Search results for "CORR"

showing 10 items of 6535 documents

The Lotus japonicus ROP3 Is Involved in the Establishment of the Nitrogen-Fixing Symbiosis but Not of the Arbuscular Mycorrhizal Symbiosis

2021

Legumes form root mutualistic symbioses with some soil microbes promoting their growth, rhizobia, and arbuscular mycorrhizal fungi (AMF). A conserved set of plant proteins rules the transduction of symbiotic signals from rhizobia and AMF in a so-called common symbiotic signaling pathway (CSSP). Despite considerable efforts and advances over the past 20 years, there are still key elements to be discovered about the establishment of these root symbioses. Rhizobia and AMF root colonization are possible after a deep cell reorganization. In the interaction between the model legume Lotus japonicus and Mesorhizobium loti, this reorganization has been shown to be dependent on a SCAR/Wave-like signa…

symbiotic nitrogen fixationarbuscular mycorrhizal symbiosisbiologyfungiLotusLotus japonicusPlant culturerho-GTPasePlant Sciencebiology.organism_classificationPhenotypeROPSB1-1110RhizobiaSymbiosisLotus japonicusBotanyNitrogen fixationColonizationGeneOriginal ResearchFrontiers in Plant Science
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One‐magnon Raman scattering in Ni c Mg 1–c O solid solutions

2005

The one-magnon Raman scattering was studied for the first time in antiferromagnetic NicMg1–cO solid solutions as a function of temperature and composition. We found that (i) the one-magnon frequency extrapolated to T = 0 K experiences an abrupt change between c = 0.99 and c = 0.9 and (ii) the one-magnon energy for highly diluted nickel oxide vanishes significantly below the Neel temperature. The obtained dependences are compared to the theoretical predictions within the mean field approximation. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

symbols.namesakeCondensed matter physicsMean field theoryChemistryNickel oxideMagnonsymbolsAntiferromagnetismCondensed Matter::Strongly Correlated ElectronsNéel temperatureRaman scatteringSolid solutionphysica status solidi (c)
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On the autocorrelation function of Rice processes for unsymmetrical doppler power spectral densities

2010

In this paper, we derive an analytical expression for the ACF of Rice processes in the general case of unsymmetrical Doppler power spectral densities. This expression, which is obtained based on the multidimensional Gaussian distribution approach, is shown to cover the ACF of Rayleigh processes as a special case. Various numerical examples are presented to illustrate the impact of the channel parameters on the ACF. Computer simulations, considering the von Mises distribution for the angle of arrivals, are also performed to check the validity of the analytical result. Finally, the analysis of the covariance spectrum is addressed.

symbols.namesakeGaussianAutocorrelationStatisticssymbolsvon Mises distributionStatistical physicsRayleigh scatteringCovarianceDoppler effectMathematicsPower (physics)Rayleigh fadingThe 2010 International Conference on Advanced Technologies for Communications
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Predictive Model for Cut-Edge Corrosion of Galvanized Steels

2006

A numerical model for the electrochemical behavior of cut-edge of galvanized steels is proposed. Some experimental data of current densities above cut-edge immersed in a 0.03M NaCl solution have been measured, using a scanning vibrating electrode technique, and compared with some simulated ones. A good fit has been obtained. The model geometry has been modified by decreasing the electrolyte thickness in order to tend towards an atmospheric corrosion case; such situation that is not easily accessible by electrochemical studies. Three regions can be distinguished according to the efficiency of the galvanic coupling to protect steel.

symbols.namesakeMaterials scienceAtmospheric corrosionGalvanic couplingVibrating electrodeMetallurgysymbolsElectrolyteEdge (geometry)ElectrochemistryGalvanizationCorrosionECS Transactions
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An Improved Method for Estimating the Time ACF of a Sum of Complex Plane Waves

2010

Time averaging is a well-known technique for evaluating the temporal autocorrelation function (ACF) from a sample function of a stochastic process. For stochastic processes that can be modelled as a sum of plane waves, it is shown that the ACF obtained by time averaging can be expressed as a sum of auto-terms (ATs) and cross-terms (CTs). The ATs result from the autocorrelation of the individual plane waves, while the CTs are due to the cross-correlation between different plane wave components. The CTs cause an estimation error of the ACF. This estimation error increases as the observation time decreases. For the practically important case that the observation time interval is limited, we pr…

symbols.namesakeMathematical optimizationFourier transformStochastic processKernel (statistics)AutocorrelationMathematical analysisPlane wavesymbolsInterval (mathematics)Frequency modulationComplex planeMathematics2010 IEEE Global Telecommunications Conference GLOBECOM 2010
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Computing variations of entropy and redundancy under nonlinear mappings not preserving the signal dimension: quantifying the efficiency of V1 cortex

