Time-Resolved Resonance Raman Spectroscopy: Exploring Reactive Intermediates

The study of reaction mechanisms involves systematic investigations of the correlation between structure, reactivity, and time. The challenge is to be able to observe the chemical changes undergone by reactants as they change into products via one or several intermediates such as electronic excited states (singlet and triplet), radicals, radical ions, carbocations, carbanions, carbenes, nitrenes, nitrinium ions, etc. The vast array of intermediates and timescales means there is no single ``do-it-all'' technique. The simultaneous advances in contemporary time-resolved Raman spectroscopic techniques and computational methods have done much towards visualizing molecular fingerprint snapshots of the reactive intermediates in the microsecond to femtosecond time domain. Raman spectroscopy and its sensitive counterpart resonance Raman spectroscopy have been well proven as means for determining molecular structure, chemical bonding, reactivity, and dynamics of short-lived intermediates in solution phase and are advantageous in comparison to commonly used time-resolved absorption and emission spectroscopy. Today time-resolved Raman spectroscopy is a mature technique; its development owes much to the advent of pulsed tunable lasers, highly efficient spectrometers, and high speed, highly sensitive multichannel detectors able to collect a complete spectrum. This review article will provide a brief chronological development of the experimental setup and demonstrate how experimentalists have conquered numerous challenges to obtain background-free (removing fluorescence), intense, and highly spectrally resolved Raman spectra in the nanosecond to microsecond (ns-mu s) and picosecond (ps) time domains and, perhaps surprisingly, laid the foundations for new techniques such as spatially offset Raman spectroscopy.

A hybrid pre-whitening technique for detection of additive spread spectrum watermarks in audio signals

Pre-whitening techniques are employed in blind correlation detection of additive spread spectrum watermarks in audio signals to reduce the host signal interference. A direct deterministic whitening (DDW) scheme is derived in this paper from the frequency domain analysis of the time domain correlation process. Our experimental studies reveal that, the Savitzky-Golay Whitening (SGW), which is otherwise inferior to DDW technique, performs better when the audio signal is predominantly lowpass. The novelty of this paper lies in exploiting the complementary nature to the two whitening techniques to obtain a hybrid whitening (HbW) scheme. In the hybrid scheme the DDW and SGW techniques are selectively applied, based on short time spectral characteristics of the audio signal. The hybrid scheme extends the reliability of watermark detection to a wider range of audio signals.

Passive vibration isolation of reaction wheel disturbances using a low frequency flexible space platform

Reaction wheel assemblies (RWAs) are momentum exchange devices used in fine pointing control of spacecrafts. Even though the spinning rotor of the reaction wheel is precisely balanced to minimize emitted vibration due to static and dynamic imbalances, precision instrument payloads placed in the neighborhood can always be severely impacted by residual vibration forces emitted by reaction wheel assemblies. The reduction of the vibration level at sensitive payloads can be achieved by placing the RWA on appropriate mountings. A low frequency flexible space platform consisting of folded continuous beams has been designed to serve as a mount for isolating a disturbance source in precision payloads equipped spacecrafts. Analytical and experimental investigations have been carried out to test the usefulness of the low frequency flexible platform as a vibration isolator for RWAs. Measurements and tests have been conducted at varying wheel speeds, to quantify and characterize the amount of isolation obtained from the reaction wheel generated vibration. These tests are further extended to other variants of similar design in order to bring out the best isolation for given disturbance loads. Both time and frequency domain analysis of test data show that the flexible beam platform as a mount for reaction wheels is quite effective and can be used in spacecrafts for passive vibration control. (C) 2011 Elsevier Ltd. All rights reserved.

An approach to multi-temporal MODIS image analysis using image classification and segmentation

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation for extracting water-covered regions. Analysis of MODIS satellite images is applied in three stages: before flood, during flood and after flood. Water regions are extracted from the MODIS images using image classification (based on spectral information) and image segmentation (based on spatial information). Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification (SVM and ANN) and region-based image segmentation is an accurate and reliable approach for the extraction of water-covered regions. (c) 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.

