Gaussian-mixture umbrella sampling
Maragakis, Paul; van der Vaart, Arjan; Karplus, Martin
2009-01-01
We introduce the Gaussian-mixture umbrella sampling method (GAMUS), a biased molecular dynamics technique based on adaptive umbrella sampling that efficiently escapes free energy minima in multi-dimensional problems. The prior simulation data are reweighted with a maximum likelihood formulation, and the new approximate probability density is fit to a Gaussian-mixture model, augmented by information about the unsampled areas. The method can be used to identify free energy minima in multi-dimen...
Gaussian mixture model of heart rate variability.
Directory of Open Access Journals (Sweden)
Tommaso Costa
Full Text Available Heart rate variability (HRV is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters.
Transport of a two-component mixture in one-dimensional channels
Borman, VD; Tronin, VN; Tronin, [No Value; Troyan, [No Value
2004-01-01
The transport of a two-component gas mixture in subnanometer channels is investigated theoretically for an arbitrary filling of channels. Special attention is paid to consistent inclusion of density effects, which are associated both with the interaction and with a finite size of particles. The anal
Transport of a two-component mixture in one-dimensional channels
Borman, VD; Tronin, VN; Tronin, [No Value; Troyan, [No Value
2004-01-01
The transport of a two-component gas mixture in subnanometer channels is investigated theoretically for an arbitrary filling of channels. Special attention is paid to consistent inclusion of density effects, which are associated both with the interaction and with a finite size of particles. The
Modeling text with generalizable Gaussian mixtures
DEFF Research Database (Denmark)
Hansen, Lars Kai; Sigurdsson, Sigurdur; Kolenda, Thomas
2000-01-01
We apply and discuss generalizable Gaussian mixture (GGM) models for text mining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of these models depends on the dimensionality of the representation and the sample size. We discuss...
The Supervised Learning Gaussian Mixture Model
Institute of Scientific and Technical Information of China (English)
马继涌; 高文
1998-01-01
The traditional Gaussian Mixture Model(GMM)for pattern recognition is an unsupervised learning method.The parameters in the model are derived only by the training samples in one class without taking into account the effect of sample distributions of other classes,hence,its recognition accuracy is not ideal sometimes.This paper introduces an approach for estimating the parameters in GMM in a supervising way.The Supervised Learning Gaussian Mixture Model(SLGMM)improves the recognition accuracy of the GMM.An experimental example has shown its effectiveness.The experimental results have shown that the recognition accuracy derived by the approach is higher than those obtained by the Vector Quantization(VQ)approach,the Radial Basis Function (RBF) network model,the Learning Vector Quantization (LVQ) approach and the GMM.In addition,the training time of the approach is less than that of Multilayer Perceptrom(MLP).
DEFF Research Database (Denmark)
Bellotti, Filipe Furlan; Salami Dehkharghani, Amin; Zinner, Nikolaj Thomas
2017-01-01
We investigate one-dimensional harmonically trapped two-component systems for repulsive interaction strengths ranging from the non-interacting to the strongly interacting regime for Fermi-Fermi mixtures. A new and powerful mapping between the interaction strength parameters from a continuous......) and exact diagonalization) and analytically. Since DMRG results do not converge as the interaction strength is increased, analytical solutions are used as a benchmark to identify the point where these calculations become unstable. We use the proposed mapping to set a quantitative limit on the interaction...
Two-component mixture model: Application to palm oil and exchange rate
Phoong, Seuk-Yen; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad
2014-12-01
Palm oil is a seed crop which is widely adopt for food and non-food products such as cookie, vegetable oil, cosmetics, household products and others. Palm oil is majority growth in Malaysia and Indonesia. However, the demand for palm oil is getting growth and rapidly running out over the years. This phenomenal cause illegal logging of trees and destroy the natural habitat. Hence, the present paper investigates the relationship between exchange rate and palm oil price in Malaysia by using Maximum Likelihood Estimation via Newton-Raphson algorithm to fit a two components mixture model. Besides, this paper proposes a mixture of normal distribution to accommodate with asymmetry characteristics and platykurtic time series data.
Video compressive sensing using Gaussian mixture models.
Yang, Jianbo; Yuan, Xin; Liao, Xuejun; Llull, Patrick; Brady, David J; Sapiro, Guillermo; Carin, Lawrence
2014-11-01
A Gaussian mixture model (GMM)-based algorithm is proposed for video reconstruction from temporally compressed video measurements. The GMM is used to model spatio-temporal video patches, and the reconstruction can be efficiently computed based on analytic expressions. The GMM-based inversion method benefits from online adaptive learning and parallel computation. We demonstrate the efficacy of the proposed inversion method with videos reconstructed from simulated compressive video measurements, and from a real compressive video camera. We also use the GMM as a tool to investigate adaptive video compressive sensing, i.e., adaptive rate of temporal compression.
Bellotti, Filipe F.; Dehkharghani, Amin S.; Zinner, Nikolaj T.
2017-02-01
We investigate one-dimensional harmonically trapped two-component systems for repulsive interaction strengths ranging from the non-interacting to the strongly interacting regime for Fermi-Fermi mixtures. A new and powerful mapping between the interaction strength parameters from a continuous Hamiltonian and a discrete lattice Hamiltonian is derived. As an example, we show that this mapping does not depend neither on the state of the system nor on the number of particles. Energies, density profiles and correlation functions are obtained both numerically (density matrix renormalization group (DMRG) and exact diagonalization) and analytically. Since DMRG results do not converge as the interaction strength is increased, analytical solutions are used as a benchmark to identify the point where these calculations become unstable. We use the proposed mapping to set a quantitative limit on the interaction parameter of a discrete lattice Hamiltonian above which DMRG gives unrealistic results.
Statistical Compressed Sensing of Gaussian Mixture Models
Yu, Guoshen
2011-01-01
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution, and achieving accurate reconstruction on average, is introduced. SCS based on Gaussian models is investigated in depth. For signals that follow a single Gaussian model, with Gaussian or Bernoulli sensing matrices of O(k) measurements, considerably smaller than the O(k log(N/k)) required by conventional CS based on sparse models, where N is the signal dimension, and with an optimal decoder implemented via linear filtering, significantly faster than the pursuit decoders applied in conventional CS, the error of SCS is shown tightly upper bounded by a constant times the best k-term approximation error, with overwhelming probability. The failure probability is also significantly smaller than that of conventional sparsity-oriented CS. Stronger yet simpler results further show that for any sensing matrix, the error of Gaussian SCS is u...
Statistical Compressive Sensing of Gaussian Mixture Models
Yu, Guoshen
2010-01-01
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution and achieving accurate reconstruction on average, is introduced. For signals following a Gaussian distribution, with Gaussian or Bernoulli sensing matrices of O(k) measurements, considerably smaller than the O(k log(N/k)) required by conventional CS, where N is the signal dimension, and with an optimal decoder implemented with linear filtering, significantly faster than the pursuit decoders applied in conventional CS, the error of SCS is shown tightly upper bounded by a constant times the k-best term approximation error, with overwhelming probability. The failure probability is also significantly smaller than that of conventional CS. Stronger yet simpler results further show that for any sensing matrix, the error of Gaussian SCS is upper bounded by a constant times the k-best term approximation with probability one, and the ...
Phase equilibria in DOPC/DPPC: Conversion from gel to subgel in two component mixtures.
Schmidt, Miranda L; Ziani, Latifa; Boudreau, Michelle; Davis, James H
2009-11-07
Biological membranes contain a mixture of phospholipids with varying degrees of hydrocarbon chain unsaturation. Mixtures of long chain saturated and unsaturated lipids with cholesterol have attracted a lot of attention because of the formation of two coexisting fluid bilayer phases in such systems over a broad range of temperature and composition. Interpretation of the phase behavior of such ternary mixtures must be based on a thorough understanding of the phase behavior of the binary mixtures formed with the same components. This article describes the phase behavior of mixtures of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) with 1,2-di-d(31)-palmitoyl-sn-glycero-3-phosphocholine (DPPC) between -20 and 50 degrees C. Particular attention has been paid to the phase coexistence below about 16 degrees C where the subgel phase appears. The changes in the shape of the spectrum (and its spectral moments) during the slow transformation process leads to the conclusion that below 16 degrees C the gel phase is metastable and the gel component of the two-phase mixture slowly transforms to the subgel phase with a slightly different composition. This results in a line of three-phase coexistence near 16 degrees C. Analysis of the transformation of the metastable gel domains into the subgel phase using the nucleation and growth model shows that the subgel domain growth is a two dimensional process.
Directory of Open Access Journals (Sweden)
Ghenadie Bulgac
2006-12-01
Full Text Available In this paper we find the analytical solution of simple one-dimensional unsteady elastic problem of two-component mixture using Laplace integral transformation. The integral transformations simplify the initial motion systems for finding analytical solutions. The analytical solutions are represented as the graphic on time dependence in the fixed point of medium, and the graphic on the horizontal coordinate at the fixed time.
Tails assumptions and posterior concentration rates for mixtures of Gaussians
Naulet, Zacharie; Rousseau, Judith
2016-01-01
Nowadays in density estimation, posterior rates of convergence for location and location-scale mixtures of Gaussians are only known under light-tail assumptions; with better rates achieved by location mixtures. It is conjectured, but not proved, that the situation should be reversed under heavy tails assumptions. The conjecture is based on the feeling that there is no need to achieve a good order of approximation in regions with few data (say, in the tails), favoring location-scale mixtures w...
Gaussian mixture models as flux prediction method for central receivers
Grobler, Annemarie; Gauché, Paul; Smit, Willie
2016-05-01
Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.
Minimum Mean Square Error Estimation Under Gaussian Mixture Statistics
Flam, John T; Kansanen, Kimmo; Ekman, Torbjorn
2011-01-01
This paper investigates the minimum mean square error (MMSE) estimation of x, given the observation y = Hx+n, when x and n are independent and Gaussian Mixture (GM) distributed. The introduction of GM distributions, represents a generalization of the more familiar and simpler Gaussian signal and Gaussian noise instance. We present the necessary theoretical foundation and derive the MMSE estimator for x in a closed form. Furthermore, we provide upper and lower bounds for its mean square error (MSE). These bounds are validated through Monte Carlo simulations.
Continuous fractionation of a two-component mixture by zone electrophoresis.
Zalewski, Dawid R; Gardeniers, Han J G E
2009-12-01
Synchronized continuous-flow zone electrophoresis is a recently demonstrated tool for performing electrophoretic fractionation of a complex sample. The method resembles free flow electrophoresis, but unlike in that technique, no mechanical fluid pumping is required. Instead, fast electrokinetic flow switching is used to produce complex stream patterns, which results in lateral separation of components in a separation chamber. Here a solution is presented which allows for simultaneous collection of two fractions in synchronized continuous-flow zone electrophoresis. The method is demonstrated on a model mixture, with subsequent evaluation of the collected fractions purity by MCE. The necessary theoretical background is provided including both steering schemes and calculations of optimum operating points.
Improved Gaussian Mixture Models for Adaptive Foreground Segmentation
DEFF Research Database (Denmark)
Katsarakis, Nikolaos; Pnevmatikakis, Aristodemos; Tan, Zheng-Hua
2016-01-01
Adaptive foreground segmentation is traditionally performed using Stauffer & Grimson’s algorithm that models every pixel of the frame by a mixture of Gaussian distributions with continuously adapted parameters. In this paper we provide an enhancement of the algorithm by adding two important dynamic...... elements to the baseline algorithm: The learning rate can change across space and time, while the Gaussian distributions can be merged together if they become similar due to their adaptation process. We quantify the importance of our enhancements and the effect of parameter tuning using an annotated...
Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs
DEFF Research Database (Denmark)
Jensen, Jesper Højvang; Ellis, Dan P. W.; Christensen, Mads Græsbøll
2007-01-01
In music similarity and in the related task of genre classification, a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although the norma......In music similarity and in the related task of genre classification, a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although...... the normalized L2 distance was slightly inferior to the Kullback-Leibler distance with respect to classification performance, it has the advantage of obeying the triangle inequality, which allows for efficient searching....
Detecting Clusters in Atom Probe Data with Gaussian Mixture Models.
Zelenty, Jennifer; Dahl, Andrew; Hyde, Jonathan; Smith, George D W; Moody, Michael P
2017-04-01
Accurately identifying and extracting clusters from atom probe tomography (APT) reconstructions is extremely challenging, yet critical to many applications. Currently, the most prevalent approach to detect clusters is the maximum separation method, a heuristic that relies heavily upon parameters manually chosen by the user. In this work, a new clustering algorithm, Gaussian mixture model Expectation Maximization Algorithm (GEMA), was developed. GEMA utilizes a Gaussian mixture model to probabilistically distinguish clusters from random fluctuations in the matrix. This machine learning approach maximizes the data likelihood via expectation maximization: given atomic positions, the algorithm learns the position, size, and width of each cluster. A key advantage of GEMA is that atoms are probabilistically assigned to clusters, thus reflecting scientifically meaningful uncertainty regarding atoms located near precipitate/matrix interfaces. GEMA outperforms the maximum separation method in cluster detection accuracy when applied to several realistically simulated data sets. Lastly, GEMA was successfully applied to real APT data.
Invariant image object recognition using Gaussian mixture densities
Dahmen, Jörg
2002-01-01
In this work, a statistical image object recognition system is presented, which is based on the use of Gaussian mixture densities in the context of the Bayesian decision rule. Optionally, to reduce the number of free model parameters, a linear discriminant analysis is applied. This baseline system is then extended with respect to the incorporation of invariances. To do so, we start by suitably multiplying the available reference images. This idea is then applied to the observations to be clas...
Hidden Markov Models with Factored Gaussian Mixtures Densities
Institute of Scientific and Technical Information of China (English)
LI Hao-zheng; LIU Zhi-qiang; ZHU Xiang-hua
2004-01-01
We present a factorial representation of Gaussian mixture models for observation densities in Hidden Markov Models(HMMs), which uses the factorial learning in the HMM framework. We derive the reestimation formulas for estimating the factorized parameters by the Expectation Maximization (EM) algorithm. We conduct several experiments to compare the performance of this model structure with Factorial Hidden Markov Models(FHMMs) and HMMs, some conclusions and promising empirical results are presented.
XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling
Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.
2017-08-01
XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.
Multi-resolution image segmentation based on Gaussian mixture model
Institute of Scientific and Technical Information of China (English)
Tang Yinggan; Liu Dong; Guan Xinping
2006-01-01
Mixture model based image segmentation method, which assumes that image pixels are independent and do not consider the position relationship between pixels, is not robust to noise and usually leads to misclassification. A new segmentation method, called multi-resolution Gaussian mixture model method, is proposed. First, an image pyramid is constructed and son-father link relationship is built between each level of pyramid. Then the mixture model segmentation method is applied to the top level. The segmentation result on the top level is passed top-down to the bottom level according to the son-father link relationship between levels. The proposed method considers not only local but also global information of image, it overcomes the effect of noise and can obtain better segmentation result. Experimental result demonstrates its effectiveness.
Classifying Gamma-Ray Bursts with Gaussian Mixture Model
Yang, En-Bo; Choi, Chul-Sung; Chang, Heon-Young
2016-01-01
Using Gaussian Mixture Model (GMM) and Expectation Maximization Algorithm, we perform an analysis of time duration ($T_{90}$) for \\textit{CGRO}/BATSE, \\textit{Swift}/BAT and \\textit{Fermi}/GBM Gamma-Ray Bursts. The $T_{90}$ distributions of 298 redshift-known \\textit{Swift}/BAT GRBs have also been studied in both observer and rest frames. Bayesian Information Criterion has been used to compare between different GMM models. We find that two Gaussian components are better to describe the \\textit{CGRO}/BATSE and \\textit{Fermi}/GBM GRBs in the observer frame. Also, we caution that two groups are expected for the \\textit{Swift}/BAT bursts in the rest frame, which is consistent with some previous results. However, \\textit{Swift} GRBs in the observer frame seem to show a trimodal distribution, of which the superficial intermediate class may result from the selection effect of \\textit{Swift}/BAT.
Classifying gamma-ray bursts with Gaussian Mixture Model
Zhang, Zhi-Bin; Yang, En-Bo; Choi, Chul-Sung; Chang, Heon-Young
2016-11-01
Using Gaussian Mixture Model (GMM) and expectation-maximization algorithm, we perform an analysis of time duration (T90) for Compton Gamma Ray Observatory (CGRO)/BATSE, Swift/BAT and Fermi/GBM gamma-ray bursts (GRBs). The T90 distributions of 298 redshift-known Swift/BAT GRBs have also been studied in both observer and rest frames. Bayesian information criterion has been used to compare between different GMM models. We find that two Gaussian components are better to describe the CGRO/BATSE and Fermi/GBM GRBs in the observer frame. Also, we caution that two groups are expected for the Swift/BAT bursts in the rest frame, which is consistent with some previous results. However, Swift GRBs in the observer frame seem to show a trimodal distribution, of which the superficial intermediate class may result from the selection effect of Swift/BAT.
Rafal Podlaski; Francis Roesch
2014-01-01
In recent years finite-mixture models have been employed to approximate and model empirical diameter at breast height (DBH) distributions. We used two-component mixtures of either the Weibull distribution or the gamma distribution for describing the DBH distributions of mixed-species, two-cohort forest stands, to analyse the relationships between the DBH components,...
Novel blind source separation algorithm using Gaussian mixture density function
Institute of Scientific and Technical Information of China (English)
孔薇; 杨杰; 周越
2004-01-01
The blind source separation (BSS) is an important task for numerous applications in signal processing, communications and array processing. But for many complex sources blind separation algorithms are not efficient because the probability distribution of the sources cannot be estimated accurately. So in this paper, to justify the ME(maximum enteropy) approach, the relation between the ME and the MMI(minimum mutual information) is elucidated first. Then a novel algorithm that uses Gaussian mixture density to approximate the probability distribution of the sources is presented based on the ME approach. The experiment of the BSS of ship-radiated noise demonstrates that the proposed algorithm is valid and efficient.
