Effect of amplitude correlations on coherence in the local field potential

Neural activity across the brain shows both spatial and temporal correlations at multiple scales, and understanding these correlations is a key step toward understanding cortical processing. Correlation in the local field potential (LFP) recorded from two brain areas is often characterized by computing the coherence, which is generally taken to reflect the degree of phase consistency across trials between two sites. Coherence, however, depends on two factors-phase consistency as well as amplitude covariation across trials-but the spatial structure of amplitude correlations across sites and its contribution to coherence are not well characterized. We recorded LFP from an array of microelectrodes chronically implanted in the primary visual cortex of monkeys and studied correlations in amplitude across electrodes as a function of interelectrode distance. We found that amplitude correlations showed a similar trend as coherence as a function of frequency and interelectrode distance. Importantly, even when phases were completely randomized between two electrodes, amplitude correlations introduced significant coherence. To quantify the contributions of phase consistency and amplitude correlations to coherence, we simulated pairs of sinusoids with varying phase consistency and amplitude correlations. These simulations confirmed that amplitude correlations can significantly bias coherence measurements, resulting in either over-or underestimation of true phase coherence. Our results highlight the importance of accounting for the correlations in amplitude while using coherence to study phase relationships across sites and frequencies.

TRANSIENT NATURAL CONVECTION FLOW IN A RECTANGULAR CAVITY FILLED WITH A POROUS MATERIAL WITH LOCALIZED HEATING FROM BELOW AND THERMAL STRATIFICATION

The transient natural convection flow with thermal stratification in a rectangular cavity filled with fluid saturated porous medium obeying Darcy's law has been studied. Prior to the time t* = 0, the flow in the cavity is assumed to be motionless and all four walls of the cavity are at the same constant temperature. At time t* = 0, the temperatures of the vertical walls are suddenly increased which vary linearly with the distance y and at the same time on the bottom wall an isothermal heat source is placed centrally. This sudden change in the wall temperatures gives rise to unsteadiness in the problem. The horizontal temperature difference induces and sustains a buoyancy driven flow in the cavity which is then controlled by the vertical temperature difference. The partial differential equations governing the transient natural convection flow have been solved numerically. The local and average Nusselt numbers decrease rapidly in a small time interval after the start of the impulsive change in the wall temperatures and the steady state is reached quickly. The time required to reach the steady state depends on the Rayleigh number and the thermal stratification parameter.

Local Structural and Environmental Factors Define the Efficiency of an RNA Pseudoknot Involved in Programmed Ribosomal Frameshift Process

In programmed -1 ribosomal frameshift, an RNA pseudoknot stalls the ribosome at specific sequence and restarts translation in a new reading frame. A precise understanding of structural characteristics of these pseudoknots and their PRF inducing ability has not been clear to date. To investigate this phenomenon, we have studied various structural aspects of a -1 PRF inducing RNA pseudoknot from BWYV using extensive molecular dynamics simulations. A set of functional and poorly functional forms, for which previous mutational data were available, were chosen for analysis. These structures differ from each other by either single base substitutions or base-pair replacements from the native structure. We have rationalized how certain mutations in RNA pseudoknot affect its function; e.g., a specific base substitution in loop 2 stabilizes the junction geometry by forming multiple noncanonical hydrogen bonds, leading to a highly rigid structure that could effectively resist ribosome-induced unfolding, thereby increasing efficiency. While, a CG to AU pair substitution in stem 1 leads to loss of noncanonical hydrogen bonds between stems and loop, resulting in a less stable structure and reduced PRF inducing ability, inversion of a pair in stem 2 alters specific base-pair geometry that might be required in ribosomal recognition of nucleobase groups, negatively affecting pseudoknot functioning. These observations illustrate that the ability of an RNA pseudoknot to induce -1 PRF with an optimal rate depends on several independent factors that contribute to either the local conformational variability or geometry

Local disorder investigation in NiS2-xSex using Raman and Ni K-edge x-ray absorption spectroscopies

We report on Raman and Ni K-edge x-ray absorption investigations of a NiS2-xSex (with x = 0.00, 0.50/0.55, 0.60, and 1.20) pyrite family. The Ni K-edge absorption edge shows a systematic shift going from an insulating phase (x = 0.00 and 0.50) to a metallic phase (x = 0.60 and 1.20). The near-edge absorption features show a clear evolution with Se doping. The extended x-ray absorption fine structure data reveal the evolution of the local structure with Se doping which mainly governs the local disorder. We also describe the decomposition of the NiS2-xSex Raman spectra and investigate the weights of various phonon modes using Gaussian and Lorentzian profiles. The effectiveness of the fitting models in describing the data is evaluated by means of Bayes factor estimation. The Raman analysis clearly demonstrates the disorder effects due to Se alloying in describing the phonon spectra of NiS2-xSex pyrites.

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.

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Formation Flying with Nonlinear Partial Integrated Guidance and Control

Using the dynamic inversion philosophy, a nonlinear partial integrated guidance and control approach is presented in this paper for formation flying. It is based on the evolving philosophy of integrated guidance and control. However, it also retains the advantages of the conventional guidance then control philosophy by retaining the timescale separation between translational and rotational dynamics explicitly. Simulation studies demonstrate that the proposed technique is effective in bringing the vehicles into formation quickly and maintaining the formation.