Frequency domain turbo equalization for MIMO-CPSC systems with large delay spreads

In this paper, we consider low-complexity turbo equalization for multiple-input multiple-output (MIMO) cyclic prefixed single carrier (CPSC) systems in MIMO inter-symbol interference (ISI) channels characterized by large delay spreads. A low-complexity graph based equalization is carried out in the frequency domain. Because of the reduction in correlation among the noise samples that happens for large frame sizes and delay spreads in frequency domain processing, improved performance compared to time domain processing is shown to be achieved. This improved performance is attractive for equalization in severely delay spread ISI channels like ultrawideband channels and underwater acoustic channels.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Solvation dynamics of tryptophan in water-dimethyl sulfoxide binary mixture: In search of molecular origin of composition dependent multiple anomalies

Experimental and simulation studies have uncovered at least two anomalous concentration regimes in water-dimethyl sulfoxide (DMSO) binary mixture whose precise origin has remained a subject of debate. In order to facilitate time domain experimental investigation of the dynamics of such binary mixtures, we explore strength or extent of influence of these anomalies in dipolar solvation dynamics by carrying out long molecular dynamics simulations over a wide range of DMSO concentration. The solvation time correlation function so calculated indeed displays strong composition dependent anomalies, reflected in pronounced non-exponential kinetics and non-monotonous composition dependence of the average solvation time constant. In particular, we find remarkable slow-down in the solvation dynamics around 10%-20% and 35%-50% mole percentage. We investigate microscopic origin of these two anomalies. The population distribution analyses of different structural morphology elucidate that these two slowing down are reflections of intriguing structural transformations in water-DMSO mixture. The structural transformations themselves can be explained in terms of a change in the relative coordination number of DMSO and water molecules, from 1DMSO:2H(2)O to 1H(2)O:1DMSO and 1H(2)O:2DMSO complex formation. Thus, while the emergence of first slow down (at 15% DMSO mole percentage) is due to the percolation among DMSO molecules supported by the water molecules (whose percolating network remains largely unaffected), the 2nd anomaly (centered on 40%-50%) is due to the formation of the network structure where the unit of 1DMSO:1H(2)O and 2DMSO:1H(2)O dominates to give rise to rich dynamical features. Through an analysis of partial solvation dynamics an interesting negative cross-correlation between water and DMSO is observed that makes an important contribution to relaxation at intermediate to longer times.

Multi-Temporal Satellite Image Analysis Using Gene Expression Programming

This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images is applied in two stages: before flood and during flood. For these images the extraction of water region utilizes spectral information for image classification and spatial information for image segmentation. Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as artificial neural networks and gene expression programming to separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water region. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification and region-based segmentation is an accurate and reliable for the extraction of water-covered region.

Comparative study of different nonconserving time integrators for wave propagation in hyperelastic waveguides

This paper addresses the formulation and numerical efficiency of various numerical models of different nonconserving time integrators for studying wave propagation in nonlinear hyperelastic waveguides. The study includes different nonlinear finite element formulations based on standard Galerkin finite element model, time domain spectral finite element model, Taylor-Galerkin finite element model, generalized Galerkin finite element model and frequency domain spectral finite element model. A comparative study on the computational efficiency of these different models is made using a hyperelastic rod model, and the optimal computational scheme is identified. The identified scheme is then used to study the propagation of transverse and longitudinal waves in a Timoshenko beam with Murnaghan material nonlinearity.

Time resolved terahertz spectroscopy of low frequency electronic resonances and optical pump-induced terahertz photoconductivity in reduced graphene oxide membrane

Towards ultrafast optoelectronic applications of single and a few layer reduced graphene oxide (RGO), we study time domain terahertz spectroscopy and optical pump induced changes in terahertz conductivity of self-supported RGO membrane in the spectral window of 0.5-3.5 THz. The real and imaginary parts of conductivity spectra clearly reveal low frequency resonances, attributed to the energy gaps due to the van Hove singularities in the density of states flanking the Dirac points arising due to the relative rotation of the graphene layers. Further, optical pump induced terahertz conductivity is positive, pointing to the dominance of intraband scattering processes. The relaxation dynamics of the photo-excited carriers consists of three cooling pathways: the faster (similar to 450 fs) one due to optical phonon emission followed by disorder mediated large momentum and large energy acoustic phonon emission with a time constant of a few ps (called the super-collision mechanism) and a very large time (similar to 100 ps) arising from the deep trap states. The frequency dependence of the dynamic conductivity at different delay times is analyzed in term of Drude-Smith model. (C) 2014 Published by Elsevier Ltd.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

