the pore diameter and inter-pore distance. Using UV-Visible spectroscopy, the reflectance spectra of anodized samples were measured. The alumina (Al2O3) peaks were identified by x-ray diffraction (XRD) technique. The x-ray photo electron spectroscopy (XPS) analysis confirmed the Al 2p peak at 73.1 eV along with the oxygen O 1s at 530.9 eV and carbon traces C 1s at 283.6 eV.

Sandwiched assembly of ZnO nanowires between graphene layers for a self-powered and fast responsive ultraviolet photodetector

A heterostructure of graphene and zinc oxide (ZnO) nanowires (NWs) is fabricated by sandwiching an array of ZnO NWs between two graphene layers for an ultraviolet (UV) photodetector. This unique structure allows NWs to be in direct contact with the graphene layers, minimizing the effect of the substrate or metal electrodes. In this device, graphene layers act as highly conducting electrodes with a high mobility of the generated charge carriers. An excellent sensitivity is demonstrated towards UV illumination, with a reversible photoresponse even for a short period of UV illumination. Response and recovery times of a few milliseconds demonstrated a much faster photoresponse than most of the conventional ZnO nanostructure-based photodetectors. It is shown that the generation of a built-in electric field between the interface of graphene and ZnO NWs effectively contributes to the separation of photogenerated electron-hole pairs for photocurrent generation without applying any external bias. Upon application of external bias voltage, the electric field further increases the drift velocity of photogenerated electrons by reducing the charge recombination rates, and results in an enhancement of the photocurrent. Therefore, the graphene-based heterostructure (G/ZnO NW/G) opens avenues to constructing a novel heterostructure with a combination of two functionally dissimilar materials.

Sandwiched assembly of ZnO nanowires between graphene layers for a self-powered and fast responsive ultraviolet photodetector

A heterostructure of graphene and zinc oxide (ZnO) nanowires (NWs) is fabricated by sandwiching an array of ZnO NWs between two graphene layers for an ultraviolet (UV) photodetector. This unique structure allows NWs to be in direct contact with the graphene layers, minimizing the effect of the substrate or metal electrodes. In this device, graphene layers act as highly conducting electrodes with a high mobility of the generated charge carriers. An excellent sensitivity is demonstrated towards UV illumination, with a reversible photoresponse even for a short period of UV illumination. Response and recovery times of a few milliseconds demonstrated a much faster photoresponse than most of the conventional ZnO nanostructure-based photodetectors. It is shown that the generation of a built-in electric field between the interface of graphene and ZnO NWs effectively contributes to the separation of photogenerated electron-hole pairs for photocurrent generation without applying any external bias. Upon application of external bias voltage, the electric field further increases the drift velocity of photogenerated electrons by reducing the charge recombination rates, and results in an enhancement of the photocurrent. Therefore, the graphene-based heterostructure (G/ZnO NW/G) opens avenues to constructing a novel heterostructure with a combination of two functionally dissimilar materials.

Stimuli-responsive colorimetric and NIR fluorescence combination probe for selective reporting of cellular hydrogen peroxide

Hydrogen peroxide (H2O2) is a key reactive oxygen species and a messenger in cellular signal transduction apart from playing a vital role in many biological processes in living organisms. In this article, we present phenyl boronic acid-functionalized quinone-cyanine (QCy-BA) in combination with AT-rich DNA (exogenous or endogenous cellular DNA), i.e., QCy-BA subset of DNA as a stimuli-responsive NIR fluorescence probe for measuring in vitro levels of H2O2. In response to cellular H2O2 stimulus, QCy-BA converts into QCy-DT, a one-donor-two-acceptor (D2A) system that exhibits switch-on NIR fluorescence upon binding to the DNA minor groove. Fluorescence studies on the combination probe QCy-BA subset of DNA showed strong NIR fluorescence selectively in the presence of H2O2. Furthermore, glucose oxidase (GOx) assay confirmed the high efficiency of the combination probe QCy-BA subset of DNA for probing H2O2 generated in situ through GOx-mediated glucose oxidation. Quantitative analysis through fluorescence plate reader, flow cytometry and live imaging approaches showed that QCy-BA is a promising probe to detect the normal as well as elevated levels of H2O2 produced by EGF/Nox pathways and post-genotoxic stress in both primary and senescent cells. Overall, QCy-BA, in combination with exogenous or cellular DNA, is a versatile probe to quantify and image H2O2 in normal and disease-associated cells.

On Fast Bilateral Filtering Using Fourier Kernels

It was demonstrated in earlier work that, by approximating its range kernel using shiftable functions, the nonlinear bilateral filter can be computed using a series of fast convolutions. Previous approaches based on shiftable approximation have, however, been restricted to Gaussian range kernels. In this work, we propose a novel approximation that can be applied to any range kernel, provided it has a pointwise-convergent Fourier series. More specifically, we propose to approximate the Gaussian range kernel of the bilateral filter using a Fourier basis, where the coefficients of the basis are obtained by solving a series of least-squares problems. The coefficients can be efficiently computed using a recursive form of the QR decomposition. By controlling the cardinality of the Fourier basis, we can obtain a good tradeoff between the run-time and the filtering accuracy. In particular, we are able to guarantee subpixel accuracy for the overall filtering, which is not provided by the most existing methods for fast bilateral filtering. We present simulation results to demonstrate the speed and accuracy of the proposed algorithm.