Molecular Code Division Multiple Access: Gaussian Mixture Modeling
Zamiri-Jafarian, Yeganeh
Communications between nano-devices is an emerging research field in nanotechnology. Molecular Communication (MC), which is a bio-inspired paradigm, is a promising technique for communication in nano-network. In MC, molecules are administered to exchange information among nano-devices. Due to the nature of molecular signals, traditional communication methods can't be directly applied to the MC framework. The objective of this thesis is to present novel diffusion-based MC methods when multi nano-devices communicate with each other in the same environment. A new channel model and detection technique, along with a molecular-based access method, are proposed in here for communication between asynchronous users. In this work, the received molecular signal is modeled as a Gaussian mixture distribution when the MC system undergoes Brownian noise and inter-symbol interference (ISI). This novel approach demonstrates a suitable modeling for diffusion-based MC system. Using the proposed Gaussian mixture model, a simple receiver is designed by minimizing the error probability. To determine an optimum detection threshold, an iterative algorithm is derived which minimizes a linear approximation of the error probability function. Also, a memory-based receiver is proposed to improve the performance of the MC system by considering previously detected symbols in obtaining the threshold value. Numerical evaluations reveal that theoretical analysis of the bit error rate (BER) performance based on the Gaussian mixture model match simulation results very closely. Furthermore, in this thesis, molecular code division multiple access (MCDMA) is proposed to overcome the inter-user interference (IUI) caused by asynchronous users communicating in a shared propagation environment. Based on the selected molecular codes, a chip detection scheme with an adaptable threshold value is developed for the MCDMA system when the proposed Gaussian mixture model is considered. Results indicate that the
Immune adaptive Gaussian mixture par ticle filter for state estimation
Institute of Scientific and Technical Information of China (English)
Wenlong Huang; Xiaodan Wang; Yi Wang; Guohong Li
2015-01-01
The particle filter (PF) is a flexible and powerful sequen-tial Monte Carlo (SMC) technique capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. However, the generic PF suffers from particle degeneracy and sample im-poverishment, which greatly affects its performance for nonlinear, non-Gaussian tracking problems. To deal with those issues, an improved PF is proposed. The algorithm consists of a PF that uses an immune adaptive Gaussian mixture model (IAGM) based immune algorithm to re-approximate the posterior density. At the same time, three immune antibody operators are embed in the new filter. Instead of using a resample strategy, the newest obser-vation and conditional likelihood are integrated into those immune antibody operators to update the particles, which can further im-prove the diversity of particles, and drive particles toward their close local maximum of the posterior probability. The improved PF algorithm can produce a closed-form expression for the posterior state distribution. Simulation results show the proposed algorithm can maintain the effectiveness and diversity of particles and avoid sample impoverishment, and its performance is superior to several PFs and Kalman filters.
Efficient speaker verification using Gaussian mixture model component clustering.
Energy Technology Data Exchange (ETDEWEB)
De Leon, Phillip L. (New Mexico State University, Las Cruces, NM); McClanahan, Richard D.
2012-04-01
In speaker verification (SV) systems that employ a support vector machine (SVM) classifier to make decisions on a supervector derived from Gaussian mixture model (GMM) component mean vectors, a significant portion of the computational load is involved in the calculation of the a posteriori probability of the feature vectors of the speaker under test with respect to the individual component densities of the universal background model (UBM). Further, the calculation of the sufficient statistics for the weight, mean, and covariance parameters derived from these same feature vectors also contribute a substantial amount of processing load to the SV system. In this paper, we propose a method that utilizes clusters of GMM-UBM mixture component densities in order to reduce the computational load required. In the adaptation step we score the feature vectors against the clusters and calculate the a posteriori probabilities and update the statistics exclusively for mixture components belonging to appropriate clusters. Each cluster is a grouping of multivariate normal distributions and is modeled by a single multivariate distribution. As such, the set of multivariate normal distributions representing the different clusters also form a GMM. This GMM is referred to as a hash GMM which can be considered to a lower resolution representation of the GMM-UBM. The mapping that associates the components of the hash GMM with components of the original GMM-UBM is referred to as a shortlist. This research investigates various methods of clustering the components of the GMM-UBM and forming hash GMMs. Of five different methods that are presented one method, Gaussian mixture reduction as proposed by Runnall's, easily outperformed the other methods. This method of Gaussian reduction iteratively reduces the size of a GMM by successively merging pairs of component densities. Pairs are selected for merger by using a Kullback-Leibler based metric. Using Runnal's method of reduction, we
Fuzzy local Gaussian mixture model for brain MR image segmentation.
Ji, Zexuan; Xia, Yong; Sun, Quansen; Chen, Qiang; Xia, Deshen; Feng, David Dagan
2012-05-01
Accurate brain tissue segmentation from magnetic resonance (MR) images is an essential step in quantitative brain image analysis. However, due to the existence of noise and intensity inhomogeneity in brain MR images, many segmentation algorithms suffer from limited accuracy. In this paper, we assume that the local image data within each voxel's neighborhood satisfy the Gaussian mixture model (GMM), and thus propose the fuzzy local GMM (FLGMM) algorithm for automated brain MR image segmentation. This algorithm estimates the segmentation result that maximizes the posterior probability by minimizing an objective energy function, in which a truncated Gaussian kernel function is used to impose the spatial constraint and fuzzy memberships are employed to balance the contribution of each GMM. We compared our algorithm to state-of-the-art segmentation approaches in both synthetic and clinical data. Our results show that the proposed algorithm can largely overcome the difficulties raised by noise, low contrast, and bias field, and substantially improve the accuracy of brain MR image segmentation.
Protein local conformations arise from a mixture of Gaussian distributions
Indian Academy of Sciences (India)
Ashish V Tendulkar; Babatunde Ogunnaike; Pramod P Wangikar
2007-08-01
The classical approaches for protein structure prediction rely either on homology of the protein sequence with a template structure or on ab initio calculations for energy minimization. These methods suffer from disadvantages such as the lack of availability of homologous template structures or intractably large conformational search space, respectively. The recently proposed fragment library based approaches first predict the local structures, which can be used in conjunction with the classical approaches of protein structure prediction. The accuracy of the predictions is dependent on the quality of the fragment library. In this work, we have constructed a library of local conformation classes purely based on geometric similarity. The local conformations are represented using Geometric Invariants, properties that remain unchanged under transformations such as translation and rotation, followed by dimension reduction via principal component analysis. The local conformations are then modeled as a mixture of Gaussian probability distribution functions (PDF). Each one of the Gaussian PDF’s corresponds to a conformational class with the centroid representing the average structure of that class. We find 46 classes when we use an octapeptide as a unit of local conformation. The protein 3-D structure can now be described as a sequence of local conformational classes. Further, it was of interest to see whether the local conformations can be predicted from the amino acid sequences. To that end, we have analyzed the correlation between sequence features and the conformational classes.
Decision Based Uncertainty Propagation Using Adaptive Gaussian Mixtures
Terejanu, Gabriel; Singh, Tarunraj; Scott, Peter D
2011-01-01
Given a decision process based on the approximate probability density function returned by a data assimilation algorithm, an interaction level between the decision making level and the data assimilation level is designed to incorporate the information held by the decision maker into the data assimilation process. Here the information held by the decision maker is a loss function at a decision time which maps the state space onto real numbers which represent the threat associated with different possible outcomes or states. The new probability density function obtained will address the region of interest, the area in the state space with the highest threat, and will provide overall a better approximation to the true conditional probability density function within it. The approximation used for the probability density function is a Gaussian mixture and a numerical example is presented to illustrate the concept.
Gaussian Mixture Model and Rjmcmc Based RS Image Segmentation
Shi, X.; Zhao, Q. H.
2017-09-01
For the image segmentation method based on Gaussian Mixture Model (GMM), there are some problems: 1) The number of component was usually a fixed number, i.e., fixed class and 2) GMM is sensitive to image noise. This paper proposed a RS image segmentation method that combining GMM with reversible jump Markov Chain Monte Carlo (RJMCMC). In proposed algorithm, GMM was designed to model the distribution of pixel intensity in RS image. Assume that the number of component was a random variable. Respectively build the prior distribution of each parameter. In order to improve noise resistance, used Gibbs function to model the prior distribution of GMM weight coefficient. According to Bayes' theorem, build posterior distribution. RJMCMC was used to simulate the posterior distribution and estimate its parameters. Finally, an optimal segmentation is obtained on RS image. Experimental results show that the proposed algorithm can converge to the optimal number of class and get an ideal segmentation results.
Efficient Kernel-Based Ensemble Gaussian Mixture Filtering
Liu, Bo
2015-11-11
We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.
Replacing standard galaxy profiles with mixtures of Gaussians
Hogg, David W
2012-01-01
Exponential, de Vaucouleurs, and S\\'ersic profiles are simple and successful models for fitting two-dimensional images of galaxies. One numerical issue encountered in this kind of fitting is the pixel rendering and convolution (or correlation) of the models with the telescope point-spread function (PSF); these operations are slow, and easy to get slightly wrong at small radii. Here we exploit the realization that these models can be approximated to arbitrary accuracy with a mixture (linear superposition) of two-dimensional Gaussians (MoGs). MoGs are fast to render and fast to affine-transform. Most importantly, if you have a MoG model for the pixel-convolved PSF, the PSF-convolved, affine-transformed galaxy models are themselves MoGs and therefore very fast to compute, integrate, and render precisely. We present worked examples that can be directly used in image fitting; we are using them ourselves. The MoG profiles we provide can be swapped in to replace the standard models in any image-fitting code; they sp...
Compressive sensing by learning a Gaussian mixture model from measurements.
Yang, Jianbo; Liao, Xuejun; Yuan, Xin; Llull, Patrick; Brady, David J; Sapiro, Guillermo; Carin, Lawrence
2015-01-01
Compressive sensing of signals drawn from a Gaussian mixture model (GMM) admits closed-form minimum mean squared error reconstruction from incomplete linear measurements. An accurate GMM signal model is usually not available a priori, because it is difficult to obtain training signals that match the statistics of the signals being sensed. We propose to solve that problem by learning the signal model in situ, based directly on the compressive measurements of the signals, without resorting to other signals to train a model. A key feature of our method is that the signals being sensed are treated as random variables and are integrated out in the likelihood. We derive a maximum marginal likelihood estimator (MMLE) that maximizes the likelihood of the GMM of the underlying signals given only their linear compressive measurements. We extend the MMLE to a GMM with dominantly low-rank covariance matrices, to gain computational speedup. We report extensive experimental results on image inpainting, compressive sensing of high-speed video, and compressive hyperspectral imaging (the latter two based on real compressive cameras). The results demonstrate that the proposed methods outperform state-of-the-art methods by significant margins.
Mixtures of conditional Gaussian scale mixtures applied to multiscale image representations.
Directory of Open Access Journals (Sweden)
Lucas Theis
Full Text Available We present a probabilistic model for natural images that is based on mixtures of Gaussian scale mixtures and a simple multiscale representation. We show that it is able to generate images with interesting higher-order correlations when trained on natural images or samples from an occlusion-based model. More importantly, our multiscale model allows for a principled evaluation. While it is easy to generate visually appealing images, we demonstrate that our model also yields the best performance reported to date when evaluated with respect to the cross-entropy rate, a measure tightly linked to the average log-likelihood. The ability to quantitatively evaluate our model differentiates it from other multiscale models, for which evaluation of these kinds of measures is usually intractable.
Podlaski, Rafał; Roesch, Francis A
2014-03-01
In recent years finite-mixture models have been employed to approximate and model empirical diameter at breast height (DBH) distributions. We used two-component mixtures of either the Weibull distribution or the gamma distribution for describing the DBH distributions of mixed-species, two-cohort forest stands, to analyse the relationships between the DBH components, age cohorts and dominant species, and to assess the significance of differences between the mixture distributions and the kernel density estimates. The data consisted of plots from the Świętokrzyski National Park (Central Poland) and areas close to and including the North Carolina section of the Great Smoky Mountains National Park (USA; southern Appalachians). The fit of the mixture Weibull model to empirical DBH distributions had a precision similar to that of the mixture gamma model, slightly less accurate estimate was obtained with the kernel density estimator. Generally, in the two-cohort, two-storied, multi-species stands in the southern Appalachians, the two-component DBH structure was associated with age cohort and dominant species. The 1st DBH component of the mixture model was associated with the 1st dominant species sp1 occurred in young age cohort (e.g., sweetgum, eastern hemlock); and to a lesser degree, the 2nd DBH component was associated with the 2nd dominant species sp2 occurred in old age cohort (e.g., loblolly pine, red maple). In two-cohort, partly multilayered, stands in the Świętokrzyski National Park, the DBH structure was usually associated with only age cohorts (two dominant species often occurred in both young and old age cohorts). When empirical DBH distributions representing stands of complex structure are approximated using mixture models, the convergence of the estimation process is often significantly dependent on the starting strategies. Depending on the number of DBHs measured, three methods for choosing the initial values are recommended: min.k/max.k, 0.5/1.5/mean
Statistical imitation system using relational interest points and Gaussian mixture models
CSIR Research Space (South Africa)
Claassens, J
2009-11-01
Full Text Available The author proposes an imitation system that uses relational interest points (RIPs) and Gaussian mixture models (GMMs) to characterize a behaviour. The system's structure is inspired by the Robot Programming by Demonstration (RDP) paradigm...
Background based Gaussian mixture model lesion segmentation in PET
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Soffientini, Chiara Dolores, E-mail: chiaradolores.soffientini@polimi.it; Baselli, Giuseppe [DEIB, Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan 20133 (Italy); De Bernardi, Elisabetta [Department of Medicine and Surgery, Tecnomed Foundation, University of Milano—Bicocca, Monza 20900 (Italy); Zito, Felicia; Castellani, Massimo [Nuclear Medicine Department, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, via Francesco Sforza 35, Milan 20122 (Italy)
2016-05-15
Purpose: Quantitative {sup 18}F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. Methods: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previous analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). Results: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was
Institute of Scientific and Technical Information of China (English)
P. K. Paul; Md. N. Islam; D. Bhattacharjee; S. A. Hussain
2007-01-01
We report the miscibility characteristics of two components in a binary mixture of 9-phenyl anthracene (PA) mixed with stearic acid (SA) or polymethyl methacrylate (PMMA). The behaviour of surface pressure versus area per molecule isotherms reveal that the area per molecule decreases systematically with increasing molefractions of PA. The characteristics of areas per molecule versus molefractions and collapse pressure vs molefraction indicate that various interactions involved among the sample and matrix molecules. The interaction scheme is found to change with the change in surface pressure and molefraction of mixing. Scanning electron microscopic study confirms the aggregation of PA molecules in the mixed films.
Overlapping Mixtures of Gaussian Processes for the Data Association Problem
Lázaro-Gredilla, Miguel; Lawrence, Neil
2011-01-01
In this work we introduce a mixture of GPs to address the data association problem, i.e. to label a group of observations according to the sources that generated them. Unlike several previously proposed GP mixtures, the novel mixture has the distinct characteristic of using no gating function to determine the association of samples and mixture components. Instead, all the GPs in the mixture are global and samples are clustered following "trajectories" across input space. We use a non-standard variational Bayesian algorithm to efficiently recover sample labels and learn the hyperparameters. We show how multi-object tracking problems can be disambiguated and also explore the characteristics of the model in traditional regression settings.
Directory of Open Access Journals (Sweden)
Shih-Sian Cheng
2004-12-01
Full Text Available We propose a self-splitting Gaussian mixture learning (SGML algorithm for Gaussian mixture modelling. The SGML algorithm is deterministic and is able to find an appropriate number of components of the Gaussian mixture model (GMM based on a self-splitting validity measure, Bayesian information criterion (BIC. It starts with a single component in the feature space and splits adaptively during the learning process until the most appropriate number of components is found. The SGML algorithm also performs well in learning the GMM with a given component number. In our experiments on clustering of a synthetic data set and the text-independent speaker identification task, we have observed the ability of the SGML for model-based clustering and automatically determining the model complexity of the speaker GMMs for speaker identification.
Infrared image segmentation based on region of interest extraction with Gaussian mixture modeling
Yeom, Seokwon
2017-05-01
Infrared (IR) imaging has the capability to detect thermal characteristics of objects under low-light conditions. This paper addresses IR image segmentation with Gaussian mixture modeling. An IR image is segmented with Expectation Maximization (EM) method assuming the image histogram follows the Gaussian mixture distribution. Multi-level segmentation is applied to extract the region of interest (ROI). Each level of the multi-level segmentation is composed of the k-means clustering, the EM algorithm, and a decision process. The foreground objects are individually segmented from the ROI windows. In the experiments, various methods are applied to the IR image capturing several humans at night.
Bridging asymptotic independence and dependence in spatial exbtremes using Gaussian scale mixtures
Huser, Raphaël
2017-06-23
Gaussian scale mixtures are constructed as Gaussian processes with a random variance. They have non-Gaussian marginals and can exhibit asymptotic dependence unlike Gaussian processes, which are asymptotically independent except in the case of perfect dependence. In this paper, we study the extremal dependence properties of Gaussian scale mixtures and we unify and extend general results on their joint tail decay rates in both asymptotic dependence and independence cases. Motivated by the analysis of spatial extremes, we propose flexible yet parsimonious parametric copula models that smoothly interpolate from asymptotic dependence to independence and include the Gaussian dependence as a special case. We show how these new models can be fitted to high threshold exceedances using a censored likelihood approach, and we demonstrate that they provide valuable information about tail characteristics. In particular, by borrowing strength across locations, our parametric model-based approach can also be used to provide evidence for or against either asymptotic dependence class, hence complementing information given at an exploratory stage by the widely used nonparametric or parametric estimates of the χ and χ̄ coefficients. We demonstrate the capacity of our methodology by adequately capturing the extremal properties of wind speed data collected in the Pacific Northwest, US.
Directory of Open Access Journals (Sweden)
Nsiri Benayad
2010-01-01
Full Text Available This article investigates a new method of motion estimation based on block matching criterion through the modeling of image blocks by a mixture of two and three Gaussian distributions. Mixture parameters (weights, means vectors, and covariance matrices are estimated by the Expectation Maximization algorithm (EM which maximizes the log-likelihood criterion. The similarity between a block in the current image and the more resembling one in a search window on the reference image is measured by the minimization of Extended Mahalanobis distance between the clusters of mixture. Performed experiments on sequences of real images have given good results, and PSNR reached 3 dB.
Performance of BICM-T transceivers over Gaussian mixture noise channels
Malik, Muhammad Talha
2014-04-01
Experimental measurements have shown that the noise in many communication channels is non-Gaussian. Bit interleaved coded modulation (BICM) is very popular for spectrally efficient transmission. Recent results have shown that the performance of BICM using convolutional codes in non-fading channels can be significantly improved if the coded bits are not interleaved at all. This particular BICM design is called BICM trivial (BICM-T). In this paper, we analyze the performance of a generalized BICM-T design for communication over Gaussian mixture noise (GMN) channels. The results disclose that for an optimal bit error rate (BER) performance, the use of an interleaver in BICM for GMN channels depends upon the strength of the impulsive noise components in the Gaussian mixture. The results presented for 16-QAM show that the BICM-T can result in gains up to 1.5 dB for a target BER of 10-6 if the impulsive noise in the Gaussian mixture is below a certain threshold level. The simulation results verify the tightness of developed union bound (UB) on BER performance.