REDUCED ORDER MODELLING OF COMBUSTION INSTABILITY IN A BACKWARD FACING STEP COMBUSTOR

This paper develops a fully coupled time domain Reduced Order Modelling (ROM) approach to model unsteady combustion dynamics in a backward facing step combustor The acoustic field equations are projected onto the canonical acoustic eigenmodes of the systems to obtain a coupled system of modal evolution equations. The heat release response of the flame is modelled using the G-equation approach. Vortical velocity fluctuations that arise due to shear layer rollup downstream of the step are modelled using a simplified 1D-advection equation whose phase speed is determined from a linear, local, temporal stability analysis of the shear layer just downstream of the step. The hydrodynamic stability analysis reveals a abrupt change in the value of disturbance phase speed from unity for Re < Re-crit to 0.5 for Re > Re-crit, where Remit for the present geometry was found to be approximate to 10425. The results for self-excited flame response show highly wrinkled flame shapes that are qualitatively similar to those seen in prior experiments of acoustically forced flames. The effect of constructive and destructive interference between the two contributions to flame surface wrinkling results in high amplitude wrinkles for the case when K-c -> 1.

Lightning induced currents in isolated towers

During a lightning strike to ground or structure nearby, currents are induced in all conducting structures including tall towers. As compared to the case of a direct strike, these induced currents will be of much lower amplitude, however, appear more frequently. A quantitative knowledge on these induced currents will be of interest to instrumented and communication towers. A preliminary analysis on the characteristics of the induced currents was reported in an earlier work 1], which employed simplifications by neglecting the induced charge on the tower and also the contribution from the upward connecting leader. This work aims to make further progress by considering all the essential aspects in ascertaining the induced currents. For determining the field produced by the developing return stroke, a macro-physical model for the return stroke is employed and for the evaluation of the induced currents, an in-house time domain numerical electromagnetic code along with suitable modifications for incorporating the dynamics of upward leader is employed.

Time-Instant Sampling Based Encoding of Time-Varying Acoustic Spectrum

The inner ear has been shown to characterize an acoustic stimuli by transducing fluid motion in the inner ear to mechanical bending of stereocilia on the inner hair cells (IHCs). The excitation motion/energy transferred to an IHC is dependent on the frequency spectrum of the acoustic stimuli, and the spatial location of the IHC along the length of the basilar membrane (BM). Subsequently, the afferent auditory nerve fiber (ANF) bundle samples the encoded waveform in the IHCs by synapsing with them. In this work we focus on sampling of information by afferent ANFs from the IHCs, and show computationally that sampling at specific time instants is sufficient for decoding of time-varying acoustic spectrum embedded in the acoustic stimuli. The approach is based on sampling the signal at its zero-crossings and higher-order derivative zero-crossings. We show results of the approach on time-varying acoustic spectrum estimation from cricket call signal recording. The framework gives a time-domain and non-spatial processing perspective to auditory signal processing. The approach works on the full band signal, and is devoid of modeling any bandpass filtering mimicking the BM action. Instead, we motivate the approach from the perspective of event-triggered sampling by afferent ANFs on the stimuli encoded in the IHCs. Though the approach gives acoustic spectrum estimation but it is shallow on its complete understanding for plausible bio-mechanical replication with current mammalian auditory mechanics insights.

Identification of nonlinear dynamic systems: Time-frequency filtering and skeleton curves

The nonlinear behavior varying with the instantaneous response was analyzed through the joint time-frequency analysis method for a class of S. D. O. F nonlinear system. A masking operator an definite regions is defined and two theorems are presented. Based on these, the nonlinear system is modeled with a special time-varying linear one, called the generalized skeleton linear system (GSLS). The frequency skeleton curve and the damping skeleton curve are defined to describe the main feature of the non-linearity as well. Moreover, an identification method is proposed through the skeleton curves and the time-frequency filtering technique.