Concentration Fluctuations and Segmental Dynamics in Weakly Dynamic Asymmetric Blends in the Presence of Surface-Functionalized Multiwall Carbon Nanotubes

Surface-functionalized multiwall carbon nanotubes (MWCNTs) are incorporated in poly(methyl methacrylate)/styrene acrylonitrile (PMMA/SAN) blends and the pretransitional regime is monitored in situ by melt rheology and dielectric spectroscopy. As the blends exhibit weak dynamic asymmetry, the obvious transitions in the melt rheology due to thermal concentration fluctuations are weak. This is further supported by the weak temperature dependence of the correlation length ( approximate to 10-12 angstrom) in the vicinity of demixing. Hence, various rheological techniques in both the temperature and frequency domains are adopted to evaluate the demixing temperature. The spinodal decomposition temperature is manifested in an increase in the miscibility gap in the presence of MWCNTs. Furthermore, MWCNTs lead to a significant slowdown of the segmental dynamics in the blends. Thermally induced phase separation in the PMMA/SAN blends lead to selective localization of MWCNTs in the PMMA phase. This further manifests itself in a significant increase in the melt conductivity.

Velocity Fluctuations in Helical Propulsion: How Small Can a Propeller Be

Helical propulsion is at the heart of locomotion strategies utilized by various natural and artificial swimmers. We used experimental observations and a numerical model to study the various fluctuation mechanisms that determine the performance of an externally driven helical propeller as the size of the helix is reduced. From causality analysis, an overwhelming effect of orientational noise at low length scales is observed, which strongly affects the average velocity and direction of motion of a propeller. For length scales smaller than a few micrometers in aqueous media, the operational frequency for the propulsion system would have to increase as the inverse cube of the size, which can be the limiting factor for a helical propeller to achieve locomotion in the desired direction.

Universal Conductance Fluctuations as a direct probe to valley coherence and universality class of disordered graphene

We demonstrate that the universal conductance fluctuations (UCF) can be used as a direct probe to study the valley quantum states in disordered graphene. The UCF magnitude in graphene is suppressed by a factor of four at high carrier densities where the short-range disorder essentially breaks the valley degeneracy of the K and K' valleys, leading to a density dependent crossover of symmetry class from symplectic near the Dirac point to orthogonal at high densities.

SPATIO-TEMPORAL DYNAMICS ALONG THE TERRAIN GRADIENT OF DIVERSE LANDSCAPE

Land use (LU) land cover (LC) information at a temporal scale illustrates the physical coverage of the Earth's terrestrial surface according to its use and provides the intricate information for effective planning and management activities. LULC changes are stated as local and location specific, collectively they act as drivers of global environmental changes. Understanding and predicting the impact of LULC change processes requires long term historical restorations and projecting into the future of land cover changes at regional to global scales. The present study aims at quantifying spatio temporal landscape dynamics along the gradient of varying terrains presented in the landscape by multi-data approach (MDA). MDA incorporates multi temporal satellite imagery with demographic data and other additional relevant data sets. The gradient covers three different types of topographic features, planes; hilly terrain and coastal region to account the significant role of elevation in land cover change. The seasonality is another aspect to be considered in the vegetation dominated landscapes; variations are accounted using multi seasonal data. Spatial patterns of the various patches are identified and analysed using landscape metrics to understand the forest fragmentation. The prediction of likely changes in 2020 through scenario analysis has been done to account for the changes, considering the present growth rates and due to the proposed developmental projects. This work summarizes recent estimates on changes in cropland, agricultural intensification, deforestation, pasture expansion, and urbanization as the causal factors for LULC change.