Iterative Diffusion-Based Distributed Cubature Gaussian Mixture Filter for Multisensor Estimation
Directory of Open Access Journals (Sweden)
Bin Jia
2016-10-01
Full Text Available In this paper, a distributed cubature Gaussian mixture filter (DCGMF based on an iterative diffusion strategy (DCGMF-ID is proposed for multisensor estimation and information fusion. The uncertainties are represented as Gaussian mixtures at each sensor node. A high-degree cubature Kalman filter provides accurate estimation of each Gaussian mixture component. An iterative diffusion scheme is utilized to fuse the mean and covariance of each Gaussian component obtained from each sensor node. The DCGMF-ID extends the conventional diffusion-based fusion strategy by using multiple iterative information exchanges among neighboring sensor nodes. The convergence property of the iterative diffusion is analyzed. In addition, it is shown that the convergence of the iterative diffusion can be interpreted from the information-theoretic perspective as minimization of the Kullback–Leibler divergence. The performance of the DCGMF-ID is compared with the DCGMF based on the average consensus (DCGMF-AC and the DCGMF based on the iterative covariance intersection (DCGMF-ICI via a maneuvering target-tracking problem using multiple sensors. The simulation results show that the DCGMF-ID has better performance than the DCGMF based on noniterative diffusion, which validates the benefit of iterative information exchanges. In addition, the DCGMF-ID outperforms the DCGMF-ICI and DCGMF-AC when the number of iterations is limited.
An efficient approach for shadow detection based on Gaussian mixture model
Institute of Scientific and Technical Information of China (English)
韩延祥; 张志胜; 陈芳; 陈恺
2014-01-01
An efficient approach was proposed for discriminating shadows from moving objects. In the background subtraction stage, moving objects were extracted. Then, the initial classification for moving shadow pixels and foreground object pixels was performed by using color invariant features. In the shadow model learning stage, instead of a single Gaussian distribution, it was assumed that the density function computed on the values of chromaticity difference or bright difference, can be modeled as a mixture of Gaussian consisting of two density functions. Meanwhile, the Gaussian parameter estimation was performed by using EM algorithm. The estimates were used to obtain shadow mask according to two constraints. Finally, experiments were carried out. The visual experiment results confirm the effectiveness of proposed method. Quantitative results in terms of the shadow detection rate and the shadow discrimination rate (the maximum values are 85.79%and 97.56%, respectively) show that the proposed approach achieves a satisfying result with post-processing step.
Directory of Open Access Journals (Sweden)
Cohen S.X.
2014-03-01
Full Text Available In this article, we describe a novel unsupervised spectral image segmentation algorithm. This algorithm extends the classical Gaussian Mixture Model-based unsupervised classification technique by incorporating a spatial flavor into the model: the spectra are modelized by a mixture of K classes, each with a Gaussian distribution, whose mixing proportions depend on the position. Using a piecewise constant structure for those mixing proportions, we are able to construct a penalized maximum likelihood procedure that estimates the optimal partition as well as all the other parameters, including the number of classes. We provide a theoretical guarantee for this estimation, even when the generating model is not within the tested set, and describe an efficient implementation. Finally, we conduct some numerical experiments of unsupervised segmentation from a real dataset.
Automated sleep spindle detection using IIR filters and a Gaussian Mixture Model.
Patti, Chanakya Reddy; Penzel, Thomas; Cvetkovic, Dean
2015-08-01
Sleep spindle detection using modern signal processing techniques such as the Short-Time Fourier Transform and Wavelet Analysis are common research methods. These methods are computationally intensive, especially when analysing data from overnight sleep recordings. The authors of this paper propose an alternative using pre-designed IIR filters and a multivariate Gaussian Mixture Model. Features extracted with IIR filters are clustered using a Gaussian Mixture Model without the use of any subject independent thresholds. The Algorithm was tested on a database consisting of overnight sleep PSG of 5 subjects and an online public spindles database consisting of six 30 minute sleep excerpts. An overall sensitivity of 57% and a specificity of 98.24% was achieved in the overnight database group and a sensitivity of 65.19% at a 16.9% False Positive proportion for the 6 sleep excerpts.
Filling the gaps: Gaussian mixture models from noisy, truncated or incomplete samples
Melchior, Peter
2016-01-01
We extend the common mixtures-of-Gaussians density estimation approach to account for a known sample incompleteness by simultaneous imputation from the current model. The method called GMMis generalizes existing Expectation-Maximization techniques for truncated data to arbitrary truncation geometries and probabilistic rejection. It can incorporate an uniform background distribution as well as independent multivariate normal measurement errors for each of the observed samples, and recovers an estimate of the error-free distribution from which both observed and unobserved samples are drawn. We compare GMMis to the standard Gaussian mixture model for simple test cases with different types of incompleteness, and apply it to observational data from the NASA Chandra X-ray telescope. The python code is capable of performing density estimation with millions of samples and thousands of model components and is released as an open-source package at https://github.com/pmelchior/pyGMMis
Directory of Open Access Journals (Sweden)
Yli-Harja Olli
2009-05-01
Full Text Available Abstract Background Cluster analysis has become a standard computational method for gene function discovery as well as for more general explanatory data analysis. A number of different approaches have been proposed for that purpose, out of which different mixture models provide a principled probabilistic framework. Cluster analysis is increasingly often supplemented with multiple data sources nowadays, and these heterogeneous information sources should be made as efficient use of as possible. Results This paper presents a novel Beta-Gaussian mixture model (BGMM for clustering genes based on Gaussian distributed and beta distributed data. The proposed BGMM can be viewed as a natural extension of the beta mixture model (BMM and the Gaussian mixture model (GMM. The proposed BGMM method differs from other mixture model based methods in its integration of two different data types into a single and unified probabilistic modeling framework, which provides a more efficient use of multiple data sources than methods that analyze different data sources separately. Moreover, BGMM provides an exceedingly flexible modeling framework since many data sources can be modeled as Gaussian or beta distributed random variables, and it can also be extended to integrate data that have other parametric distributions as well, which adds even more flexibility to this model-based clustering framework. We developed three types of estimation algorithms for BGMM, the standard expectation maximization (EM algorithm, an approximated EM and a hybrid EM, and propose to tackle the model selection problem by well-known model selection criteria, for which we test the Akaike information criterion (AIC, a modified AIC (AIC3, the Bayesian information criterion (BIC, and the integrated classification likelihood-BIC (ICL-BIC. Conclusion Performance tests with simulated data show that combining two different data sources into a single mixture joint model greatly improves the clustering
A Rough Set Bounded Spatially Constrained Asymmetric Gaussian Mixture Model for Image Segmentation.
Ji, Zexuan; Huang, Yubo; Sun, Quansen; Cao, Guo; Zheng, Yuhui
2017-01-01
Accurate image segmentation is an important issue in image processing, where Gaussian mixture models play an important part and have been proven effective. However, most Gaussian mixture model (GMM) based methods suffer from one or more limitations, such as limited noise robustness, over-smoothness for segmentations, and lack of flexibility to fit data. In order to address these issues, in this paper, we propose a rough set bounded asymmetric Gaussian mixture model with spatial constraint for image segmentation. First, based on our previous work where each cluster is characterized by three automatically determined rough-fuzzy regions, we partition the target image into three rough regions with two adaptively computed thresholds. Second, a new bounded indicator function is proposed to determine the bounded support regions of the observed data. The bounded indicator and posterior probability of a pixel that belongs to each sub-region is estimated with respect to the rough region where the pixel lies. Third, to further reduce over-smoothness for segmentations, two novel prior factors are proposed that incorporate the spatial information among neighborhood pixels, which are constructed based on the prior and posterior probabilities of the within- and between-clusters, and considers the spatial direction. We compare our algorithm to state-of-the-art segmentation approaches in both synthetic and real images to demonstrate the superior performance of the proposed algorithm.
CSIR Research Space (South Africa)
Miya, WS
2008-10-01
Full Text Available In this paper, a comparison between Extension Neural Network (ENN), Gaussian Mixture Model (GMM) and Hidden Markov model (HMM) is conducted for bushing condition monitoring. The monitoring process is a two-stage implementation of a classification...
Novel Methods for Surface EMG Analysis and Exploration Based on Multi-Modal Gaussian Mixture Models.
Directory of Open Access Journals (Sweden)
Anna Magdalena Vögele
Full Text Available This paper introduces a new method for data analysis of animal muscle activation during locomotion. It is based on fitting Gaussian mixture models (GMMs to surface EMG data (sEMG. This approach enables researchers/users to isolate parts of the overall muscle activation within locomotion EMG data. Furthermore, it provides new opportunities for analysis and exploration of sEMG data by using the resulting Gaussian modes as atomic building blocks for a hierarchical clustering. In our experiments, composite peak models representing the general activation pattern per sensor location (one sensor on the long back muscle, three sensors on the gluteus muscle on each body side were identified per individual for all 14 horses during walk and trot in the present study. Hereby we show the applicability of the method to identify composite peak models, which describe activation of different muscles throughout cycles of locomotion.
Unbiased free energy estimates in fast nonequilibrium transformations using Gaussian mixtures
Energy Technology Data Exchange (ETDEWEB)
Procacci, Piero [Dipartimento di Chimica, Università di Firenze, Via della Lastruccia 3, I-50019 Sesto Fiorentino, Italy and Centro Interdipartimentale per lo Studio delle Dinamiche Complesse (CSDC), Via Sansone 1, I-50019 Sesto Fiorentino (Italy)
2015-04-21
In this paper, we present an improved method for obtaining unbiased estimates of the free energy difference between two thermodynamic states using the work distribution measured in nonequilibrium driven experiments connecting these states. The method is based on the assumption that any observed work distribution is given by a mixture of Gaussian distributions, whose normal components are identical in either direction of the nonequilibrium process, with weights regulated by the Crooks theorem. Using the prototypical example for the driven unfolding/folding of deca-alanine, we show that the predicted behavior of the forward and reverse work distributions, assuming a combination of only two Gaussian components with Crooks derived weights, explains surprisingly well the striking asymmetry in the observed distributions at fast pulling speeds. The proposed methodology opens the way for a perfectly parallel implementation of Jarzynski-based free energy calculations in complex systems.
The Shape of Solar Cycles Described by a Simplified Binary Mixture of Gaussian Functions
Li, F. Y.; Xiang, N. B.; Kong, D. F.; Xie, J. L.
2017-01-01
Sunspot cycles usually present a double-peak structure. This work is devoted to using a function to describe the shape of sunspot cycles, including bimodal cycles, and we find that the shape of sunspot cycles can be described by a binary mixture of Gaussian functions with six parameters, two amplitudes, two gradients of curve, and two rising times, and the parameters could be reduced to three. The fitting result of this binary mixture of Gaussian functions is compared with some other functions used previously in the literature, and this function works pretty well, especially at cycle peaks. It is worth mentioning that the function can describe well the shape of those sunspot cycles that show double peaks, and it is superior to the binary mixture of the Laplace functions that was once utilized. The Solar Influences Data Analysis Center, on behalf of the World Data Center, recently issued a new version (version 2) of sunspot number. The characteristics of sunspot cycles are investigated, based on the function description of the new version.
Energy Technology Data Exchange (ETDEWEB)
Fouque, A.L.; Ciuciu, Ph.; Risser, L. [NeuroSpin/CEA, F-91191 Gif-sur-Yvette (France); Fouque, A.L.; Ciuciu, Ph.; Risser, L. [IFR 49, Institut d' Imagerie Neurofonctionnelle, Paris (France)
2009-07-01
In this paper, a novel statistical parcellation of intra-subject functional MRI (fMRI) data is proposed. The key idea is to identify functionally homogenous regions of interest from their hemodynamic parameters. To this end, a non-parametric voxel-based estimation of hemodynamic response function is performed as a prerequisite. Then, the extracted hemodynamic features are entered as the input data of a Multivariate Spatial Gaussian Mixture Model (MSGMM) to be fitted. The goal of the spatial aspect is to favor the recovery of connected components in the mixture. Our statistical clustering approach is original in the sense that it extends existing works done on univariate spatially regularized Gaussian mixtures. A specific Gibbs sampler is derived to account for different covariance structures in the feature space. On realistic artificial fMRI datasets, it is shown that our algorithm is helpful for identifying a parsimonious functional parcellation required in the context of joint detection estimation of brain activity. This allows us to overcome the classical assumption of spatial stationarity of the BOLD signal model. (authors)
Semi-Supervised Classification based on Gaussian Mixture Model for remote imagery
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
Semi-Supervised Classification (SSC),which makes use of both labeled and unlabeled data to determine classification borders in feature space,has great advantages in extracting classification information from mass data.In this paper,a novel SSC method based on Gaussian Mixture Model (GMM) is proposed,in which each class’s feature space is described by one GMM.Experiments show the proposed method can achieve high classification accuracy with small amount of labeled data.However,for the same accuracy,supervised classification methods such as Support Vector Machine,Object Oriented Classification,etc.should be provided with much more labeled data.
Novel pseudo-divergence of Gaussian mixture models based speaker clustering method
Institute of Scientific and Technical Information of China (English)
Wang Bo; Xu Yiqiong; Li Bicheng
2006-01-01
Serial structure is applied to speaker recognition to reduce the algorithm delay and computational complexity. The speech is first classified into speaker class, and then searches the most likely one inside the class.Difference between Gaussian Mixture Models (GMMs) is widely applied in speaker classification. The paper proposes a novel mean of pseudo-divergence, the ratio of Inter-Model dispersion to Intra-Model dispersion, to present the difference between GMMs, to perform speaker cluster. Weight, mean and variance, GMM's components, are involved in the dispersion. Experiments indicate that the measurement can well present the difference of GMMs and has improved performance of speaker clustering.
Gaussian mixture models and semantic gating improve reconstructions from human brain activity
Directory of Open Access Journals (Sweden)
Sanne eSchoenmakers
2015-01-01
Full Text Available Better acquisition protocols and analysis techniques are making it possible to use fMRI to obtain highly detailed visualizations of brain processes. In particular we focus on the reconstruction of natural images from BOLD responses in visual cortex. We expand our linear Gaussian framework for percept decoding with Gaussian mixture models to better represent the prior distribution of natural images. Reconstruction of such images then boils down to probabilistic inference in a hybrid Bayesian network. In our set-up, different mixture components correspond to different character categories. Our framework can automatically infer higher-order semantic categories from lower-level brain areas. Furthermore the framework can gate semantic information from higher-order brain areas to enforce the correct category during reconstruction. When categorical information is not available, we show that automatically learned clusters in the data give a similar improvement in reconstruction. The hybrid Bayesian network leads to highly accurate reconstructions in both supervised and unsupervised settings.
A Novel Robust Scene Change Detection Algorithm for Autonomous Robots Using Mixtures of Gaussians
Directory of Open Access Journals (Sweden)
Luis J. Manso
2014-02-01
Full Text Available Interest in change detection techniques has considerably increased during recent years in the field of autonomous robotics. This is partly because changes in a robot's working environment are useful for several robotic skills (e.g., spatial cognition, modelling or navigation and applications (e.g., surveillance or guidance robots. Changes are usually detected by comparing current data provided by the robot's sensors with a previously known map or model of the environment. When the data consists of a large point cloud, dealing with it is a computationally expensive task, mainly due to the amount of points and the redundancy. Using Gaussian Mixture Models (GMM instead of raw point clouds leads to a more compact feature space that can be used to efficiently process the input data. This allows us to successfully segment the set of 3D points acquired by the sensor and reduce the computational load of the change detection algorithm. However, the segmentation of the environment as a Mixture of Gaussians has some problems that need to be properly addressed. In this paper, a novel change detection algorithm is described in order to improve the robustness and computational cost of previous approaches. The proposal is based on the classic Expectation Maximization (EM algorithm, for which different selection criteria are evaluated. As demonstrated in the experimental results section, the proposed change detection algorithm achieves the detection of changes in the robot's working environment faster and more accurately than similar approaches.
Assessing clustering strategies for Gaussian mixture filtering a subsurface contaminant model
Liu, Bo
2016-02-03
An ensemble-based Gaussian mixture (GM) filtering framework is studied in this paper in term of its dependence on the choice of the clustering method to construct the GM. In this approach, a number of particles sampled from the posterior distribution are first integrated forward with the dynamical model for forecasting. A GM representation of the forecast distribution is then constructed from the forecast particles. Once an observation becomes available, the forecast GM is updated according to Bayes’ rule. This leads to (i) a Kalman filter-like update of the particles, and (ii) a Particle filter-like update of their weights, generalizing the ensemble Kalman filter update to non-Gaussian distributions. We focus on investigating the impact of the clustering strategy on the behavior of the filter. Three different clustering methods for constructing the prior GM are considered: (i) a standard kernel density estimation, (ii) clustering with a specified mixture component size, and (iii) adaptive clustering (with a variable GM size). Numerical experiments are performed using a two-dimensional reactive contaminant transport model in which the contaminant concentration and the heterogenous hydraulic conductivity fields are estimated within a confined aquifer using solute concentration data. The experimental results suggest that the performance of the GM filter is sensitive to the choice of the GM model. In particular, increasing the size of the GM does not necessarily result in improved performances. In this respect, the best results are obtained with the proposed adaptive clustering scheme.
Chen, Yunjie; Zhan, Tianming; Zhang, Ji; Wang, Hongyuan
2016-01-01
We propose a novel segmentation method based on regional and nonlocal information to overcome the impact of image intensity inhomogeneities and noise in human brain magnetic resonance images. With the consideration of the spatial distribution of different tissues in brain images, our method does not need preestimation or precorrection procedures for intensity inhomogeneities and noise. A nonlocal information based Gaussian mixture model (NGMM) is proposed to reduce the effect of noise. To reduce the effect of intensity inhomogeneity, the multigrid nonlocal Gaussian mixture model (MNGMM) is proposed to segment brain MR images in each nonoverlapping multigrid generated by using a new multigrid generation method. Therefore the proposed model can simultaneously overcome the impact of noise and intensity inhomogeneity and automatically classify 2D and 3D MR data into tissues of white matter, gray matter, and cerebral spinal fluid. To maintain the statistical reliability and spatial continuity of the segmentation, a fusion strategy is adopted to integrate the clustering results from different grid. The experiments on synthetic and clinical brain MR images demonstrate the superior performance of the proposed model comparing with several state-of-the-art algorithms.
A Novel Robust Scene Change Detection Algorithm for Autonomous Robots Using Mixtures of Gaussians
Directory of Open Access Journals (Sweden)
Luis J. Manso
2014-02-01
Full Text Available Interest in change detection techniques has considerably increased during recent years in the field of autonomous robotics. This is partly because changes in a robot’s working environment are useful for several robotic skills (e.g., spatial cognition, modelling or navigation and applications (e.g., surveillance or guidance robots. Changes are usually detected by comparing current data provided by the robot’s sensors with a previously known map or model of the environment. When the data consists of a large point cloud, dealing with it is a computationally expensive task, mainly due to the amount of points and the redundancy. Using Gaussian Mixture Models (GMM instead of raw point clouds leads to a more compact feature space that can be used to efficiently process the input data. This allows us to successfully segment the set of 3D points acquired by the sensor and reduce the computational load of the change detection algorithm. However, the segmentation of the environment as a Mixture of Gaussians has some problems that need to be properly addressed. In this paper, a novel change detection algorithm is described in order to improve the robustness and computational cost of previous approaches. The proposal is based on the classic Expectation Maximization (EM algorithm, for which different selection criteria are evaluated. As demonstrated in the experimental results section, the proposed change detection algorithm achieves the detection of changes in the robot’s working environment faster and more accurately than similar approaches.