2021

In computational neuroscience, the Efficient Coding Hypothesis argues that the neural organization comes from the optimization of information-theoretic goals [Barlow Proc.Nat.Phys.Lab.59]. A way to confirm this requires the analysis of the statistical performance of biological systems that have not been statistically optimized [Renart et al. Science10, Malo&Laparra Neur.Comp.10, Foster JOSA18, Gomez-Villa&Malo J.Neurophysiol.19]. However, when analyzing the information-theoretic performance, cortical magnification in the retina-cortex pathway poses a theoretical problem. Cortical magnification stands for the increase the signal dimensionality [Cowey&Rolls Exp. Brain Res.74]. Conventional mo…

symbols.namesakeWaveletRedundancy (information theory)Dimension (vector space)Computer scienceJacobian matrix and determinantsymbolsEntropy (information theory)Total correlationEfficient coding hypothesisAlgorithmCurse of dimensionalityProceedings of Entropy 2021: The Scientific Tool of the 21st Century
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DOBRO : a prediction error correcting robot under drifts

2016

We propose DOBRO, a light online learning module, which is equipped with a smart correction policy helping making decision to correct or not the given prediction depending on how likely the correction will lead to a better prediction performance. DOBRO is a standalone module requiring nothing more than a time series of prediction errors and it is flexible to be integrated into any black-box model to improve its performance under drifts. We performed evaluation in a real-world application with bus arrival time prediction problem. The obtained results show that DOBRO improved prediction performance significantly meanwhile it did not hurt the accuracy when drift does not happen.

ta113Concept driftComputer scienceMean squared prediction error02 engineering and technologyARIMAconcept drifton-line prediction error correction020204 information systems0202 electrical engineering electronic engineering information engineeringRobot020201 artificial intelligence & image processingAutoregressive integrated moving averageSimulation
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A novel heuristic memetic clustering algorithm

2013

In this paper we introduce a novel clustering algorithm based on the Memetic Algorithm meta-heuristic wherein clusters are iteratively evolved using a novel single operator employing a combination of heuristics. Several heuristics are described and employed for the three types of selections used in the operator. The algorithm was exhaustively tested on three benchmark problems and compared to a classical clustering algorithm (k-Medoids) using the same performance metrics. The results show that our clustering algorithm consistently provides better clustering solutions with less computational effort.

ta113Determining the number of clusters in a data setBiclusteringClustering high-dimensional dataDBSCANComputingMethodologies_PATTERNRECOGNITIONTheoretical computer scienceCURE data clustering algorithmCorrelation clusteringCanopy clustering algorithmCluster analysisAlgorithmMathematics2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
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Linear fusion of interrupted reports in cooperative spectrum sensing for cognitive radio networks

2015

Interrupted reporting has recently been introduced as an effective method to increase the energy efficiency of cooperative spectrum sensing schemes in cognitive radio networks. In this paper, joint optimization of the reporting and fusion phases in a cooperative sensing with interrupted reporting is considered. This optimization aims at finding the best weights used at the fusion center to construct a linear fusion of the received interrupted reports, jointly with Bernoulli distributions governing the statistical behavior of the interruptions. The problem is formulated by using the deflection criterion and as a nonconvex quadratic program which is then solved for a suboptimal solution, in a…

ta113Mathematical optimizationFusionta213Artificial neural networkComputer sciencedecision fusioncooperative spectrum sensingBernoulli's principleCognitive radionon-ideal reporting channelscorrelationcognitive radio (CR)Quadratic programmingEfficient energy use2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
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Combining PCA and multiset CCA for dimension reduction when group ICA is applied to decompose naturalistic fMRI data

2015

An extension of group independent component analysis (GICA) is introduced, where multi-set canonical correlation analysis (MCCA) is combined with principal component analysis (PCA) for three-stage dimension reduction. The method is applied on naturalistic functional MRI (fMRI) images acquired during task-free continuous music listening experiment, and the results are compared with the outcome of the conventional GICA. The extended GICA resulted slightly faster ICA convergence and, more interestingly, extracted more stimulus-related components than its conventional counterpart. Therefore, we think the extension is beneficial enhancement for GICA, especially when applied to challenging fMRI d…

ta113MultisetPCAGroup (mathematics)business.industrydimension reductionSpeech recognitionDimensionality reductionPattern recognitionMusic listeningta3112naturalistic fMRIGroup independent component analysisPrincipal component analysistemporal cocatenationArtificial intelligenceCanonical correlationbusinessmultiset CCAMathematics
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