Globally coupled stochastic two-state oscillators: Fluctuations due to finite numbers

Infinite arrays of coupled two-state stochastic oscillators exhibit well-defined steady states. We study the fluctuations that occur when the number N of oscillators in the array is finite. We choose a particular form of global coupling that in the infinite array leads to a pitchfork bifurcation from a monostable to a bistable steady state, the latter with two equally probable stationary states. The control parameter for this bifurcation is the coupling strength. In finite arrays these states become metastable: The fluctuations lead to distributions around the most probable states, with one maximum in the monostable regime and two maxima in the bistable regime. In the latter regime, the fluctuations lead to transitions between the two peak regions of the distribution. Also, we find that the fluctuations break the symmetry in the bimodal regime, that is, one metastable state becomes more probable than the other, increasingly so with increasing array size. To arrive at these results, we start from microscopic dynamical evolution equations from which we derive a Langevin equation that exhibits an interesting multiplicative noise structure. We also present a master equation description of the dynamics. Both of these equations lead to the same Fokker-Planck equation, the master equation via a 1/N expansion and the Langevin equation via standard methods of Ito calculus for multiplicative noise. From the Fokker-Planck equation we obtain an effective potential that reflects the transition from the monomodal to the bimodal distribution as a function of a control parameter. We present a variety of numerical and analytic results that illustrate the strong effects of the fluctuations. We also show that the limits N -> infinity and t -> infinity(t is the time) do not commute. In fact, the two orders of implementation lead to drastically different results.

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.

Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition

A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.

Dislocation dynamical approach to force fluctuations in nanoindentation experiments

We develop an approach that combines the power of nonlinear dynamics with the evolution equations for the mobile and immobile dislocation densities and force to explain force fluctuations in nanoindentation experiments. The model includes nucleation, multiplication, and propagation thresholds for mobile dislocations, and other well known dislocation transformation mechanisms. The model predicts all the generic features of nanoindentation such as the Hertzian elastic branch followed by several force drops of decreasing magnitudes, and residual plasticity after unloading. The stress corresponding to the elastic force maximum is close to the yield stress of an ideal solid. The predicted values for all the quantities are close to those reported by experiments. Our model allows us to address the indentation-size effect including the ambiguity in defining the hardness in the force drop dominated regime. At large indentation depths, the hardness remains nearly constant with a marginal decreasing trend.

Estimation of voice-onset time in continuous speech using temporal measures

This paper proposes an automatic acoustic-phonetic method for estimating voice-onset time of stops. This method requires neither transcription of the utterance nor training of a classifier. It makes use of the plosion index for the automatic detection of burst onsets of stops. Having detected the burst onset, the onset of the voicing following the burst is detected using the epochal information and a temporal measure named the maximum weighted inner product. For validation, several experiments are carried out on the entire TIMIT database and two of the CMU Arctic corpora. The performance of the proposed method compares well with three state-of-the-art techniques. (C) 2014 Acoustical Society of America

Probing a spin-glass state in SrRuO3 thin films through higher-order statistics of resistance fluctuations

The complex perovskite oxide SrRuO3 shows intriguing transport properties at low temperatures due to the interplay of spin, charge, and orbital degrees of freedom. One of the open questions in this system is regarding the origin and nature of the low-temperature glassy state. In this paper we report on measurements of higher-order statistics of resistance fluctuations performed in epitaxial thin films of SrRuO3 to probe this issue. We observe large low-frequency non-Gaussian resistance fluctuations over a certain temperature range. Our observations are compatible with that of a spin-glass system with properties described by hierarchical dynamics rather than with that of a simple ferromagnet with a large coercivity.

Dynamics of intermittent force fluctuations in vesicular nanotubulation

Irregular force fluctuations are seen in most nanotubulation experiments. The dynamics behind their presence has, however, been neither commented upon nor modeled. A simple estimate of the mean energy dissipated in force drops turns out to be several times the thermal energy. This coupled with the rate dependent nature of the deformation reported in several experiments point to a dynamical origin of the serrations. We simplify the whole process of tether formation through a three-stage model of successive deformations of sphere to ellipsoid, neck-formation, and tubule birth and extension. Based on this, we envisage a rate-softening frictional force at the neck that must be overcome before a nanotube can be pulled out. Our minimal model includes elastic and visco-elastic deformation of the vesicle, and has built-in dependence on pull velocity, vesicle radius, and other material parameters, enabling us to capture various kinds of serrated force-extension curves for different parameter choices. Serrations are predicted in the nanotubulation region. Other features of force-extension plots reported in the literature such as a plateauing serrated region beyond a force drop, serrated flow region with a small positive slope, an increase in the elastic threshold with pull velocity, force-extension curves for vesicles with larger radius lying lower than those for smaller radius, are all also predicted by the model. A toy model is introduced to demonstrate that the role of the friction law is limited to inducing stick-slip oscillations in the force, and all other qualitative and quantitative features emerging from the model can only be attributed to other physical mechanisms included in the deformation dynamics of the vesicle. (C) 2014 AIP Publishing LLC.