ADAPTIVE BACKGROUND DENGAN METODE GAUSSIAN MIXTURE MODELS UNTUK REAL-TIME TRACKING
Directory of Open Access Journals (Sweden)
Silvia Rostianingsih
2008-01-01
Full Text Available Nowadays, motion tracking application is widely used for many purposes, such as detecting traffic jam and counting how many people enter a supermarket or a mall. A method to separate background and the tracked object is required for motion tracking. It will not be hard to develop the application if the tracking is performed on a static background, but it will be difficult if the tracked object is at a place with a non-static background, because the changing part of the background can be recognized as a tracking area. In order to handle the problem an application can be made to separate background where that separation can adapt to change that occur. This application is made to produce adaptive background using Gaussian Mixture Models (GMM as its method. GMM method clustered the input pixel data with pixel color value as it’s basic. After the cluster formed, dominant distributions are choosen as background distributions. This application is made by using Microsoft Visual C 6.0. The result of this research shows that GMM algorithm could made adaptive background satisfactory. This proofed by the result of the tests that succeed at all condition given. This application can be developed so the tracking process integrated in adaptive background maker process. Abstract in Bahasa Indonesia : Saat ini, aplikasi motion tracking digunakan secara luas untuk banyak tujuan, seperti mendeteksi kemacetan dan menghitung berapa banyak orang yang masuk ke sebuah supermarket atau sebuah mall. Sebuah metode untuk memisahkan antara background dan obyek yang di-track dibutuhkan untuk melakukan motion tracking. Membuat aplikasi tracking pada background yang statis bukanlah hal yang sulit, namun apabila tracking dilakukan pada background yang tidak statis akan lebih sulit, dikarenakan perubahan background dapat dikenali sebagai area tracking. Untuk mengatasi masalah tersebut, dapat dibuat suatu aplikasi untuk memisahkan background dimana aplikasi tersebut dapat
Energy Technology Data Exchange (ETDEWEB)
Razhev, A M; Kargapol' tsev, E S [Institute of Laser Physics, Siberian Branch, Russian Academy of Sciences, Novosibirsk (Russian Federation); Churkin, D S [Novosibirsk State University, Novosibirsk (Russian Federation)
2016-03-31
Results of an experimental study of the influence of a gas mixture (laser active medium) composition on an output energy and total efficiency of gas-discharge excimer lasers on ArF* (193 nm), KrCl* (222 nm), KrF* (248 nm) and XeCl* (308 nm) molecules operating without a buffer gas are presented. The optimal ratios of gas components (from the viewpoint of a maximum output energy) of an active medium are found, which provide an efficient operation of laser sources. It is experimentally confirmed that for gas-discharge excimer lasers on halogenides of inert gases the presence of a buffer gas in an active medium is not a necessary condition for efficient operation. For the first time, in two-component gas mixtures of repetitively pulsed gas-discharge excimer lasers on electron transitions of excimer molecules ArF*, KrCl*, KrF* and XeCl*, the pulsed energy of laser radiation obtained under pumping by a transverse volume electric discharge in a low-pressure gas mixture without a buffer gas reached up to 170 mJ and a high pulsed output power (of up to 24 MW) was obtained at a FWHM duration of the KrF-laser pulse of 7 ns. The maximal total efficiency obtained in the experiment with two-component gas mixtures of KrF and XeCl lasers was 0.8%. (lasers)
Razhev, A. M.; Kargapol'tsev, E. S.; Churkin, D. S.
2016-03-01
Results of an experimental study of the influence of a gas mixture (laser active medium) composition on an output energy and total efficiency of gas-discharge excimer lasers on ArF* (193 nm), KrCl* (222 nm), KrF* (248 nm) and XeCl* (308 nm) molecules operating without a buffer gas are presented. The optimal ratios of gas components (from the viewpoint of a maximum output energy) of an active medium are found, which provide an efficient operation of laser sources. It is experimentally confirmed that for gas-discharge excimer lasers on halogenides of inert gases the presence of a buffer gas in an active medium is not a necessary condition for efficient operation. For the first time, in two-component gas mixtures of repetitively pulsed gas-discharge excimer lasers on electron transitions of excimer molecules ArF*, KrCl*, KrF* and XeCl*, the pulsed energy of laser radiation obtained under pumping by a transverse volume electric discharge in a low-pressure gas mixture without a buffer gas reached up to 170 mJ and a high pulsed output power (of up to 24 MW) was obtained at a FWHM duration of the KrF-laser pulse of 7 ns. The maximal total efficiency obtained in the experiment with two-component gas mixtures of KrF and XeCl lasers was 0.8%.
Directory of Open Access Journals (Sweden)
Qunyi Xie
2016-01-01
Full Text Available Content-based image retrieval has recently become an important research topic and has been widely used for managing images from repertories. In this article, we address an efficient technique, called MNGS, which integrates multiview constrained nonnegative matrix factorization (NMF and Gaussian mixture model- (GMM- based spectral clustering for image retrieval. In the proposed methodology, the multiview NMF scheme provides competitive sparse representations of underlying images through decomposition of a similarity-preserving matrix that is formed by fusing multiple features from different visual aspects. In particular, the proposed method merges manifold constraints into the standard NMF objective function to impose an orthogonality constraint on the basis matrix and satisfy the structure preservation requirement of the coefficient matrix. To manipulate the clustering method on sparse representations, this paper has developed a GMM-based spectral clustering method in which the Gaussian components are regrouped in spectral space, which significantly improves the retrieval effectiveness. In this way, image retrieval of the whole database translates to a nearest-neighbour search in the cluster containing the query image. Simultaneously, this study investigates the proof of convergence of the objective function and the analysis of the computational complexity. Experimental results on three standard image datasets reveal the advantages that can be achieved with the proposed retrieval scheme.
Xiao, Yiming; Shah, Mohak; Francis, Simon; Arnold, Douglas L.; Arbel, Tal; Collins, D. Louis
Brain tissue segmentation is important in studying markers in human brain Magnetic Resonance Images (MRI) of patients with diseases such as Multiple Sclerosis (MS). Parametric segmentation approaches typically assume unimodal Gaussian distributions on MRI intensities of individual tissue classes, even in applications on multi-spectral images. However, this assumption has not been rigorously verified especially in the context of MS. In this work, we evaluate the local MRI intensities of both healthy and diseased brain tissues of 21 multi-spectral MRIs (63 volumes in total) of MS patients for adherence to this assumption. We show that the tissue intensities are not uniform across the brain and vary across (anatomical) regions of the brain. Consequently, we show that Gaussian mixtures can better model the multi-spectral intensities. We utilize an Expectation Maximization (EM) based approach to learn the models along with a symmetric Jeffreys divergence criterion to study differences in intensity distributions. The effects of these findings are also empirically verified on automatic segmentation of brains with MS.
Gaussian mixtures on tensor fields for segmentation: applications to medical imaging.
de Luis-García, Rodrigo; Westin, Carl-Fredrik; Alberola-López, Carlos
2011-01-01
In this paper, we introduce a new approach for tensor field segmentation based on the definition of mixtures of Gaussians on tensors as a statistical model. Working over the well-known Geodesic Active Regions segmentation framework, this scheme presents several interesting advantages. First, it yields a more flexible model than the use of a single Gaussian distribution, which enables the method to better adapt to the complexity of the data. Second, it can work directly on tensor-valued images or, through a parallel scheme that processes independently the intensity and the local structure tensor, on scalar textured images. Two different applications have been considered to show the suitability of the proposed method for medical imaging segmentation. First, we address DT-MRI segmentation on a dataset of 32 volumes, showing a successful segmentation of the corpus callosum and favourable comparisons with related approaches in the literature. Second, the segmentation of bones from hand radiographs is studied, and a complete automatic-semiautomatic approach has been developed that makes use of anatomical prior knowledge to produce accurate segmentation results.
Approximating Gaussian mixture model or radial basis function network with multilayer perceptron.
Patrikar, Ajay M
2013-07-01
Gaussian mixture models (GMMs) and multilayer perceptron (MLP) are both popular pattern classification techniques. This brief shows that a multilayer perceptron with quadratic inputs (MLPQ) can accurately approximate GMMs with diagonal covariance matrices. The mapping equations between the parameters of GMM and the weights of MLPQ are presented. A similar approach is applied to radial basis function networks (RBFNs) to show that RBFNs with Gaussian basis functions and Euclidean norm can be approximated accurately with MLPQ. The mapping equations between RBFN and MLPQ weights are presented. There are well-established training procedures for GMMs, such as the expectation maximization (EM) algorithm. The GMM parameters obtained by the EM algorithm can be used to generate a set of initial weights of MLPQ. Similarly, a trained RBFN can be used to generate a set of initial weights of MLPQ. MLPQ training can be continued further with gradient-descent based methods, which can lead to improvement in performance compared to the GMM or RBFN from which it is initialized. Thus, the MLPQ can always perform as well as or better than the GMM or RBFN.
Mixture subclass discriminant analysis link to restricted Gaussian model and other generalizations.
Gkalelis, Nikolaos; Mezaris, Vasileios; Kompatsiaris, Ioannis; Stathaki, Tania
2013-01-01
In this paper, a theoretical link between mixture subclass discriminant analysis (MSDA) and a restricted Gaussian model is first presented. Then, two further discriminant analysis (DA) methods, i.e., fractional step MSDA (FSMSDA) and kernel MSDA (KMSDA) are proposed. Linking MSDA to an appropriate Gaussian model allows the derivation of a new DA method under the expectation maximization (EM) framework (EM-MSDA), which simultaneously derives the discriminant subspace and the maximum likelihood estimates. The two other proposed methods generalize MSDA in order to solve problems inherited from conventional DA. FSMSDA solves the subclass separation problem, that is, the situation in which the dimensionality of the discriminant subspace is strictly smaller than the rank of the inter-between-subclass scatter matrix. This is done by an appropriate weighting scheme and the utilization of an iterative algorithm for preserving useful discriminant directions. On the other hand, KMSDA uses the kernel trick to separate data with nonlinearly separable subclass structure. Extensive experimentation shows that the proposed methods outperform conventional MSDA and other linear discriminant analysis variants.
Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture
Li, Lingling; Wang, Pengchong; Chao, Kuei-Hsiang; Zhou, Yatong; Xie, Yang
2016-01-01
The remaining useful life (RUL) prediction of Lithium-ion batteries is closely related to the capacity degeneration trajectories. Due to the self-charging and the capacity regeneration, the trajectories have the property of multimodality. Traditional prediction models such as the support vector machines (SVM) or the Gaussian Process regression (GPR) cannot accurately characterize this multimodality. This paper proposes a novel RUL prediction method based on the Gaussian Process Mixture (GPM). It can process multimodality by fitting different segments of trajectories with different GPR models separately, such that the tiny differences among these segments can be revealed. The method is demonstrated to be effective for prediction by the excellent predictive result of the experiments on the two commercial and chargeable Type 1850 Lithium-ion batteries, provided by NASA. The performance comparison among the models illustrates that the GPM is more accurate than the SVM and the GPR. In addition, GPM can yield the predictive confidence interval, which makes the prediction more reliable than that of traditional models. PMID:27632176
GAUSSIAN MIXTURE MODEL BASED LEVEL SET TECHNIQUE FOR AUTOMATED SEGMENTATION OF CARDIAC MR IMAGES
Directory of Open Access Journals (Sweden)
G. Dharanibai,
2011-04-01
Full Text Available In this paper we propose a Gaussian Mixture Model (GMM integrated level set method for automated segmentation of left ventricle (LV, right ventricle (RV and myocardium from short axis views of cardiacmagnetic resonance image. By fitting GMM to the image histogram, global pixel intensity characteristics of the blood pool, myocardium and background are estimated. GMM provides initial segmentation andthe segmentation solution is regularized using level set. Parameters for controlling the level set evolution are automatically estimated from the Bayesian inference classification of pixels. We propose a new speed function that combines edge and region information that stops the evolving level set at the myocardial boundary. Segmentation efficacy is analyzed qualitatively via visual inspection. Results show the improved performance of our of proposed speed function over the conventional Bayesian driven adaptive speed function in automatic segmentation of myocardium
Mixed Platoon Flow Dispersion Model Based on Speed-Truncated Gaussian Mixture Distribution
Directory of Open Access Journals (Sweden)
Weitiao Wu
2013-01-01
Full Text Available A mixed traffic flow feature is presented on urban arterials in China due to a large amount of buses. Based on field data, a macroscopic mixed platoon flow dispersion model (MPFDM was proposed to simulate the platoon dispersion process along the road section between two adjacent intersections from the flow view. More close to field observation, truncated Gaussian mixture distribution was adopted as the speed density distribution for mixed platoon. Expectation maximum (EM algorithm was used for parameters estimation. The relationship between the arriving flow distribution at downstream intersection and the departing flow distribution at upstream intersection was investigated using the proposed model. Comparison analysis using virtual flow data was performed between the Robertson model and the MPFDM. The results confirmed the validity of the proposed model.
Color-texture segmentation using JSEG based on Gaussian mixture modeling
Institute of Scientific and Technical Information of China (English)
Wang Yuzhong; Yang Jie; Zhou Yue
2006-01-01
An improved approach for J-value segmentation (JSEG) is presented for unsupervised color image segmentation. Instead of color quantization algorithm, an automatic classification method based on adaptive mean shift (AMS)based clustering is used for nonparametric clustering of image data set. The clustering results are used to construct Gaussian mixture modelling (GMM) of image data for the calculation of soft J value. The region growing algorithm used in JSEG is then applied in segmenting the image based on the multiscale soft J-images. Experiments show that the synergism of JSEG and the soft classification based on AMS based clustering and GMM overcomes the limitations of JSEG successfully and is more robust.
Liu, Sijia; Sa, Ruhan; Maguire, Orla; Minderman, Hans; Chaudhary, Vipin
2015-03-01
Cytogenetic abnormalities are important diagnostic and prognostic criteria for acute myeloid leukemia (AML). A flow cytometry-based imaging approach for FISH in suspension (FISH-IS) was established that enables the automated analysis of several log-magnitude higher number of cells compared to the microscopy-based approaches. The rotational positioning can occur leading to discordance between spot count. As a solution of counting error from overlapping spots, in this study, a Gaussian Mixture Model based classification method is proposed. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) of GMM are used as global image features of this classification method. Via Random Forest classifier, the result shows that the proposed method is able to detect closely overlapping spots which cannot be separated by existing image segmentation based spot detection methods. The experiment results show that by the proposed method we can obtain a significant improvement in spot counting accuracy.
Wang, Chuanyun; Song, Fei; Qin, Shiyin
2017-02-01
Addressing the problems of infrared small target tracking in forward looking infrared (FLIR) system, a new infrared small target tracking method is presented, in which features binding of both target gray intensity and spatial relationship is implemented by compressive sensing so as to construct the Gaussian mixture model of compressive appearance distribution. Subsequently, naive Bayesian classification is carried out over testing samples acquired with non-uniform sampling probability to identify the most credible location of targets from background scene. A series of experiments are carried out over four infrared small target image sequences with more than 200 images for each sequence, the results demonstrate the effectiveness and advantages of the proposed method in both success rate and precision rate.
Loukas, Constantinos; Georgiou, Evangelos
2013-01-01
There is currently great interest in analyzing the workflow of minimally invasive operations performed in a physical or simulation setting, with the aim of extracting important information that can be used for skills improvement, optimization of intraoperative processes, and comparison of different interventional strategies. The first step in achieving this goal is to segment the operation into its key interventional phases, which is currently approached by modeling a multivariate signal that describes the temporal usage of a predefined set of tools. Although this technique has shown promising results, it is challenged by the manual extraction of the tool usage sequence and the inability to simultaneously evaluate the surgeon's skills. In this paper we describe an alternative methodology for surgical phase segmentation and performance analysis based on Gaussian mixture multivariate autoregressive (GMMAR) models of the hand kinematics. Unlike previous work in this area, our technique employs signals from orientation sensors, attached to the endoscopic instruments of a virtual reality simulator, without considering which tools are employed at each time-step of the operation. First, based on pre-segmented hand motion signals, a training set of regression coefficients is created for each surgical phase using multivariate autoregressive (MAR) models. Then, a signal from a new operation is processed with GMMAR, wherein each phase is modeled by a Gaussian component of regression coefficients. These coefficients are compared to those of the training set. The operation is segmented according to the prior probabilities of the surgical phases estimated via GMMAR. The method also allows for the study of motor behavior and hand motion synchronization demonstrated in each phase, a quality that can be incorporated into modern laparoscopic simulators for skills assessment.
A Gaussian mixture model for definition of lung tumor volumes in positron emission tomography.
Aristophanous, Michalis; Penney, Bill C; Martel, Mary K; Pelizzari, Charles A
2007-11-01
The increased interest in 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in radiation treatment planning in the past five years necessitated the independent and accurate segmentation of gross tumor volume (GTV) from FDG-PET scans. In some studies the radiation oncologist contours the GTV based on a computed tomography scan, while incorporating pertinent data from the PET images. Alternatively, a simple threshold, typically 40% of the maximum intensity, has been employed to differentiate tumor from normal tissue, while other researchers have developed algorithms to aid the PET based GTV definition. None of these methods, however, results in reliable PET tumor segmentation that can be used for more sophisticated treatment plans. For this reason, we developed a Gaussian mixture model (GMM) based segmentation technique on selected PET tumor regions from non-small cell lung cancer patients. The purpose of this study was to investigate the feasibility of using a GMM-based tumor volume definition in a robust, reliable and reproducible way. A GMM relies on the idea that any distribution, in our case a distribution of image intensities, can be expressed as a mixture of Gaussian densities representing different classes. According to our implementation, each class belongs to one of three regions in the image; the background (B), the uncertain (U) and the target (T), and from these regions we can obtain the tumor volume. User interaction in the implementation is required, but is limited to the initialization of the model parameters and the selection of an "analysis region" to which the modeling is restricted. The segmentation was developed on three and tested on another four clinical cases to ensure robustness against differences observed in the clinic. It also compared favorably with thresholding at 40% of the maximum intensity and a threshold determination function based on tumor to background image intensities proposed in a recent paper. The parts of the
Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning.
Lin, Lanny; Goodrich, Michael A
2014-12-01
During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal.