Hydrogen Bonds Computing Server (HBCS): an online web server to compute hydrogen-bond interactions and their precision

Hydrogen bonds in biological macromolecules play significant structural and functional roles. They are the key contributors to most of the interactions without which no living system exists. In view of this, a web-based computing server, the Hydrogen Bonds Computing Server (HBCS), has been developed to compute hydrogen-bond interactions and their standard deviations for any given macromolecular structure. The computing server is connected to a locally maintained Protein Data Bank (PDB) archive. Thus, the user can calculate the above parameters for any deposited structure, and options have also been provided for the user to upload a structure in PDB format from the client machine. In addition, the server has been interfaced with the molecular viewers Jmol and JSmol to visualize the hydrogen-bond interactions. The proposed server is freely available and accessible via the World Wide Web at http://bioserver1.physics.iisc.ernet.in/hbcs/.

Triplet excited electronic state switching induced by hydrogen bonding: A transient absorption spectroscopy and time-dependent DFT study

The solvent plays a decisive role in the photochemistry and photophysics of aromatic ketones. Xanthone (XT) is one such aromatic ketone and its triplet-triplet (T-T) absorption spectra show intriguing solvatochromic behavior. Also, the reactivity of XT towards H-atom abstraction shows an unprecedented decrease in protic solvents relative to aprotic solvents. Therefore, a comprehensive solvatochromic analysis of the triplet-triplet absorption spectra of XT was carried out in conjunction with time dependent density functional theory using the ad hoc explicit solvent model approach. A detailed solvatochromic analysis of the T-T absorption bands of XT suggests that the hydrogen bonding interactions are different in the corresponding triplet excited states. Furthermore, the contributions of non-specific and hydrogen bonding interactions towards differential solvation of the triplet states in protic solvents were found to be of equal magnitude. The frontier molecular orbital and electron density difference analysis of the T-1 and T-2 states of XT indicates that the charge redistribution in these states leads to intermolecular hydrogen bond strengthening and weakening, respectively, relative to the S-0 state. This is further supported by the vertical excitation energy calculations of the XT-methanol supra-molecular complex. The intermolecular hydrogen bonding potential energy curves obtained for this complex in the S-0, T-1, and T-2 states support the model. In summary, we propose that the different hydrogen bonding mechanisms exhibited by the two lowest triplet excited states of XT result in a decreasing role of the n pi* triplet state, and are thus responsible for its reduced reactivity towards H-atom abstraction in protic solvents. (C) 2016 AIP Publishing LLC.

IMAGE DENOISING USING OPTIMALLY WEIGHTED BILATERAL FILTERS: A SURE AND FAST APPROACH

The bilateral filter is known to be quite effective in denoising images corrupted with small dosages of additive Gaussian noise. The denoising performance of the filter, however, is known to degrade quickly with the increase in noise level. Several adaptations of the filter have been proposed in the literature to address this shortcoming, but often at a substantial computational overhead. In this paper, we report a simple pre-processing step that can substantially improve the denoising performance of the bilateral filter, at almost no additional cost. The modified filter is designed to be robust at large noise levels, and often tends to perform poorly below a certain noise threshold. To get the best of the original and the modified filter, we propose to combine them in a weighted fashion, where the weights are chosen to minimize (a surrogate of) the oracle mean-squared-error (MSE). The optimally-weighted filter is thus guaranteed to perform better than either of the component filters in terms of the MSE, at all noise levels. We also provide a fast algorithm for the weighted filtering. Visual and quantitative denoising results on standard test images are reported which demonstrate that the improvement over the original filter is significant both visually and in terms of PSNR. Moreover, the denoising performance of the optimally-weighted bilateral filter is competitive with the computation-intensive non-local means filter.

FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL DECOMPOSITION

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A common form of the filter is the Gaussian bilateral filter in which both the spatial and range kernels are Gaussian. A direct implementation of this filter requires O(sigma(2)) operations per pixel, where sigma is the standard deviation of the spatial Gaussian. In this paper, we propose an accurate approximation algorithm that can cut down the computational complexity to O(1) per pixel for any arbitrary sigma (constant-time implementation). This is based on the observation that the range kernel operates via the translations of a fixed Gaussian over the range space, and that these translated Gaussians can be accurately approximated using the so-called Gauss-polynomials. The overall algorithm emerging from this approximation involves a series of spatial Gaussian filtering, which can be efficiently implemented (in parallel) using separability and recursion. We present some preliminary results to demonstrate that the proposed algorithm compares favorably with some of the existing fast algorithms in terms of speed and accuracy.