Enhancement of circular differential deflection of light in an optically active medium

In this letter, we investigate the circular differential deflection of a light beam refracted at the interface of an optically active medium. We show that the difference between the angles of deviation of the two circularly polarized components of the transmitted beam is enhanced manyfold near total internal reflection, which suggests a simple way of increasing the limit of detection of chiro-optical measurements. (C) 2012 Optical Society of America

Carbon Nanotube based Composite Fibers for Strain Sensing, Signal Processing and Computing

Carbon nanotubes dispersed in polymer matrix have been aligned in the form of fibers and interconnects and cured electrically and by UV light. Conductivity and effective semiconductor tunneling against reverse to forward bias field have been designed to have differentiable current-voltage response of each of the fiber/channel. The current-voltage response is a function of the strain applied to the fibers along axial direction. Biaxial and shear strains are correlated by differentiating signals from the aligned fibers/channels. Using a small doping of magnetic nanoparticles in these composite fibers, magneto-resistance properties are realized which are strong enough to use the resulting magnetostriction as a state variable for signal processing and computing. Various basic analog signal processing tasks such as addition, convolution and filtering etc. can be performed. These preliminary study shows promising application of the concept in combined analog-digital computation in carbon nanotube based fibers. Various dynamic effects such as relaxation, electric field dependent nonlinearities and hysteresis on the output signals are studied using experimental data and analytical model.

Signal-Powered Low-Drop-Diode Equivalent Circuit for Full-Wave Bridge Rectifier

Piezoelectric-device-based vibration energy harvesting requires a rectifier for conversion of input ac to usable dc form. Power loss due to diode drop in rectifier is a significant fraction of the already low levels of harvested power. The proposed circuit is a low-drop-diode equivalent, which mimics a diode using linear region-operated MOSFET. The proposed diode equivalent is powered directly from input signal and requires no additional power supply for its control. Power used by the control circuit is kept at a bare minimum to have an overall output power improvement. Diode equivalent was used to replace the four diodes in a full-wave bridge rectifier, which is the basic full- wave rectifier and is a part of the more advanced rectifiers like switch-only and bias-flip rectifiers. Simulation in 130-nm technology and experiment with discrete components show that a bridge rectifier with the proposed diode provides a 30-169% increase in output power extracted from piezoelectric device, as compared to a bridge rectifier with diode-connected MOSFETs. The bridge rectifier with the proposed diode can extract 90% of the maximum available power from an ideal piezoelectric device-bridge rectifier circuit. Setting aside the constraint of power loss, simulations indicate that diode drop as low as 10 mV at 38 mu A can be achieved.

Fluorescence Enhancement Using Silver Nanotriangle Arrays

We describe the fabrication of silver nanotriangle array using angle resolved nanosphere lithography and utilizing the same for enhancing fluorescence. The well established nanosphere lithography is modified by changing the angle of deposition between the nanosphere mask and the beam of silver being deposited resulting in nanotriangles of varying surface area and density. The 470 nm plasmon resonance wavelength of the substrate was determined using minimum reflectivity method which closely matches with excitation wavelength of the fluorophore. Ten times enhancement in fluorescence emission intensity is obtained from fluorescein isothiocyanate coated on top of silver nanotriangle array separated by a spacer layer of poly vinyl alcohol as compared to glass. The enhanced fluorescence emission is attributed to the increase in local field enhancement.

A Technique to Compute Smooth Amplitude, Phase, and Frequency Modulations From the Analytic Signal

Gabor's analytic signal (AS) is a unique complex signal corresponding to a real signal, but in general, it admits infinitely-many combinations of amplitude and frequency modulations (AM and FM, respectively). The standard approach is to enforce a non-negativity constraint on the AM, but this results in discontinuities in the corresponding phase modulation (PM), and hence, an FM with discontinuities particularly when the underlying AM-FM signal is over-modulated. In this letter, we analyze the phase discontinuities and propose a technique to compute smooth AM and FM from the AS, by relaxing the non-negativity constraint on the AM. The proposed technique is effective at handling over-modulated signals. We present simulation results to support the theoretical calculations.

Albedo enhancement over land to counteract global warming: impacts on hydrological cycle

A recent modelling study has shown that precipitation and runoff over land would increase when the reflectivity of marine clouds is increased to counter global warming. This implies that large scale albedo enhancement over land could lead to a decrease in runoff over land. In this study, we perform simulations using NCAR CAM3.1 that have implications for Solar Radiation Management geoengineering schemes that increase the albedo over land. We find that an increase in reflectivity over land that mitigates the global mean warming from a doubling of CO2 leads to a large residual warming in the southern hemisphere and cooling in the northern hemisphere since most of the land is located in northern hemisphere. Precipitation and runoff over land decrease by 13.4 and 22.3%, respectively, because of a large residual sinking motion over land triggered by albedo enhancement over land. Soil water content also declines when albedo over land is enhanced. The simulated magnitude of hydrological changes over land are much larger when compared to changes over oceans in the recent marine cloud albedo enhancement study since the radiative forcing over land needed (-8.2 W m(-2)) to counter global mean radiative forcing from a doubling of CO2 (3.3 W m(-2)) is approximately twice the forcing needed over the oceans (-4.2 W m(-2)). Our results imply that albedo enhancement over oceans produce climates closer to the unperturbed climate state than do albedo changes on land when the consequences on land hydrology are considered. Our study also has important implications for any intentional or unintentional large scale changes in land surface albedo such as deforestation/afforestation/reforestation, air pollution, and desert and urban albedo modification.