A Gaussian mixture model based cost function for parameter estimation of chaotic biological systems
Shekofteh, Yasser; Jafari, Sajad; Sprott, Julien Clinton; Hashemi Golpayegani, S. Mohammad Reza; Almasganj, Farshad
2015-02-01
As we know, many biological systems such as neurons or the heart can exhibit chaotic behavior. Conventional methods for parameter estimation in models of these systems have some limitations caused by sensitivity to initial conditions. In this paper, a novel cost function is proposed to overcome those limitations by building a statistical model on the distribution of the real system attractor in state space. This cost function is defined by the use of a likelihood score in a Gaussian mixture model (GMM) which is fitted to the observed attractor generated by the real system. Using that learned GMM, a similarity score can be defined by the computed likelihood score of the model time series. We have applied the proposed method to the parameter estimation of two important biological systems, a neuron and a cardiac pacemaker, which show chaotic behavior. Some simulated experiments are given to verify the usefulness of the proposed approach in clean and noisy conditions. The results show the adequacy of the proposed cost function.
Gaussian Mixture Model and Deep Neural Network based Vehicle Detection and Classification
Directory of Open Access Journals (Sweden)
S Sri Harsha
2016-09-01
Full Text Available The exponential rise in the demand of vision based traffic surveillance systems have motivated academia-industries to develop optimal vehicle detection and classification scheme. In this paper, an adaptive learning rate based Gaussian mixture model (GMM algorithm has been developed for background subtraction of multilane traffic data. Here, vehicle rear information and road dash-markings have been used for vehicle detection. Performing background subtraction, connected component analysis has been applied to retrieve vehicle region. A multilayered AlexNet deep neural network (DNN has been applied to extract higher layer features. Furthermore, scale invariant feature transform (SIFT based vehicle feature extraction has been performed. The extracted 4096-dimensional features have been processed for dimensional reduction using principle component analysis (PCA and linear discriminant analysis (LDA. The features have been mapped for SVM-based classification. The classification results have exhibited that AlexNet-FC6 features with LDA give the accuracy of 97.80%, followed by AlexNet-FC6 with PCA (96.75%. AlexNet-FC7 feature with LDA and PCA algorithms has exhibited classification accuracy of 91.40% and 96.30%, respectively. On the contrary, SIFT features with LDA algorithm has exhibited 96.46% classification accuracy. The results revealed that enhanced GMM with AlexNet DNN at FC6 and FC7 can be significant for optimal vehicle detection and classification.
Gaussian mixture sigma-point particle filter for optical indoor navigation system
Zhang, Weizhi; Gu, Wenjun; Chen, Chunyi; Chowdhury, M. I. S.; Kavehrad, Mohsen
2013-12-01
With the fast growing and popularization of smart computing devices, there is a rise in demand for accurate and reliable indoor positioning. Recently, systems using visible light communications (VLC) technology have been considered as candidates for indoor positioning applications. A number of researchers have reported that VLC-based positioning systems could achieve position estimation accuracy in the order of centimeter. This paper proposes an Indoors navigation environment, based on visible light communications (VLC) technology. Light-emitting-diodes (LEDs), which are essentially semiconductor devices, can be easily modulated and used as transmitters within the proposed system. Positioning is realized by collecting received-signal-strength (RSS) information on the receiver side, following which least square estimation is performed to obtain the receiver position. To enable tracking of user's trajectory and reduce the effect of wild values in raw measurements, different filters are employed. In this paper, by computer simulations we have shown that Gaussian mixture Sigma-point particle filter (GM-SPPF) outperforms other filters such as basic Kalman filter and sequential importance-resampling particle filter (SIR-PF), at a reasonable computational cost.
Remote sensing image fusion based on Gaussian mixture model and multiresolution analysis
Xiao, Moyan; He, Zhibiao
2013-10-01
A novel image fusion algorithm based on region segmentation and multiresolution analysis(MRA) is proposed to make full use of advantages of different multiscale transform. Nonsubsampled contourlet transform(NSCT) processes edges better than wavelet transform does. While wavelet transform handles smooth area and singularities better than NSCT does. As an image often includes more than one feature, the proposed method is conducted on the basis of Gaussian mixture model(GMM) based region segmentation. Firstly, transform the multispectral(MS) image into intensity, hue and saturation component. Secondly, segment intensity component into dense contour and smooth regions according to GMM and NSCT. And then gain new intensity component by fusing intensity component and high resolution image with Àtrous wavelet transform(ATWT) fusion in smooth areas and NSCT fusion in dense contour areas. Finally transform the new intensity together with hue component, saturation component back into RGB space and obtain the fused image. Multisource remote sensing images are tested to assess this proposed algorithm. Visual evaluation and statistics analysis are employed to evaluate the quality of fused images of different methods. The proposed improved algorithm demonstrates excellent spectrum information and high resolution. Experiment results show that the new proposed fusion algorithm incorporating with region segmentation based improved GMM and MRA outperforms those algorithms based on single multiscale transform.
Multi-Atlas Segmentation for Abdominal Organs with Gaussian Mixture Models.
Burke, Ryan P; Xu, Zhoubing; Lee, Christopher P; Baucom, Rebeccah B; Poulose, Benjamin K; Abramson, Richard G; Landman, Bennett A
2015-03-17
Abdominal organ segmentation with clinically acquired computed tomography (CT) is drawing increasing interest in the medical imaging community. Gaussian mixture models (GMM) have been extensively used through medical segmentation, most notably in the brain for cerebrospinal fluid/gray matter/white matter differentiation. Because abdominal CT exhibit strong localized intensity characteristics, GMM have recently been incorporated in multi-stage abdominal segmentation algorithms. In the context of variable abdominal anatomy and rich algorithms, it is difficult to assess the marginal contribution of GMM. Herein, we characterize the efficacy of an a posteriori framework that integrates GMM of organ-wise intensity likelihood with spatial priors from multiple target-specific registered labels. In our study, we first manually labeled 100 CT images. Then, we assigned 40 images to use as training data for constructing target-specific spatial priors and intensity likelihoods. The remaining 60 images were evaluated as test targets for segmenting 12 abdominal organs. The overlap between the true and the automatic segmentations was measured by Dice similarity coefficient (DSC). A median improvement of 145% was achieved by integrating the GMM intensity likelihood against the specific spatial prior. The proposed framework opens the opportunities for abdominal organ segmentation by efficiently using both the spatial and appearance information from the atlases, and creates a benchmark for large-scale automatic abdominal segmentation.
Shahrabi, Mohammad Ali; Hashemi, Hosein; Hafizi, Mohammad Kazem
2016-02-01
Seismic and magnetotelluric (MT) methods are the most applicable geophysical methods in exploration of hydrocarbon resources. In this paper, mixture of Gaussian clustering is used to combine seismic and MT images under the scheme of Expectation/Maximization (EM) algorithm. Pre-Stack Depth Migration (PSDM) velocity, Root Mean Square (RMS) velocity and vertical gradient of RMS velocity of seismic and resistivity model of MT along 19.3 km MUN-21 profile in Munir Block that has been located in Southwest of Iran in Dezful embayment over the Seh-Qanat anticline are applied. The anticline is the most important oil trap of this area. The Expectation/Maximization (EM) method that has been applied includes: (1) creation of data vectors from the seismic and MT images using image processing techniques, (2) normalizing and mapping using Principal Component Analysis (PCA) procedure (3) unsupervised learning of dataset matrix, (4) setting the matrix in Expectation/Maximization (EM) iteration algorithm (5) remapping to physical space. The final model consists fof six classes which could be given to eight formations that belong to Eocene to Neocomian geological age. Pre-Stack Depth Migration (PSDM) velocity model obtained from seismic study on Seh-Qanat anticline only detected 2 horizons of formations, Asmari and Sarvak Formations; however, the current methodology introduces subdivision anticline into six classes by matching it to the log information of Seh-Qanat Deep-1 (SQD-1) borehole where it was excavated over the anticline with total depth of 2876 m.
Directory of Open Access Journals (Sweden)
Uttam Mande
2012-06-01
Full Text Available Lot of research is projected to map the criminal with that of crime and it is observed that there is still a huge increase in the crime rate due to the gap between the optimal usage of technologies and investigation. This has given scope for the development of new methodologies in the area of crime investigation using the techniques based on data mining, image processing, forensic, and social mining. In this paper, presents a model using new methodology for mapping the criminal with the crime. This model clusters the criminal data basing on the type crime. When a crime occurs, based on the eye witness specified features, the criminal is mapped. Here we propose a novel methodology that uses Generalized Gaussian Mixture Model to map the features specified by the eyewitness with that of the features of the criminal who have committed the same type of the crime, if the criminal is not mapped, the suspect table is checked and the reports are generated
Short-term traffic safety forecasting using Gaussian mixture model and Kalman filter
Institute of Scientific and Technical Information of China (English)
Sheng JIN; Dian-hai WANG; Cheng XU; Dong-fang MA
2013-01-01
In this paper; a prediction model is developed that combines a Gaussian mixture model (GMM) and a Kalman filter for online forecasting of traffic safety on expressways.Raw time-to-collision (TTC) samples are divided into two categories:those representing vehicles in risky situations and those in safe situations.Then,the GMM is used to model the bimodal distribution of the TTC samples,and the maximum likelihood (ML) estimation parameters of the TTC distribution are obtained using the expectation-maximization (EM) algorithm.We propose a new traffic safety indicator,named the proportion of exposure to traffic conflicts (PETTC),for assessing the risk and predicting the safety of expressway traffic.A Kalman filter is applied to forecast the short-term safety indicator,PETTC,and solves the online safety prediction problem.A dataset collected from four different expressway locations is used for performance estimation.The test results demonstrate the precision and robustness of the prediction model under different traffic conditions and using different datasets.These results could help decision-makers to improve their online traffic safety forecasting and enable the optimal operation of expressway traffic management systems.
A Grasp-pose Generation Method Based on Gaussian Mixture Models
Directory of Open Access Journals (Sweden)
Wenjia Wu
2015-11-01
Full Text Available A Gaussian Mixture Model (GMM-based grasp-pose generation method is proposed in this paper. Through offline training, the GMM is set up and used to depict the distribution of the robot’s reachable orientations. By dividing the robot’s workspace into small 3D voxels and training the GMM for each voxel, a look-up table covering all the workspace is built with the x, y and z positions as the index and the GMM as the entry. Through the definition of Task Space Regions (TSR, an object’s feasible grasp poses are expressed as a continuous region. With the GMM, grasp poses can be preferentially sampled from regions with high reachability probabilities in the online grasp-planning stage. The GMM can also be used as a preliminary judgement of a grasp pose’s reachability. Experiments on both a simulated and a real robot show the superiority of our method over the existing method.
Precision Measurements of the Cluster Red Sequence using an Error Corrected Gaussian Mixture Model
Energy Technology Data Exchange (ETDEWEB)
Hao, Jiangang; /Fermilab /Michigan U.; Koester, Benjamin P.; /Chicago U.; Mckay, Timothy A.; /Michigan U.; Rykoff, Eli S.; /UC, Santa Barbara; Rozo, Eduardo; /Ohio State U.; Evrard, August; /Michigan U.; Annis, James; /Fermilab; Becker, Matthew; /Chicago U.; Busha, Michael; /KIPAC, Menlo Park /SLAC; Gerdes, David; /Michigan U.; Johnston, David E.; /Northwestern U. /Brookhaven
2009-07-01
The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors. In this paper, we describe a new error corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increases mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment. These precise measurements serve as an important observational check on simulations and mock galaxy catalogs. The observed trends in the slope and scatter of the red sequence ridgeline with redshift are clues to possible intrinsic evolution of the cluster red-sequence itself. Most importantly, the methods presented in this work lay the groundwork for further improvements in optically-based cluster cosmology.
Adaptive Gaussian mixture models for pre-screening in GPR data
Torrione, Peter; Morton, Kenneth, Jr.; Besaw, Lance E.
2011-06-01
Due to the large amount of data generated by vehicle-mounted ground penetrating radar (GPR) antennae arrays, advanced feature extraction and classification can only be performed on a small subset of data during real-time operation. As a result, most GPR based landmine detection systems implement "pre-screening" algorithms to processes all of the data generated by the antennae array and identify locations with anomalous signatures for more advanced processing. These pre-screening algorithms must be computationally efficient and obtain high probability of detection, but can permit a false alarm rate which might be higher than the total system requirements. Many approaches to prescreening have previously been proposed, including linear prediction coefficients, the LMS algorithm, and CFAR-based approaches. Similar pre-screening techniques have also been developed in the field of video processing to identify anomalous behavior or anomalous objects. One such algorithm, an online k-means approximation to an adaptive Gaussian mixture model (GMM), is particularly well-suited to application for pre-screening in GPR data due to its computational efficiency, non-linear nature, and relevance of the logic underlying the algorithm to GPR processing. In this work we explore the application of an adaptive GMM-based approach for anomaly detection from the video processing literature to pre-screening in GPR data. Results with the ARA Nemesis landmine detection system demonstrate significant pre-screening performance improvements compared to alternative approaches, and indicate that the proposed algorithm is a complimentary technique to existing methods.
Directory of Open Access Journals (Sweden)
Hossein Rabbani
2013-01-01
Full Text Available In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR.
Gu, Wenjun; Zhang, Weizhi; Wang, Jin; Amini Kashani, M. R.; Kavehrad, Mohsen
2015-01-01
Over the past decade, location based services (LBS) have found their wide applications in indoor environments, such as large shopping malls, hospitals, warehouses, airports, etc. Current technologies provide wide choices of available solutions, which include Radio-frequency identification (RFID), Ultra wideband (UWB), wireless local area network (WLAN) and Bluetooth. With the rapid development of light-emitting-diodes (LED) technology, visible light communications (VLC) also bring a practical approach to LBS. As visible light has a better immunity against multipath effect than radio waves, higher positioning accuracy is achieved. LEDs are utilized both for illumination and positioning purpose to realize relatively lower infrastructure cost. In this paper, an indoor positioning system using VLC is proposed, with LEDs as transmitters and photo diodes as receivers. The algorithm for estimation is based on received-signalstrength (RSS) information collected from photo diodes and trilateration technique. By appropriately making use of the characteristics of receiver movements and the property of trilateration, estimation on three-dimensional (3-D) coordinates is attained. Filtering technique is applied to enable tracking capability of the algorithm, and a higher accuracy is reached compare to raw estimates. Gaussian mixture Sigma-point particle filter (GM-SPPF) is proposed for this 3-D system, which introduces the notion of Gaussian Mixture Model (GMM). The number of particles in the filter is reduced by approximating the probability distribution with Gaussian components.
Flexible Mixture-Amount Models for Business and Industry Using Gaussian Processes
A. Ruseckaite (Aiste); D. Fok (Dennis); P.P. Goos (Peter)
2016-01-01
markdownabstractMany products and services can be described as mixtures of ingredients whose proportions sum to one. Specialized models have been developed for linking the mixture proportions to outcome variables, such as preference, quality and liking. In many scenarios, only the mixture
Flexible Mixture-Amount Models for Business and Industry Using Gaussian Processes
A. Ruseckaite (Aiste); D. Fok (Dennis); P.P. Goos (Peter)
2016-01-01
markdownabstractMany products and services can be described as mixtures of ingredients whose proportions sum to one. Specialized models have been developed for linking the mixture proportions to outcome variables, such as preference, quality and liking. In many scenarios, only the mixture proportion
Zhang, Ruoqiao; Pal, Debashish; Thibault, Jean-Baptiste; Sauer, Ken D; Bouman, Charles A
2016-01-01
Markov random fields (MRFs) have been widely used as prior models in various inverse problems such as tomographic reconstruction. While MRFs provide a simple and often effective way to model the spatial dependencies in images, they suffer from the fact that parameter estimation is difficult. In practice, this means that MRFs typically have very simple structure that cannot completely capture the subtle characteristics of complex images. In this paper, we present a novel Gaussian mixture Markov random field model (GM-MRF) that can be used as a very expressive prior model for inverse problems such as denoising and reconstruction. The GM-MRF forms a global image model by merging together individual Gaussian-mixture models (GMMs) for image patches. In addition, we present a novel analytical framework for computing MAP estimates using the GM-MRF prior model through the construction of surrogate functions that result in a sequence of quadratic optimizations. We also introduce a simple but effective method to adjust...
Energy Technology Data Exchange (ETDEWEB)
Holoien, Thomas W.-S.; /Ohio State U., Dept. Astron. /Ohio State U., CCAPP /KIPAC, Menlo Park /SLAC; Marshall, Philip J.; Wechsler, Risa H.; /KIPAC, Menlo Park /SLAC
2017-05-11
We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.
Yang, Y.; Liu, W.
2017-09-01
To solve the problems of existing method of change detection using fully polarimetric SAR which not takes full advantage of polarimetric information and the result of false alarm rate of which is high, a method is proposed based on test statistic and Gaussian mixture model in this paper. In the case of the flood disaster in Wuhan city in 2016, difference image is obtained by the likelihoodratio parameter which is built using coherency matrix C3 or covariance matrix T3 of fully polarimetric SAR based on test statistic, and it becomes a reality that the change information is automatic extracted by the parameter of Gaussian mixture model (GMM) of difference image based on the expectation maximization (EM) iterative algorithm. The experimental results show that the overall accuracy of change detection results can be improved and false alarm rate can be reduced using this method by comparison with traditional constant false alarm rate (CFAR) method. Thus the validity and feasibility of the method is demonstrated.
Holoien, Thomas W -S; Wechsler, Risa H
2016-01-01
We describe two new open source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program for using Gaussian mixtures to do density estimation of noisy data using extreme deconvolution (XD) algorithms that has functionality not available in other XD tools. It allows the user to select between the AstroML (Vanderplas et al. 2012; Ivezic et al. 2015) and Bovy et al. (2011) fitting methods and is compatible with scikit-learn machine learning algorithms (Pedregosa et al. 2011). Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model conditioned on known values of other parameters. EmpiriciSN is an example application of this functionality that can be used for fitting an XDGMM model to observed supernova/host datas...
Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.
2017-06-01
We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.
Hazarika, Deepika; Nath, Vijay Kumar; Bhuyan, Manbendra
2016-12-01
A new Lapped transform domain SAR image despeckling algorithm using a two-state Gaussian mixture probability density function that uses local parameters for the mixture model, is proposed. The use of lapped orthogonal transform (LOT) is motivated by its low computational complexity and robustness to oversmoothing. It is shown that the dyadic rearranged LOT coefficients of logarithmically transformed SAR images can be well approximated using two-state Gaussian mixture distribution compared to Laplacian, Gamma, generalized Gaussian and Cauchy distributions, based on the Kolmogorov-Smirnov (KS) goodness of fit test. The LOT coefficients of speckle noise are modeled using zero mean Gaussian distributions. A maximum a posteriori (MAP) estimator within Bayesian framework is developed using this proposed prior distribution and is used to restore the noisy LOT coefficients. The parameters of mixture distribution are estimated using the expectation-maximization algorithm. This paper presents a new technique to identify LOT modulus maxima which allows us to classify LOT coefficients into the edge and non edge coefficients. The classified edge coefficients are kept unmodified by the proposed algorithm whereas the noise-free estimates of non-edge coefficients are obtained using Bayesian MAP estimator developed using two state Gaussian mixture distribution with local parameters. Finally the proposed technique is combined with the cycle spinning scheme to further improve the despeckling performance. Experimental results show that the proposed method very efficiently reduces speckle in homogeneous regions while preserving more edge structures compared to some recent well known methods.