VIRTUAL VIEW SYNTHESIS BY NON-LOCAL MEANS FILTERING USING TEMPORAL DATA

A novel algorithm for Virtual View Synthesis based on Non-Local Means Filtering is presented in this paper. Apart from using the video frames from the nearby cameras and the corresponding per-pixel depth map, this algorithm also makes use of the previously synthesized frame. Simple and efficient, the algorithm can synthesize video at any given virtual viewpoint at a faster rate. In the process, the quality of the synthesized frame is not compromised. Experimental results prove the above mentioned claim. The subjective and objective quality of the synthesized frames are comparable to the existing algorithms.

Wind speed prediction using spatio-temporal covariance

High wind poses a number of hazards in different areas such as structural safety, aviation, and wind energy-where low wind speed is also a concern, pollutant transport, to name a few. Therefore, usage of a good prediction tool for wind speed is necessary in these areas. Like many other natural processes, behavior of wind is also associated with considerable uncertainties stemming from different sources. Therefore, to develop a reliable prediction tool for wind speed, these uncertainties should be taken into account. In this work, we propose a probabilistic framework for prediction of wind speed from measured spatio-temporal data. The framework is based on decompositions of spatio-temporal covariance and simulation using these decompositions. A novel simulation method based on a tensor decomposition is used here in this context. The proposed framework is composed of a set of four modules, and the modules have flexibility to accommodate further modifications. This framework is applied on measured data on wind speed in Ireland. Both short-and long-term predictions are addressed.

Sensitivity of polarization fluctuations to the nature of protein-water interactions: Study of biological water in four different protein-water systems

Since the time of Kirkwood, observed deviations in magnitude of the dielectric constant of aqueous protein solution from that of neat water (similar to 80) and slower decay of polarization have been subjects of enormous interest, controversy, and debate. Most of the common proteins have large permanent dipole moments (often more than 100 D) that can influence structure and dynamics of even distant water molecules, thereby affecting collective polarization fluctuation of the solution, which in turn can significantly alter solution's dielectric constant. Therefore, distance dependence of polarization fluctuation can provide important insight into the nature of biological water. We explore these aspects by studying aqueous solutions of four different proteins of different characteristics and varying sizes, chicken villin headpiece subdomain (HP-36), immunoglobulin binding domain protein G (GB1), hen-egg white lysozyme (LYS), and Myoglobin (MYO). We simulate fairly large systems consisting of single protein molecule and 20000-30000 water molecules (varied according to the protein size), providing a concentration in the range of similar to 2-3 mM. We find that the calculated dielectric constant of the system shows a noticeable increment in all the cases compared to that of neat water. Total dipole moment auto time correlation function of water < dM(W) (0)delta M-W (t) > is found to be sensitive to the nature of the protein. Surprisingly, dipole moment of the protein and total dipole moment of the water molecules are found to be only weakly coupled. Shellwise decomposition of water molecules around protein reveals higher density of first layer compared to the succeeding ones. We also calculate heuristic effective dielectric constant of successive layers and find that the layer adjacent to protein has much lower value (similar to 50). However, progressive layers exhibit successive increment of dielectric constant, finally reaching a value close to that of bulk 4-5 layers away. We also calculate shellwise orientational correlation function and tetrahedral order parameter to understand the local dynamics and structural re-arrangement of water. Theoretical analysis providing simple method for calculation of shellwise local dielectric constant and implication of these findings are elaborately discussed in the present work. (C) 2014 AIP Publishing LLC.