Carbonization of solvent and capping agent based enhancement in the stabilization of cobalt nanoparticles and their magnetic study

We describe a hybrid synthetic protocol, the solvated metal atom dispersion (SMAD) method, for the synthesis and stabilization of monodisperse amorphous cobalt nanoparticles. By employing an optimized ratio of a weakly coordinating solvent and a capping agent monodisperse colloidal cobalt nanoparticles (2 +/- 0.5 nm) have been prepared by the SMAD method. However, the as-prepared samples were found to be oxidatively unstable which was elucidated by their magnetic studies. Oxidative stability in our case was achieved via a pyrolysis process that led to the decomposition of the organic solvent and the capping agent resulting in the formation of carbon encapsulated cobalt nanoparticles which was confirmed by Raman spectroscopy. Controlled annealing at different temperatures led to the phase transformation of metallic cobalt from the hcp to fcc phase. The magnetic behaviour varies with the phase and the particle size; especially, the coercivity of nanoparticles exhibited strong dependence on the phase transformation of cobalt. The high saturation magnetization close to that of the bulk value was achieved in the case of the annealed samples. In addition to detailed structural and morphological characterization, the results of thermal and magnetic studies are also presented.

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.

RCS ENHANCEMENT DUE TO BRAGG SCATTERING

With the advances of techniques for RCS reduction, it has become practical to develop aircraft which are invisible to modern day radars. In order to detect such low visible targets it is necessary to explore other phenomenon that contributes to the scattering of incident electromagnetic wave. It is well known from the developments from the clear air scattering using RASS induced acoustic wave could be used to create dielectric constant fluctuation. The scattering from these fluctuations rather than from the aircraft have been observed to enhance the RCS of clear air, under the condition when the incident EM wave is half of the acoustic wave, the condition of Bragg scattering would be met and RCS would be enhanced. For detecting low visibility targets which are at significant distance away from the main radar, inducement of EM fluctuation from acoustic source collocated with the acoustic source is infeasible. However the flow past aircraft produces acoustic disturbances around the aircraft can be exploited to detect low visibility targets. In this paper numerical simulation for RCS enhancement due to acoustic disturbances is presented. In effect, this requires the solution of scattering from 3D inhomogeneous complex shaped bodies. In this volume surface integral equation (VSIE) is used to compute the RCS from fluctuation introduced through the acoustic disturbances. Though the technique developed can be used to study the scattering from radars of any shape and acoustic disturbances of any shape. For illustrative condition, enhancement due to the Bragg scattering are shown to improve the RCS by nearly 30dB, for air synthetic sinusoidal acoustic variation profile for a spherical scattering volume

SPARSE SIGNAL RECONSTRUCTION BASED ON SIGNAL DEPENDENT NON-UNIFORM SAMPLES

The classical approach to A/D conversion has been uniform sampling and we get perfect reconstruction for bandlimited signals by satisfying the Nyquist Sampling Theorem. We propose a non-uniform sampling scheme based on level crossing (LC) time information. We show stable reconstruction of bandpass signals with correct scale factor and hence a unique reconstruction from only the non-uniform time information. For reconstruction from the level crossings we make use of the sparse reconstruction based optimization by constraining the bandpass signal to be sparse in its frequency content. While overdetermined system of equations is resorted to in the literature we use an undetermined approach along with sparse reconstruction formulation. We could get a reconstruction SNR > 20dB and perfect support recovery with probability close to 1, in noise-less case and with lower probability in the noisy case. Random picking of LC from different levels over the same limited signal duration and for the same length of information, is seen to be advantageous for reconstruction.

Robust GNSS signal detection in the presence of navigation data bits

This paper considers the problem of weak signal detection in the presence of navigation data bits for Global Navigation Satellite System (GNSS) receivers. Typically, a set of partial coherent integration outputs are non-coherently accumulated to combat the effects of model uncertainties such as the presence of navigation data-bits and/or frequency uncertainty, resulting in a sub-optimal test statistic. In this work, the test-statistic for weak signal detection is derived in the presence of navigation data-bits from the likelihood ratio. It is highlighted that averaging the likelihood ratio based test-statistic over the prior distributions of the unknown data bits and the carrier phase uncertainty leads to the conventional Post Detection Integration (PDI) technique for detection. To improve the performance in the presence of model uncertainties, a novel cyclostationarity based sub-optimal PDI technique is proposed. The test statistic is analytically characterized, and shown to be robust to the presence of navigation data-bits, frequency, phase and noise uncertainties. Monte Carlo simulation results illustrate the validity of the theoretical results and the superior performance offered by the proposed detector in the presence of model uncertainties.

A finite-rate-of-innovation signal sampling perspective of the source-filter model of speech production

We consider the speech production mechanism and the asso- ciated linear source-filter model. For voiced speech sounds in particular, the source/glottal excitation is modeled as a stream of impulses and the filter as a cascade of second-order resonators. We show that the process of sampling speech signals can be modeled as filtering a stream of Dirac impulses (a model for the excitation) with a kernel function (the vocal tract response),and then sampling uniformly. We show that the problem of esti- mating the excitation is equivalent to the problem of recovering a stream of Dirac impulses from samples of a filtered version. We present associated algorithms based on the annihilating filter and also make a comparison with the classical linear prediction technique, which is well known in speech analysis. Results on synthesized as well as natural speech data are presented.

Some new results on signal reconstruction from Fourier transform magnitude spectrum

We address the problem of signal reconstruction from Fourier transform magnitude spectrum. The problem arises in many real-world scenarios where magnitude-only measurements are possible, but it is required to construct a complex-valued signal starting from those measurements. We present some new general results in this context and show that the previously known results on minimum-phase rational transfer functions, and recoverability of minimum-phase functions from magnitude spectrum, form special cases of the results reported in this paper. Some simulation results are also provided to demonstrate the practical feasibility of the reconstruction methodology.