Directory of Open Access Journals (Sweden)
Milad eLankarany
2013-09-01
Full Text Available Time-varying excitatory and inhibitory synaptic inputs govern activity of neurons and process information in the brain. The importance of trial-to-trial fluctuations of synaptic inputs has recently been investigated in neuroscience. Such fluctuations are ignored in the most conventional techniques because they are removed when trials are averaged during linear regression techniques. Here, we propose a novel recursive algorithm based on Gaussian mixture Kalman filtering for estimating time-varying excitatory and inhibitory synaptic inputs from single trials of noisy membrane potential in current clamp recordings. The Kalman filtering is followed by an expectation maximization algorithm to infer the statistical parameters (time-varying mean and variance of the synaptic inputs in a non-parametric manner. As our proposed algorithm is repeated recursively, the inferred parameters of the mixtures are used to initiate the next iteration. Unlike other recent algorithms, our algorithm does not assume an a priori distribution from which the synaptic inputs are generated. Instead, the algorithm recursively estimates such a distribution by fitting a Gaussian mixture model. The performance of the proposed algorithms is compared to a previously proposed PF-based algorithm (Paninski et al., 2012 with several illustrative examples, assuming that the distribution of synaptic input is unknown. If noise is small, the performance of our algorithms is similar to that of the previous one. However, if noise is large, they can significantly outperform the previous proposal. These promising results suggest that our algorithm is a robust and efficient technique for estimating time varying excitatory and inhibitory synaptic conductances from single trials of membrane potential recordings.
Lankarany, M; Zhu, W-P; Swamy, M N S; Toyoizumi, Taro
2013-01-01
Time-varying excitatory and inhibitory synaptic inputs govern activity of neurons and process information in the brain. The importance of trial-to-trial fluctuations of synaptic inputs has recently been investigated in neuroscience. Such fluctuations are ignored in the most conventional techniques because they are removed when trials are averaged during linear regression techniques. Here, we propose a novel recursive algorithm based on Gaussian mixture Kalman filtering (GMKF) for estimating time-varying excitatory and inhibitory synaptic inputs from single trials of noisy membrane potential in current clamp recordings. The KF is followed by an expectation maximization (EM) algorithm to infer the statistical parameters (time-varying mean and variance) of the synaptic inputs in a non-parametric manner. As our proposed algorithm is repeated recursively, the inferred parameters of the mixtures are used to initiate the next iteration. Unlike other recent algorithms, our algorithm does not assume an a priori distribution from which the synaptic inputs are generated. Instead, the algorithm recursively estimates such a distribution by fitting a Gaussian mixture model (GMM). The performance of the proposed algorithms is compared to a previously proposed PF-based algorithm (Paninski et al., 2012) with several illustrative examples, assuming that the distribution of synaptic input is unknown. If noise is small, the performance of our algorithms is similar to that of the previous one. However, if noise is large, they can significantly outperform the previous proposal. These promising results suggest that our algorithm is a robust and efficient technique for estimating time varying excitatory and inhibitory synaptic conductances from single trials of membrane potential recordings.
Institute of Scientific and Technical Information of China (English)
Zhang Zhi; Li Jianxun; Liu Liu; Liu Zhaolei; Han Shan
2015-01-01
Since the features of low energy consumption and limited power supply are very impor-tant for wireless sensor networks (WSNs), the problems of distributed state estimation with quan-tized innovations are investigated in this paper. In the first place, the assumptions of prior and posterior probability density function (PDF) with quantized innovations in the previous papers are analyzed. After that, an innovative Gaussian mixture estimator is proposed. On this basis, this paper presents a Gaussian mixture state estimation algorithm based on quantized innovations for WSNs. In order to evaluate and compare the performance of this kind of state estimation algo-rithms for WSNs, the posterior Cramer–Rao lower bound (CRLB) with quantized innovations is put forward. Performance analysis and simulations show that the proposed Gaussian mixture state estimation algorithm is efficient than the others under the same number of quantization levels and the performance of these algorithms can be benchmarked by the theoretical lower bound.
Directory of Open Access Journals (Sweden)
Zhang Zhi
2015-12-01
Full Text Available Since the features of low energy consumption and limited power supply are very important for wireless sensor networks (WSNs, the problems of distributed state estimation with quantized innovations are investigated in this paper. In the first place, the assumptions of prior and posterior probability density function (PDF with quantized innovations in the previous papers are analyzed. After that, an innovative Gaussian mixture estimator is proposed. On this basis, this paper presents a Gaussian mixture state estimation algorithm based on quantized innovations for WSNs. In order to evaluate and compare the performance of this kind of state estimation algorithms for WSNs, the posterior Cramér–Rao lower bound (CRLB with quantized innovations is put forward. Performance analysis and simulations show that the proposed Gaussian mixture state estimation algorithm is efficient than the others under the same number of quantization levels and the performance of these algorithms can be benchmarked by the theoretical lower bound.
Garrido, M C; Ruiz, A; 10.1613/jair.533
2011-01-01
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of finite mixture models, conjugate families and factorization. Both the joint probability density of the variables and the likelihood function of the (objective or subjective) observation are approximated by a special mixture model, in such a way that any desired conditional distribution can be directly obtained without numerical integration. We have developed an extended version of the expectation maximization (EM) algorithm to estimate the parameters of mixture models from uncertain training examples (indirect observations). As a consequence, any piece of exact or uncertain information about both input and output values is consistently handled in the inference and learning stages. This ability, extremely useful in certain situations, is not found in most alternative methods. The proposed framework is formally justified from standard prob...
FPGA Implementation of Gaussian Mixture Model Algorithm for 47 fps Segmentation of 1080p Video
Directory of Open Access Journals (Sweden)
Mariangela Genovese
2013-01-01
Full Text Available Circuits and systems able to process high quality video in real time are fundamental in nowadays imaging systems. The circuit proposed in the paper, aimed at the robust identification of the background in video streams, implements the improved formulation of the Gaussian Mixture Model (GMM algorithm that is included in the OpenCV library. An innovative, hardware oriented, formulation of the GMM equations, the use of truncated binary multipliers, and ROM compression techniques allow reduced hardware complexity and increased processing capability. The proposed circuit has been designed having commercial FPGA devices as target and provides speed and logic resources occupation that overcome previously proposed implementations. The circuit, when implemented on Virtex6 or StratixIV, processes more than 45 frame per second in 1080p format and uses few percent of FPGA logic resources.
Schellenberg, Graham; Stortz, Greg; Goertzen, Andrew L.
2016-02-01
A typical positron emission tomography detector is comprised of a scintillator crystal array coupled to a photodetector array or other position sensitive detector. Such detectors using light sharing to read out crystal elements require the creation of a crystal lookup table (CLUT) that maps the detector response to the crystal of interaction based on the x-y position of the event calculated through Anger-type logic. It is vital for system performance that these CLUTs be accurate so that the location of events can be accurately identified and so that crystal-specific corrections, such as energy windowing or time alignment, can be applied. While using manual segmentation of the flood image to create the CLUT is a simple and reliable approach, it is both tedious and time consuming for systems with large numbers of crystal elements. In this work we describe the development of an automated algorithm for CLUT generation that uses a Gaussian mixture model paired with thin plate splines (TPS) to iteratively fit a crystal layout template that includes the crystal numbering pattern. Starting from a region of stability, Gaussians are individually fit to data corresponding to crystal locations while simultaneously updating a TPS for predicting future Gaussian locations at the edge of a region of interest that grows as individual Gaussians converge to crystal locations. The algorithm was tested with flood image data collected from 16 detector modules, each consisting of a 409 crystal dual-layer offset LYSO crystal array readout by a 32 pixel SiPM array. For these detector flood images, depending on user defined input parameters, the algorithm runtime ranged between 17.5-82.5 s per detector on a single core of an Intel i7 processor. The method maintained an accuracy above 99.8% across all tests, with the majority of errors being localized to error prone corner regions. This method can be easily extended for use with other detector types through adjustment of the initial
Chen, Jian; Yuan, Shenfang; Qiu, Lei; Wang, Hui; Yang, Weibo
2017-07-25
Accurate on-line prognosis of fatigue crack propagation is of great meaning for prognostics and health management (PHM) technologies to ensure structural integrity, which is a challenging task because of uncertainties which arise from sources such as intrinsic material properties, loading, and environmental factors. The particle filter algorithm has been proved to be a powerful tool to deal with prognostic problems those are affected by uncertainties. However, most studies adopted the basic particle filter algorithm, which uses the transition probability density function as the importance density and may suffer from serious particle degeneracy problem. This paper proposes an on-line fatigue crack propagation prognosis method based on a novel Gaussian weight-mixture proposal particle filter and the active guided wave based on-line crack monitoring. Based on the on-line crack measurement, the mixture of the measurement probability density function and the transition probability density function is proposed to be the importance density. In addition, an on-line dynamic update procedure is proposed to adjust the parameter of the state equation. The proposed method is verified on the fatigue test of attachment lugs which are a kind of important joint components in aircraft structures. Copyright © 2017 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Bernard Mazoyer
Full Text Available Hemispheric lateralization for language production and its relationships with manual preference and manual preference strength were studied in a sample of 297 subjects, including 153 left-handers (LH. A hemispheric functional lateralization index (HFLI for language was derived from fMRI acquired during a covert sentence generation task as compared with a covert word list recitation. The multimodal HFLI distribution was optimally modeled using a mixture of 3 and 4 Gaussian functions in right-handers (RH and LH, respectively. Gaussian function parameters helped to define 3 types of language hemispheric lateralization, namely "Typical" (left hemisphere dominance with clear positive HFLI values, 88% of RH, 78% of LH, "Ambilateral" (no dominant hemisphere with HFLI values close to 0, 12% of RH, 15% of LH and "Strongly-atypical" (right-hemisphere dominance with clear negative HFLI values, 7% of LH. Concordance between dominant hemispheres for hand and for language did not exceed chance level, and most of the association between handedness and language lateralization was explained by the fact that all Strongly-atypical individuals were left-handed. Similarly, most of the relationship between language lateralization and manual preference strength was explained by the fact that Strongly-atypical individuals exhibited a strong preference for their left hand. These results indicate that concordance of hemispheric dominance for hand and for language occurs barely above the chance level, except in a group of rare individuals (less than 1% in the general population who exhibit strong right hemisphere dominance for both language and their preferred hand. They call for a revisit of models hypothesizing common determinants for handedness and for language dominance.
Vargas Cardona, Hernán Darío; Orozco, Álvaro Ángel; Álvarez, Mauricio A
2013-01-01
Automatic identification of biosignals is one of the more studied fields in biomedical engineering. In this paper, we present an approach for the unsupervised recognition of biomedical signals: Microelectrode Recordings (MER) and Electrocardiography signals (ECG). The unsupervised learning is based in classic and bayesian estimation theory. We employ gaussian mixtures models with two estimation methods. The first is derived from the frequentist estimation theory, known as Expectation-Maximization (EM) algorithm. The second is obtained from bayesian probabilistic estimation and it is called variational inference. In this framework, both methods are used for parameters estimation of Gaussian mixtures. The mixtures models are used for unsupervised pattern classification, through the responsibility matrix. The algorithms are applied in two real databases acquired in Parkinson's disease surgeries and electrocardiograms. The results show an accuracy over 85% in MER and 90% in ECG for identification of two classes. These results are statistically equal or even better than parametric (Naive Bayes) and nonparametric classifiers (K-nearest neighbor).
Li, Zheng; Jiang, Yi-han; Duan, Lian; Zhu, Chao-zhe
2017-08-01
Objective. Functional near infra-red spectroscopy (fNIRS) is a promising brain imaging technology for brain-computer interfaces (BCI). Future clinical uses of fNIRS will likely require operation over long time spans, during which neural activation patterns may change. However, current decoders for fNIRS signals are not designed to handle changing activation patterns. The objective of this study is to test via simulations a new adaptive decoder for fNIRS signals, the Gaussian mixture model adaptive classifier (GMMAC). Approach. GMMAC can simultaneously classify and track activation pattern changes without the need for ground-truth labels. This adaptive classifier uses computationally efficient variational Bayesian inference to label new data points and update mixture model parameters, using the previous model parameters as priors. We test GMMAC in simulations in which neural activation patterns change over time and compare to static decoders and unsupervised adaptive linear discriminant analysis classifiers. Main results. Our simulation experiments show GMMAC can accurately decode under time-varying activation patterns: shifts of activation region, expansions of activation region, and combined contractions and shifts of activation region. Furthermore, the experiments show the proposed method can track the changing shape of the activation region. Compared to prior work, GMMAC performed significantly better than the other unsupervised adaptive classifiers on a difficult activation pattern change simulation: 99% versus <54% in two-choice classification accuracy. Significance. We believe GMMAC will be useful for clinical fNIRS-based brain-computer interfaces, including neurofeedback training systems, where operation over long time spans is required.
Qiu, Lei; Yuan, Shenfang; Bao, Qiao; Mei, Hanfei; Ren, Yuanqiang
2016-05-01
For aerospace application of structural health monitoring (SHM) technology, the problem of reliable damage monitoring under time-varying conditions must be addressed and the SHM technology has to be fully validated on real aircraft structures under realistic load conditions on ground before it can reach the status of flight test. In this paper, the guided wave (GW) based SHM method is applied to a full-scale aircraft fatigue test which is one of the most similar test status to the flight test. To deal with the time-varying problem, a GW-Gaussian mixture model (GW-GMM) is proposed. The probability characteristic of GW features, which is introduced by time-varying conditions is modeled by GW-GMM. The weak cumulative variation trend of the crack propagation, which is mixed in time-varying influence can be tracked by the GW-GMM migration during on-line damage monitoring process. A best match based Kullback-Leibler divergence is proposed to measure the GW-GMM migration degree to reveal the crack propagation. The method is validated in the full-scale aircraft fatigue test. The validation results indicate that the reliable crack propagation monitoring of the left landing gear spar and the right wing panel under realistic load conditions are achieved.
Ortiz-Rosario, Alexis; Adeli, Hojjat; Buford, John A
2017-01-15
Researchers often rely on simple methods to identify involvement of neurons in a particular motor task. The historical approach has been to inspect large groups of neurons and subjectively separate neurons into groups based on the expertise of the investigator. In cases where neuron populations are small it is reasonable to inspect these neuronal recordings and their firing rates carefully to avoid data omissions. In this paper, a new methodology is presented for automatic objective classification of neurons recorded in association with behavioral tasks into groups. By identifying characteristics of neurons in a particular group, the investigator can then identify functional classes of neurons based on their relationship to the task. The methodology is based on integration of a multiple signal classification (MUSIC) algorithm to extract relevant features from the firing rate and an expectation-maximization Gaussian mixture algorithm (EM-GMM) to cluster the extracted features. The methodology is capable of identifying and clustering similar firing rate profiles automatically based on specific signal features. An empirical wavelet transform (EWT) was used to validate the features found in the MUSIC pseudospectrum and the resulting signal features captured by the methodology. Additionally, this methodology was used to inspect behavioral elements of neurons to physiologically validate the model. This methodology was tested using a set of data collected from awake behaving non-human primates. Copyright © 2016 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Rui Li
Full Text Available We present a method to discover discriminative brain metabolism patterns in [18F] fluorodeoxyglucose positron emission tomography (PET scans, facilitating the clinical diagnosis of Alzheimer's disease. In the work, the term "pattern" stands for a certain brain region that characterizes a target group of patients and can be used for a classification as well as interpretation purposes. Thus, it can be understood as a so-called "region of interest (ROI". In the literature, an ROI is often found by a given brain atlas that defines a number of brain regions, which corresponds to an anatomical approach. The present work introduces a semi-data-driven approach that is based on learning the characteristics of the given data, given some prior anatomical knowledge. A Gaussian Mixture Model (GMM and model selection are combined to return a clustering of voxels that may serve for the definition of ROIs. Experiments on both an in-house dataset and data of the Alzheimer's Disease Neuroimaging Initiative (ADNI suggest that the proposed approach arrives at a better diagnosis than a merely anatomical approach or conventional statistical hypothesis testing.
Chattopadhyay, Souradeep; Maitra, Ranjan
2017-08-01
Clustering methods are an important tool to enumerate and describe the different coherent kind of gamma-ray bursts (GRBs). But their performance can be affected by a number of factors such as the choice of clustering algorithm and inherent associated assumptions, the inclusion of variables in clustering, nature of initialization methods used or the iterative algorithm or the criterion used to judge the optimal number of groups supported by the data. We analysed GRBs from the Burst and Transient Source Experiment (BATSE) 4Br Catalog using k-means and Gaussian-mixture-models-based clustering methods and found that after accounting for all the above factors, all six variables - different subsets of which have been used in the literature - that are, namely, the flux duration variables (T50, T90), the peak flux (P256) measured in 256 ms bins, the total fluence (Ft) and the spectral hardness ratios (H32 and H321) contain information on clustering. Further, our analysis found evidence of five different kinds of GRBs and that these groups have different kinds of dispersions in terms of shape, size and orientation. In terms of duration, fluence and spectrum, the five types of GRBs were characterized as intermediate/faint/intermediate, long/intermediate/soft, intermediate/intermediate/intermediate, short/faint/hard and long/bright/intermediate.
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Ronghui Zhang
2013-01-01
Full Text Available Vehicle-flow detection and tracking by digital image are one of the most important technologies in the traffic monitoring system. Gaussian mixture distribution method is used to eliminate the influence of moving vehicle firstly in this text, and then we built the background images for vehicle flow. Combining the advantages of background difference algorithm with inter frame difference operator, the real-time background is segmented integrally and dynamically updated accurately by matching the reconstructed image with current background. In order to ensure the robustness of vehicle detection, three by three window templates are adopted to remove the isolated noise spot in the image of vehicle contour. The template structural element is used to do some graphical morphological filtering. So, the corrosion and expansion sets are obtained. To narrow the target search scope and improve the calculation speed and precision of the algorithm, Kalman filtering model is used to realize the tracking of fast moving vehicles. Experimental results show that the method has good real-time and reliable performance.