Statistical significance of episodes with general partial orders

Frequent episode discovery is one of the methods used for temporal pattern discovery in sequential data. An episode is a partially ordered set of nodes with each node associated with an event type. For more than a decade, algorithms existed for episode discovery only when the associated partial order is total (serial episode) or trivial (parallel episode). Recently, the literature has seen algorithms for discovering episodes with general partial orders. In frequent pattern mining, the threshold beyond which a pattern is inferred to be interesting is typically user-defined and arbitrary. One way of addressing this issue in the pattern mining literature has been based on the framework of statistical hypothesis testing. This paper presents a method of assessing statistical significance of episode patterns with general partial orders. A method is proposed to calculate thresholds, on the non-overlapped frequency, beyond which an episode pattern would be inferred to be statistically significant. The method is first explained for the case of injective episodes with general partial orders. An injective episode is one where event-types are not allowed to repeat. Later it is pointed out how the method can be extended to the class of all episodes. The significance threshold calculations for general partial order episodes proposed here also generalize the existing significance results for serial episodes. Through simulations studies, the usefulness of these statistical thresholds in pruning uninteresting patterns is illustrated. (C) 2014 Elsevier Inc. All rights reserved.

Effects of large-scale deforestation on precipitation in the monsoon regions: Remote versus local effects

In this paper, using idealized climate model simulations, we investigate the biogeophysical effects of large-scale deforestation on monsoon regions. We find that the remote forcing from large-scale deforestation in the northern middle and high latitudes shifts the Intertropical Convergence Zone southward. This results in a significant decrease in precipitation in the Northern Hemisphere monsoon regions (East Asia, North America, North Africa, and South Asia) and moderate precipitation increases in the Southern Hemisphere monsoon regions (South Africa, South America, and Australia). The magnitude of the monsoonal precipitation changes depends on the location of deforestation, with remote effects showing a larger influence than local effects. The South Asian Monsoon region is affected the most, with 18% decline in precipitation over India. Our results indicate that any comprehensive assessment of afforestation/reforestation as climate change mitigation strategies should carefully evaluate the remote effects on monsoonal precipitation alongside the large local impacts on temperatures.

Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure

This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.

Tailoring local density of optical states to control emission intensity and anisotropy of quantum dots in hybrid photonic-plasmonic templates

We report results of controlled tuning of the local density of states (LDOS) in versatile, flexible, and hierarchical self assembled plasmonic templates. Using 5 nm diameter gold (Au) spherical nanoantenna within a polymer template randomly dispersed with quantum dots, we show how the photoluminescence intensity and lifetime anisotropy of these dots can be significantly enhanced through LDOS tuning. Finite difference time domain simulations corroborate the experimental observations and extend the regime of enhancement to a wider range of geometric and spectral parameters bringing out the versatility of these functional plasmonic templates. It is also demonstrated how the templates act as plasmonic resonators for effectively engineer giant enhancement of the scattering efficiency of these nano antenna embedded in the templates. Our work provides an alternative method to achieve spontaneous emission intensity and anisotropy enhancement with true nanoscale plasmon resonators. (C) 2015 AIP Publishing LLC.

MRT Letter: A Unified Accelerated Maximum Likelihood Technique for Widefield, Confocal, and Super-Resolution 4Pi Microscopy

We propose an algorithmic technique for accelerating maximum likelihood (ML) algorithm for image reconstruction in fluorescence microscopy. This is made possible by integrating Biggs-Andrews (BA) method with ML approach. The results on widefield, confocal, and super-resolution 4Pi microscopy reveal substantial improvement in the speed of 3D image reconstruction (the number of iterations has reduced by approximately one-half). Moreover, the quality of reconstruction obtained using accelerated ML closely resembles with nonaccelerated ML method. The proposed technique is a step closer to realize real-time reconstruction in 3D fluorescence microscopy. Microsc. Res. Tech. 78:331-335, 2015. (c) 2015 Wiley Periodicals, Inc.

Identification of local variations within secondary structures of proteins

Secondary-structure elements (SSEs) play an important role in the folding of proteins. Identification of SSEs in proteins is a common problem in structural biology. A new method, ASSP (Assignment of Secondary Structure in Proteins), using only the path traversed by the C atoms has been developed. The algorithm is based on the premise that the protein structure can be divided into continuous or uniform stretches, which can be defined in terms of helical parameters, and depending on their values the stretches can be classified into different SSEs, namely -helices, 3(10)-helices, -helices, extended -strands and polyproline II (PPII) and other left-handed helices. The methodology was validated using an unbiased clustering of these parameters for a protein data set consisting of 1008 protein chains, which suggested that there are seven well defined clusters associated with different SSEs. Apart from -helices and extended -strands, 3(10)-helices and -helices were also found to occur in substantial numbers. ASSP was able to discriminate non--helical segments from flanking -helices, which were often identified as part of -helices by other algorithms. ASSP can also lead to the identification of novel SSEs. It is believed that ASSP could provide a better understanding of the finer nuances of protein secondary structure and could make an important contribution to the better understanding of comparatively less frequently occurring structural motifs. At the same time, it can contribute to the identification of novel SSEs. A standalone version of the program for the Linux as well as the Windows operating systems is freely downloadable and a web-server version is also available at .

Analysis of OSNR Requirements for Higher Modulation Schemes for Various Local Oscillator Powers

To meet the growing demands of data traffic in long haul communication, it is necessary to efficiently use the low-loss region(C-band) of the optical spectrum, by increasing the no. of optical channels and increasing the bit rate on each channel But narrow pulses occupy higher spectral bandwidth. To circumvent this problem, higher order modulation schemes such as QPSK and QAM can be used to modulate the bits, which increases the spectral efficiency without demanding any extra spectral bandwidth. On the receiver side, to meet a satisfy, a given BER, the received optical signal requires to have minimum OSNR. In our study in this paper, we analyses for different modulation schemes, the OSNR required with and without preamplifier. The theoretical limit of OSNR requirement for a modulation scheme is compared for a given link length by varying the local oscillator (LO) power. Our analysis shows that as we increase the local oscillator (LO) power, the OSNR requirement decreases for a given BER. Also a combination of preamplifier and local oscillator (LO) gives the OSNR closest to theoretical limit.