Qiu, Lei; Yuan, Shenfang; Chang, Fu-Kuo; Bao, Qiao; Mei, Hanfei
2014-12-01
Structural health monitoring technology for aerospace structures has gradually turned from fundamental research to practical implementations. However, real aerospace structures work under time-varying conditions that introduce uncertainties to signal features that are extracted from sensor signals, giving rise to difficulty in reliably evaluating the damage. This paper proposes an online updating Gaussian Mixture Model (GMM)-based damage evaluation method to improve damage evaluation reliability under time-varying conditions. In this method, Lamb-wave-signal variation indexes and principle component analysis (PCA) are adopted to obtain the signal features. A baseline GMM is constructed on the signal features acquired under time-varying conditions when the structure is in a healthy state. By adopting the online updating mechanism based on a moving feature sample set and inner probability structural reconstruction, the probability structures of the GMM can be updated over time with new monitoring signal features to track the damage progress online continuously under time-varying conditions. This method can be implemented without any physical model of damage or structure. A real aircraft wing spar, which is an important load-bearing structure of an aircraft, is adopted to validate the proposed method. The validation results show that the method is effective for edge crack growth monitoring of the wing spar bolts holes under the time-varying changes in the tightness degree of the bolts.
Spain, Christopher J.; Anderson, Derek T.; Keller, James M.; Popescu, Mihail; Stone, Kevin E.
2011-06-01
Burying objects below the ground can potentially alter their thermal properties. Moreover, there is often soil disturbance associated with recently buried objects. An intensity video frame image generated by an infrared camera in the medium and long wavelengths often locally varies in the presence of buried explosive hazards. Our approach to automatically detecting these anomalies is to estimate a background model of the image sequence. Pixel values that do not conform to the background model may represent local changes in thermal or soil signature caused by buried objects. Herein, we present a Gaussian mixture model-based technique to estimate the statistical model of background pixel values. The background model is used to detect anomalous pixel values on the road while a vehicle is moving. Foreground pixel confidence values are projected into the UTM coordinate system and a UTM confidence map is built. Different operating levels are explored and the connected component algorithm is then used to extract islands that are subjected to size, shape and orientation filters. We are currently using this approach as a feature in a larger multi-algorithm fusion system. However, in this article we also present results for using this algorithm as a stand-alone detector algorithm in order to further explore its value in detecting buried explosive hazards.
Genovese, Mariangela; Napoli, Ettore
2013-05-01
The identification of moving objects is a fundamental step in computer vision processing chains. The development of low cost and lightweight smart cameras steadily increases the request of efficient and high performance circuits able to process high definition video in real time. The paper proposes two processor cores aimed to perform the real time background identification on High Definition (HD, 1920 1080 pixel) video streams. The implemented algorithm is the OpenCV version of the Gaussian Mixture Model (GMM), an high performance probabilistic algorithm for the segmentation of the background that is however computationally intensive and impossible to implement on general purpose CPU with the constraint of real time processing. In the proposed paper, the equations of the OpenCV GMM algorithm are optimized in such a way that a lightweight and low power implementation of the algorithm is obtained. The reported performances are also the result of the use of state of the art truncated binary multipliers and ROM compression techniques for the implementation of the non-linear functions. The first circuit has commercial FPGA devices as a target and provides speed and logic resource occupation that overcome previously proposed implementations. The second circuit is oriented to an ASIC (UMC-90nm) standard cell implementation. Both implementations are able to process more than 60 frames per second in 1080p format, a frame rate compatible with HD television.
Kusmakar, Shitanshu; Muthuganapathy, Ramanathan; Yan, Bernard; O'Brien, Terence J; Palaniswami, Marimuthu
2016-08-01
Any abnormal hypersynchronus activity of neurons can be characterized as an epileptic seizure (ES). A broad class of non-epileptic seizures is comprised of Psychogenic non-epileptic seizures (PNES). PNES are paroxysmal events, which mimics epileptic seizures and pose a diagnostic challenge with epileptic seizures due to their clinical similarities. The diagnosis of PNES is done using video-electroencephalography (VEM) monitoring. VEM being a resource intensive process calls for alternative methods for detection of PNES. There is now an emerging interest in the use of accelerometer based devices for the detection of seizures. In this work, we present an algorithm based on Gaussian mixture model (GMM's) for the identification of PNES, ES and normal movements using a wrist-worn accelerometer device. Features in time, frequency and wavelet domain are extracted from the norm of accelerometry signal. All events are then classified into three classes i.e normal, PNES and ES using a parametric estimate of the multivariate normal probability density function. An algorithm based on GMM's allows us to accurately model the non-epileptic and epileptic movements, thus enhancing the overall predictive accuracy of the system. The new algorithm was tested on data collected from 16 patients and showed an overall detection accuracy of 91% with 25 false alarms.
Boberg, Owen M.; Friel, Eileen D.; Vesperini, Enrico
2016-06-01
We present the results of an analysis using Gaussian mixture models (GMM) to separate multiple populations in Milky Way globular clusters based on the Na and O abundances of their members. Recent studies have shown that the method used to separate the populations in globular clusters (e.g. photometry, molecular band strengths, light element abundances) can result in different fractions of primordial and second generation stars. These fractions have important implications on the mass lost by globular clusters during their evolution, and the mechanism responsible for creating the second generation. For many previous studies, the first generation (FG) stars, with primordial Na and O, were classified as such by falling below a maximum [Na/Fe] abundance based on the estimated [Na/Fe] of the Milky Way field population most similar to a given cluster. Stars that were above this [Na/Fe] threshold were classified as second generation (SG) stars, representing the Na enhanced and O depleted population in the cluster. The method we present here is based on separating these populations in the [Na/Fe] vs [O/Fe] plane by constructing a multi-component, and multi-dimensional, GMM. The dataset provided by Carretta et al. 2009 provides a homogeneous sample of [Na/Fe] and [O/Fe] abundances in ~1,000 stars in southern globular clusters. Using all of the stars available in this sample, we created a general GMM that was subsequently used to classify the stars in individual clusters as FG or SG. To perform this classification, the stars in each cluster are assigned a probability of belonging to each of the Gaussian components in the GMM calculated from the entire Carretta sample. Based on these probabilities, we can assign a given star to the FG or SG. Here we present how the fractions of FG and SG stars present in a given globular cluster, as calculated by our GMM, compare to those determined from a single [Na/Fe] threshold. We will also characterize how the fractions of FG and SG stars
Goossens, Bart; Aelterman, Jan; Luong, Hiep; Pizurica, Aleksandra; Philips, Wilfried
2013-02-01
In digital cameras and mobile phones, there is an ongoing trend to increase the image resolution, decrease the sensor size and to use lower exposure times. Because smaller sensors inherently lead to more noise and a worse spatial resolution, digital post-processing techniques are required to resolve many of the artifacts. Color filter arrays (CFAs), which use alternating patterns of color filters, are very popular because of price and power consumption reasons. However, color filter arrays require the use of a post-processing technique such as demosaicing to recover full resolution RGB images. Recently, there has been some interest in techniques that jointly perform the demosaicing and denoising. This has the advantage that the demosaicing and denoising can be performed optimally (e.g. in the MSE sense) for the considered noise model, while avoiding artifacts introduced when using demosaicing and denoising sequentially. In this paper, we will continue the research line of the wavelet-based demosaicing techniques. These approaches are computationally simple and very suited for combination with denoising. Therefore, we will derive Bayesian Minimum Squared Error (MMSE) joint demosaicing and denoising rules in the complex wavelet packet domain, taking local adaptivity into account. As an image model, we will use Gaussian Scale Mixtures, thereby taking advantage of the directionality of the complex wavelets. Our results show that this technique is well capable of reconstructing fine details in the image, while removing all of the noise, at a relatively low computational cost. In particular, the complete reconstruction (including color correction, white balancing etc) of a 12 megapixel RAW image takes 3.5 sec on a recent mid-range GPU.
Directory of Open Access Journals (Sweden)
Shanmugapriya. K
2014-01-01
Full Text Available The human action recognition system first gathers images by simply querying the name of the action on a web image search engine like Google or Yahoo. Based on the assumption that the set of retrieved images contains relevant images of the queried action, we construct a dataset of action images in an incremental manner. This yields a large image set, which includes images of actions taken from multiple viewpoints in a range of environments, performed by people who have varying body proportions and different clothing. The images mostly present the “key poses” since these images try to convey the action with a single pose. In existing system to support this they first used an incremental image retrieval procedure to collect and clean up the necessary training set for building the human pose classifiers. There are challenges that come at the expense of this broad and representative data. First, the retrieved images are very noisy, since the Web is very diverse. Second, detecting and estimating the pose of humans in still images is more difficult than in videos, partly due to the background clutter and the lack of a foreground mask. In videos, foreground segmentation can exploit motion cues to great benefit. In still images, the only cue at hand is the appearance information and therefore, our model must address various challenges associated with different forms of appearance. Therefore for robust separation, in proposed work a segmentation algorithm based on Gaussian Mixture Models is proposed which is adaptive to light illuminations, shadow and white balance is proposed here. This segmentation algorithm processes the video with or without noise and sets up adaptive background models based on the characteristics also this method is a very effective technique for background modeling which classifies the pixels of a video frame either background or foreground based on probability distribution.
Dai, Peishan; Luo, Hanyuan; Sheng, Hanwei; Zhao, Yali; Li, Ling; Wu, Jing; Zhao, Yuqian; Suzuki, Kenji
2015-01-01
Vessel segmentation in retinal fundus images is a preliminary step to clinical diagnosis for some systemic diseases and some eye diseases. The performances of existing methods for segmenting small vessels which are usually of more importance than the main vessels in a clinical diagnosis are not satisfactory in clinical use. In this paper, we present a method for both main and peripheral vessel segmentation. A local gray-level change enhancement algorithm called gray-voting is used to enhance the small vessels, while a two-dimensional Gabor wavelet is used to extract the main vessels. We fuse the gray-voting results with the 2D-Gabor filter results as pre-processing outcome. A Gaussian mixture model is then used to extract vessel clusters from the pre-processing outcome, while small vessels fragments are obtained using another gray-voting process, which complements the vessel cluster extraction already performed. At the last step, we eliminate the fragments that do not belong to the vessels based on the shape of the fragments. We evaluated the approach with two publicly available DRIVE (Staal et al., 2004) and STARE (Hoover et at., 2000) datasets with manually segmented results. For the STARE dataset, when using the second manually segmented results which include much more small vessels than the first manually segmented results as the "gold standard," this approach achieved an average sensitivity, accuracy and specificity of 65.0%, 92.1% and 97.0%, respectively. The sensitivities of this approach were much higher than those of the other existing methods, with comparable specificities; these results thus demonstrated that this approach was sensitive to detection of small vessels.
Directory of Open Access Journals (Sweden)
Peishan Dai
Full Text Available Vessel segmentation in retinal fundus images is a preliminary step to clinical diagnosis for some systemic diseases and some eye diseases. The performances of existing methods for segmenting small vessels which are usually of more importance than the main vessels in a clinical diagnosis are not satisfactory in clinical use. In this paper, we present a method for both main and peripheral vessel segmentation. A local gray-level change enhancement algorithm called gray-voting is used to enhance the small vessels, while a two-dimensional Gabor wavelet is used to extract the main vessels. We fuse the gray-voting results with the 2D-Gabor filter results as pre-processing outcome. A Gaussian mixture model is then used to extract vessel clusters from the pre-processing outcome, while small vessels fragments are obtained using another gray-voting process, which complements the vessel cluster extraction already performed. At the last step, we eliminate the fragments that do not belong to the vessels based on the shape of the fragments. We evaluated the approach with two publicly available DRIVE (Staal et al., 2004 and STARE (Hoover et at., 2000 datasets with manually segmented results. For the STARE dataset, when using the second manually segmented results which include much more small vessels than the first manually segmented results as the "gold standard," this approach achieved an average sensitivity, accuracy and specificity of 65.0%, 92.1% and 97.0%, respectively. The sensitivities of this approach were much higher than those of the other existing methods, with comparable specificities; these results thus demonstrated that this approach was sensitive to detection of small vessels.
基于高斯混合模型的腹主动脉图像分割%Image Segmentation of Abdominal Aorta Based on Gaussian Mixture Model
Institute of Scientific and Technical Information of China (English)
刘海华; 郭杰龙
2015-01-01
为了有效地分割腹主动脉图像，提出了基于适度空间约束的高斯混合模型分割算法。该算法将三维空间邻域信息融入高斯混合模型中，利用最大期望算法（ EM）获取腹部血管灰度图像的估计参数，从而分割出血管图像。实验结果表明：所提出的方法不仅能准确地分割腹主动脉的血管分支图像，而且对于图像噪声的抑制有较好的效果。%To segment the abdominal aorta from CT images effectively, a improved segmentation algorithm based on Gaussian mixture model with space constraints is proposed.This algorithm integrates 3D neighborhood information into Gaussian mixture model, then estimates the parameters of Gaussian mixture model by using EM algorithm to segment the aorta from gray image of abdominal aorta.The experiments demonstrate that the proposed not only achieves the better segmentation of aortic branches, but also inhibits noise in images by considering the spatial neighborhood information.
Itinerant Ferromagnetism in a Polarized Two-Component Fermi Gas
DEFF Research Database (Denmark)
Massignan, Pietro; Yu, Zhenhua; Bruun, Georg
2013-01-01
We analyze when a repulsively interacting two-component Fermi gas becomes thermodynamically unstable against phase separation. We focus on the strongly polarized limit, where the free energy of the homogeneous mixture can be calculated accurately in terms of well-defined quasiparticles, the repul......We analyze when a repulsively interacting two-component Fermi gas becomes thermodynamically unstable against phase separation. We focus on the strongly polarized limit, where the free energy of the homogeneous mixture can be calculated accurately in terms of well-defined quasiparticles...
Dinç, Erdal; Ertekin, Zehra Ceren; Büker, Eda
2016-09-01
Two-way and three-way calibration models were applied to ultra high performance liquid chromatography with photodiode array data with coeluted peaks in the same wavelength and time regions for the simultaneous quantitation of ciprofloxacin and ornidazole in tablets. The chromatographic data cube (tensor) was obtained by recording chromatographic spectra of the standard and sample solutions containing ciprofloxacin and ornidazole with sulfadiazine as an internal standard as a function of time and wavelength. Parallel factor analysis and trilinear partial least squares were used as three-way calibrations for the decomposition of the tensor, whereas three-way unfolded partial least squares was applied as a two-way calibration to the unfolded dataset obtained from the data array of ultra high performance liquid chromatography with photodiode array detection. The validity and ability of two-way and three-way analysis methods were tested by analyzing validation samples: synthetic mixture, interday and intraday samples, and standard addition samples. Results obtained from two-way and three-way calibrations were compared to those provided by traditional ultra high performance liquid chromatography. The proposed methods, parallel factor analysis, trilinear partial least squares, unfolded partial least squares, and traditional ultra high performance liquid chromatography were successfully applied to the quantitative estimation of the solid dosage form containing ciprofloxacin and ornidazole.
Two component theory and electron magnetic moment
Veltman, M.J.G.
1998-01-01
The two-component formulation of quantum electrodynamics is studied. The relation with the usual Dirac formulation is exhibited, and the Feynman rules for the two-component form of the theory are presented in terms of familiar objects. The transformation from the Dirac theory to the two-component th
Two component theory and electron magnetic moment
Veltman, M.J.G.
1998-01-01
The two-component formulation of quantum electrodynamics is studied. The relation with the usual Dirac formulation is exhibited, and the Feynman rules for the two-component form of the theory are presented in terms of familiar objects. The transformation from the Dirac theory to the two-component
Majka, M.; Góra, P. F.
2015-05-01
The Gaussian chain model is the classical description of a polymeric chain, which provides analytical results regarding end-to-end distance, the distribution of segments around the mass center of a chain, coarse-grained interactions between two chains and effective interactions in binary mixtures. This hierarchy of results can be calculated thanks to the α stability of the Gaussian distribution. In this paper we show that it is possible to generalize the model of Gaussian chain to the entire class of α -stable distributions, obtaining the analogous hierarchy of results expressed by the analytical closed-form formulas in the Fourier space. This allows us to establish the α -stable chain model. We begin with reviewing the applications of Levy flights in the context of polymer sciences, which include: chains described by the heavy-tailed distributions of persistence length; polymers adsorbed to the surface; and the chains driven by a noise with power-law spatial correlations. Further, we derive the distribution of segments around the mass center of the α -stable chain and construct the coarse-grained interaction potential between two chains. These results are employed to discuss the model of binary mixture consisting of the α -stable chains. In what follows, we establish the spinodal decomposition condition generalized to the mixtures of the α -stable polymers. This condition is further applied to compare the on-surface phase separation of adsorbed polymers (which are known to be described with heavy-tailed statistics) with the phase separation condition in the bulk. Finally, we predict the four different scenarios of simultaneous mixing and demixing in the two- and three-dimensional systems.
Two-component Fermi gas in a Harmonic Trap
Yi, X X; Cui, H T; Zhang, C M
2002-01-01
We consider a mixture of two-component Fermi gases at low temperature. The density profile of this degenerate Fermi gas is calculated under the semiclassical approximation. The results show that the fermion-fermion interactions make a large correction to the density profile at low temperature. The phase separation of such a mixture is also discussed for both attractive and repulsive interatomic interactions, and the numerical calculations demonstrate the exist of a stable temperature region $T_{c1}
Two-component Duality and Strings
Freund, Peter G O
2007-01-01
A phenomenologically successful two-component hadronic duality picture led to Veneziano's amplitude, the fundamental first step to string theory. This picture is briefly recalled and its two components are identified as the open strings (mesons and baryons) and closed strings (Pomeron).
Yu, Kai; Chen, Xinjian; Shi, Fei; Zhu, Weifang; Zhang, Bin; Xiang, Dehui
2016-03-01
Positron Emission Tomography (PET) and Computed Tomography (CT) have been widely used in clinical practice for radiation therapy. Most existing methods only used one image modality, either PET or CT, which suffers from the low spatial resolution in PET or low contrast in CT. In this paper, a novel 3D graph cut method is proposed, which integrated Gaussian Mixture Models (GMMs) into the graph cut method. We also employed the random walk method as an initialization step to provide object seeds for the improvement of the graph cut based segmentation on PET and CT images. The constructed graph consists of two sub-graphs and a special link between the sub-graphs which penalize the difference segmentation between the two modalities. Finally, the segmentation problem is solved by the max-flow/min-cut method. The proposed method was tested on 20 patients' PET-CT images, and the experimental results demonstrated the accuracy and efficiency of the proposed algorithm.
Directory of Open Access Journals (Sweden)
Silva-Aguilar Martín
2011-01-01
Full Text Available Metals are ubiquitous pollutants present as mixtures. In particular, mixture of arsenic-cadmium-lead is among the leading toxic agents detected in the environment. These metals have carcinogenic and cell-transforming potential. In this study, we used a two step cell transformation model, to determine the role of oxidative stress in transformation induced by a mixture of arsenic-cadmium-lead. Oxidative damage and antioxidant response were determined. Metal mixture treatment induces the increase of damage markers and the antioxidant response. Loss of cell viability and increased transforming potential were observed during the promotion phase. This finding correlated significantly with generation of reactive oxygen species. Cotreatment with N-acetyl-cysteine induces effect on the transforming capacity; while a diminution was found in initiation, in promotion phase a total block of the transforming capacity was observed. Our results suggest that oxidative stress generated by metal mixture plays an important role only in promotion phase promoting transforming capacity.
Inhibitors targeting two-component signal transduction.
Watanabe, Takafumi; Okada, Ario; Gotoh, Yasuhiro; Utsumi, Ryutaro
2008-01-01
A two-component signal transduction system (TCS) is an attractive target for antibacterial agents. In this chapter, we review the TCS inhibitors developed during the past decade and introduce novel drug discovery systems to isolate the inhibitors of the YycG/YycF system, an essential TCS for bacterial growth, in an effort to develop a new class of antibacterial agents.
Trajectory Prediction Algorithm Based on Gaussian Mixture Model%一种基于高斯混合模型的轨迹预测算法
Institute of Scientific and Technical Information of China (English)
乔少杰; 金琨; 韩楠; 唐常杰; 格桑多吉; Louis Alberto GUTIERREZ
2015-01-01
For intelligent transportation systems, digital military battlefield and driver assistance systems, it is of great practical value to predict the trajectories of moving objects with uncertainty in a real-time, accurate and reliable fashion. Intelligent trajectory prediction can not only provide accurate location-based services, but also monitor and estimate traffic to suggest the best path, and as such becomes an active research direction. Aiming to overcome the drawbacks of the existing methods, a new trajectory prediction model based on Gaussian mixture models called GMTP is proposed. The new model contains the following essential phases: (1) modeling the complex motion patterns based on Gaussian mixture models, (2) calculating the probability distribution of different types of motion patterns by using Gaussian mixture model in order to partition trajectory data into distinct components, and (3) inferring the most possible trajectories of moving objects via Gaussian process regression. The GMTP algorithm is naturally a Gaussian nonlinear statistical probability model and the advantage of the proposed model is that the result is not only a predicted value, but also a whole distribution beyond the future trajectories, therefore making it possible to infer the location in regard to some motion patterns, e.g., uniformly accelerated motion, by using statistical probability distribution. Extensive experiments are conducted on real trajectory data sets and the results show that the prediction accuracy of the GMTP algorithm is improved by 22.2% and 23.8%, and the runtime can be reduced by 92.7% and 95.9% on average, respectively, when compared to the Gaussian process regression model and Kalman filter prediction algorithm with similar parameter setting.%在智能交通控制系统、军事数字化战场、辅助驾驶系统中,实时、精确、可靠的移动对象不确定性轨迹预测具有极高的应用价值.智能轨迹预测不仅可以提供精准的基
Institute of Scientific and Technical Information of China (English)
程红伟; 陶俊勇; 蒋瑜; 陈循
2014-01-01
Aiming at the difficulty in deriving mathematical expressions of amplitude probability density functions of non-Gaussian vibrations,a Gaussian mixture model-based probability density function (PDF ) was proposed for non-Gaussian vibration signals.The estimation of higher-order moments of a non-Gaussian vibration process was obtained with sample time histories.Based on the quantitative relations between the even order moments of a given Gaussian process, combining with a secorld order Gaussian mixture model,an equation set for achieving the parameters of each Gaussian component in the Gaussian mixture model was established.Based on the obtained weighting factors and variances of Gaussian components,the mathematical model of non-Gaussian probability density function was then achieved.The examples of simulated signals and measured signals verified the validity of the presented method.%针对非高斯振动信号的幅值概率密度函数难以用数学模型表述的问题，提出了基于高斯混合模型的非高斯概率密度函数表示方法。首先，基于时域样本信号得到非高斯振动信号的高阶矩估计值。其次，基于高斯随机过程偶次高阶矩之间的定量关系，结合二阶高斯混合模型建立方程组，求解得到混合模型中每个高斯分量的方差和权值。然后，将各高斯分量的权值和方差代入高斯混合模型，得到适用于对称非高斯振动信号的幅值概率密度函数。最后，通过仿真信号和实测振动信号，验证了该方法的有效性和适用性。
Itinerant ferromagnetism in a polarized two-component Fermi gas.
Massignan, Pietro; Yu, Zhenhua; Bruun, Georg M
2013-06-07
We analyze when a repulsively interacting two-component Fermi gas becomes thermodynamically unstable against phase separation. We focus on the strongly polarized limit, where the free energy of the homogeneous mixture can be calculated accurately in terms of well-defined quasiparticles, the repulsive polarons. Phase diagrams as a function of polarization, temperature, mass imbalance, and repulsive polaron energy, as well as scattering length and range parameter, are provided. We show that the lifetime of the repulsive polaron increases significantly with the interaction range and the mass of the minority atoms, raising the prospects of detecting the transition to the elusive itinerant ferromagnetic state with ultracold atoms.
Two-component Abelian sandpile models.
Alcaraz, F C; Pyatov, P; Rittenberg, V
2009-04-01
In one-component Abelian sandpile models, the toppling probabilities are independent quantities. This is not the case in multicomponent models. The condition of associativity of the underlying Abelian algebras imposes nonlinear relations among the toppling probabilities. These relations are derived for the case of two-component quadratic Abelian algebras. We show that Abelian sandpile models with two conservation laws have only trivial avalanches.
Chen, Tai-Been; Chen, Jyh-Cheng; Lu, Henry Horng-Shing
2012-01-01
Segmentation of positron emission tomography (PET) is typically achieved using the K-Means method or other approaches. In preclinical and clinical applications, the K-Means method needs a prior estimation of parameters such as the number of clusters and appropriate initialized values. This work segments microPET images using a hybrid method combining the Gaussian mixture model (GMM) with kernel density estimation. Segmentation is crucial to registration of disordered 2-deoxy-2-fluoro-D-glucose (FDG) accumulation locations with functional diagnosis and to estimate standardized uptake values (SUVs) of region of interests (ROIs) in PET images. Therefore, simulation studies are conducted to apply spherical targets to evaluate segmentation accuracy based on Tanimoto's definition of similarity. The proposed method generates a higher degree of similarity than the K-Means method. The PET images of a rat brain are used to compare the segmented shape and area of the cerebral cortex by the K-Means method and the proposed method by volume rendering. The proposed method provides clearer and more detailed activity structures of an FDG accumulation location in the cerebral cortex than those by the K-Means method.
Avendaño-Valencia, Luis David; Fassois, Spilios D.
2017-07-01
The study focuses on vibration response based health monitoring for an operating wind turbine, which features time-dependent dynamics under environmental and operational uncertainty. A Gaussian Mixture Model Random Coefficient (GMM-RC) model based Structural Health Monitoring framework postulated in a companion paper is adopted and assessed. The assessment is based on vibration response signals obtained from a simulated offshore 5 MW wind turbine. The non-stationarity in the vibration signals originates from the continually evolving, due to blade rotation, inertial properties, as well as the wind characteristics, while uncertainty is introduced by random variations of the wind speed within the range of 10-20 m/s. Monte Carlo simulations are performed using six distinct structural states, including the healthy state and five types of damage/fault in the tower, the blades, and the transmission, with each one of them characterized by four distinct levels. Random vibration response modeling and damage diagnosis are illustrated, along with pertinent comparisons with state-of-the-art diagnosis methods. The results demonstrate consistently good performance of the GMM-RC model based framework, offering significant performance improvements over state-of-the-art methods. Most damage types and levels are shown to be properly diagnosed using a single vibration sensor.
Two-component model of solar plages
Institute of Scientific and Technical Information of China (English)
LI; Jianping(李建平); DING; Mingde(丁明德); FANG; Cheng(方成)
2002-01-01
By use of the 2-m Mcmath-Pierce telescope at Kitt Peak, the high-quality spectra of a plage with moderate brightness near the center of solar disk were obtained. The data include seven spectral lines, which are Hα, Hβ, CaII H and K lines and the infrared triplet. With the consideration of fine structures of solar plages, a two-component atmospheric model is constructed by keeping the cool component to be the quiet atmosphere. Three cases of the hot component are given for different filling factors where the temperature and density distribution are adjusted in order to reproduce the seven observed spectral profiles. We also briefly discuss the influence of the column density at the base of the corona, m0, and the macro-turbulent velocity on the required filling factor and computed profiles. The two-component model is compared with precious one-component semi-empirical models. The limitation of the model is pointed out and further improvement is indicated.
Two Component Signal Transduction in Desulfovibrio Species
Energy Technology Data Exchange (ETDEWEB)
Luning, Eric; Rajeev, Lara; Ray, Jayashree; Mukhopadhyay, Aindrila
2010-05-17
The environmentally relevant Desulfovibrio species are sulfate-reducing bacteria that are of interest in the bioremediation of heavy metal contaminated water. Among these, the genome of D. vulgaris Hildenborough encodes a large number of two component systems consisting of 72 putative response regulators (RR) and 64 putative histidinekinases (HK), the majority of which are uncharacterized. We classified the D. vulgaris Hildenborough RRs based on their output domains and compared the distribution of RRs in other sequenced Desulfovibrio species. We have successfully purified most RRs and several HKs as His-tagged proteins. We performed phospho-transfer experiments to verify relationships between cognate pairs of HK and RR, and we have also mapped a few non-cognate HK-RR pairs. Presented here are our discoveries from the Desulfovibrio RR categorization and results from the in vitro studies using purified His tagged D. vulgaris HKs and RRs.
Two-Component Description for Relativistic Fermions
Institute of Scientific and Technical Information of China (English)
CHEN Yu-Qi; SANG Wen-Long; YANG Lan-Fei
2009-01-01
We propose a two-component form to describe massive relativistic fermions in gauge theories. Relations between the Green's functions in this form and those in the conventional four-component form are derived. It is shown that the S-matrix elements in both forms are exactly the same. The description of the fermion in the new form simplifies significantly the γ-matrix algebra in the four-component form. In particular, in perturbative calculations the propagator of the fermion is a scalar function. As examples, we use this form to reproduce the relativistic spectrum of hydrodron atom, the S-matrix of e+ e-→μ+ μ- and QED one-loop vacuum polarization of photon.
Tobacco two-component gene NTHK2
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
By using a previously isolated tobacco two- component gene NTHK1 as a probe, we screened a cDNA library and obtained a homologous gene designated NTHK2. Sequencing analysis revealed that NTHK2 encoded a putative ethylene receptor homolog and contained a histidine kinase domain and a receiver domain. In the histidine kinase domain, the histidine at the phosphorylation site was replaced by an asparagine. Southern analysis indicated that NTHK2 was present at low copies in tobacco genome. The expression of NTHK2 was studied using a competitive RT-PCR method. It was found that, in young flower buds, NTHK2 was expressed abundantly, while in other organs or tissues, it was expressed in a low level. When leaf was subjected to wounding (cutting) treatment, NTHK2 expression was increased. When tobacco seedlings were stressed with PEG and heat shock, NTHK2 transcription was also enhanced. Other treatments showed little effects. These results indicated that NTHK2 might be involved in the developmental processes and in plant responses to some environmental stresses.
Energy Technology Data Exchange (ETDEWEB)
Liu, T [Department of Radiation Oncology and Winship Cancer Institute, Emory Univ, Atlanta, GA (United States); Yu, D; Beitler, J; Curran, W; Yang, X [Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA (United States); Tridandapani, S [Department of Radiology and Imaging Sciences and Winship Cancer Institute, Emory University, Atlanta, GA (United States); Bruner, D [School of Nursing and Winship Cancer Institute, Emory Univesity, Atlanta, GA (United States)
2014-06-15
Purpose: Xerostomia (dry mouth), secondary to parotid-gland injury, is a distressing side-effect in head-and-neck radiotherapy (RT). This study's purpose is to develop a novel ultrasound technique to quantitatively evaluate post-RT parotid-gland injury. Methods: Recent ultrasound studies have shown that healthy parotid glands exhibit homogeneous echotexture, whereas post-RT parotid glands are often heterogeneous, with multiple hypoechoic (inflammation) or hyperechoic (fibrosis) regions. We propose to use a Gaussian mixture model to analyze the ultrasonic echo-histogram of the parotid glands. An IRB-approved clinical study was conducted: (1) control-group: 13 healthy-volunteers, served as the control; (2) acutetoxicity group − 20 patients (mean age: 62.5 ± 8.9 years, follow-up: 2.0±0.8 months); and (3) late-toxicity group − 18 patients (mean age: 60.7 ± 7.3 years, follow-up: 20.1±10.4 months). All patients experienced RTOG grade 1 or 2 salivary-gland toxicity. Each participant underwent an ultrasound scan (10 MHz) of the bilateral parotid glands. An echo-intensity histogram was derived for each parotid and a Gaussian mixture model was used to fit the histogram using expectation maximization (EM) algorithm. The quality of the fitting was evaluated with the R-squared value. Results: (1) Controlgroup: all parotid glands fitted well with one Gaussian component, with a mean intensity of 79.8±4.9 (R-squared>0.96). (2) Acute-toxicity group: 37 of the 40 post-RT parotid glands fitted well with two Gaussian components, with a mean intensity of 42.9±7.4, 73.3±12.2 (R-squared>0.95). (3) Latetoxicity group: 32 of the 36 post-RT parotid fitted well with 3 Gaussian components, with mean intensities of 49.7±7.6, 77.2±8.7, and 118.6±11.8 (R-squared>0.98). Conclusion: RT-associated parotid-gland injury is common in head-and-neck RT, but challenging to assess. This work has demonstrated that the Gaussian mixture model of the echo-histogram could quantify acute and
基于Davinei-DM6467的高斯混合模型算法的实现%Realization of gaussian mixture model algorithm based on Davinci-DM6467
Institute of Scientific and Technical Information of China (English)
刘德方; 王戴木; 邓明; 陈静; 赵正平
2012-01-01
针对智能监控中运动目标检测的问题，提出了基于Davinci—DM6467的高斯混合模型像素级的背景分割策略。对彩色图像建立高斯混合模型，根据场景中象素点的稳定性来调整模型参数的更新速率；通过和马氏阈值进行对比来判断是不是要更新背景模型；通过和背景阈值进行对比来判断哪几个模型是属于背景区域。经验证性实验测试，结果表明，高斯混合模型在运动检测中实时性好，对环境有较强的鲁棒性。%In the light of movement target detection during intelligence monitoring, the author put forward Gaussian mixture model of pixel level background segmentation strategy based on Davinei-DM6467. Firstly establishing Gaussian mixture model for colorful images and then adjusting the updating velocity of model parameters according to the stability of each pixels in frames ; secondly comparing them with Markov threshold to judge whether to update the background model; finally comparing them with back-ground threshold to judge which several models belong to background region. Experimental results show that Gaussian mixture model in motion detection is possessed of good real-time and strong robustness to environment.
An Introductory Idea for Teaching Two-Component Phase Diagrams
Peckham, Gavin D.; McNaught, Ian J.
2011-01-01
The teaching of two-component phase diagrams has attracted little attention in this "Journal," and it is hoped that this article will make a useful contribution. Current physical chemistry textbooks describe two-component phase diagrams adequately, but do so in a piecemeal fashion one section at a time; first solid-liquid equilibria, then…
Two-component micro injection moulding for hearing aid applications
DEFF Research Database (Denmark)
Islam, Aminul; Hansen, Hans Nørgaard; Marhöfer, David Maximilian
2012-01-01
Two-component (2k) injection moulding is an important process technique at the present state of technology, and it is growing rapidly in the field of precision micro moulding. Besides combining different material properties in the same product, two-component moulding can eliminate many assembly s...
Feedback Control of Two-Component Regulatory Systems.
Groisman, Eduardo A
2016-09-08
Two-component systems are a dominant form of bacterial signal transduction. The prototypical two-component system consists of a sensor that responds to a specific input(s) by modifying the output of a cognate regulator. Because the output of a two-component system is the amount of phosphorylated regulator, feedback mechanisms may alter the amount of regulator, and/or modify the ability of a sensor or other proteins to alter the phosphorylation state of the regulator. Two-component systems may display intrinsic feedback whereby the amount of phosphorylated regulator changes under constant inducing conditions and without the participation of additional proteins. Feedback control allows a two-component system to achieve particular steady-state levels, to reach a given steady state with distinct dynamics, to express coregulated genes in a given order, and to activate a regulator to different extents, depending on the signal acting on the sensor.
Institute of Scientific and Technical Information of China (English)
孔晨燕; 谢从华; 苏剑峰; 于丹
2012-01-01
To remove the trailing noise, histogram fuzzy based filter denoising methods often have the problems of image blurring and residual noisy. To address this problem, the authors of this paper propose a new image de⁃noising method based on Generalized Gaussian Mixture (GGM) model and weighted average image filter. Firstly, the generalized Gaussian mixture model for image is constructed. Secondly, the noise data is determined accord⁃ing to the feature differences between this point and its neighbors. Finally, a weighted average filter is construct⁃ed by the GGM to build an image denoising. Histogram based filter and classical partial differential equation method are compared with the proposed method. Experimental results show that the method has a better denois⁃ing effect than the other methods.% 基于直方图的模糊滤波方法对图像的拖尾噪声去噪会导致图像模糊、残留的噪声较多等问题，本文提出一种新的基于广义高斯混合模型的图像去噪方法。首先，建立图像的广义高斯分布及其有限混合模型；其次，通过像素周围点特征值的变化范围确定噪声数据；最后，利用广义高斯函数构建一个加权平均滤波器进行图像去噪。对基于直方图的滤波方法、经典的偏微分方程和本文方法进行比较实验，结果表明本文方法具有更好的去噪效果。
Mixture Based Outlier Filtration
Directory of Open Access Journals (Sweden)
P. Pecherková
2006-01-01
Full Text Available Success/failure of adaptive control algorithms – especially those designed using the Linear Quadratic Gaussian criterion – depends on the quality of the process data used for model identification. One of the most harmful types of process data corruptions are outliers, i.e. ‘wrong data’ lying far away from the range of real data. The presence of outliers in the data negatively affects an estimation of the dynamics of the system. This effect is magnified when the outliers are grouped into blocks. In this paper, we propose an algorithm for outlier detection and removal. It is based on modelling the corrupted data by a two-component probabilistic mixture. The first component of the mixture models uncorrupted process data, while the second models outliers. When the outlier component is detected to be active, a prediction from the uncorrupted data component is computed and used as a reconstruction of the observed data. The resulting reconstruction filter is compared to standard methods on simulated and real data. The filter exhibits excellent properties, especially in the case of blocks of outliers.
Indian Academy of Sciences (India)
Surendra P Verma
2000-03-01
This paper presents error propagation equations for modeling of radiogenic isotopes during mixing of two components or end-members. These equations can be used to estimate errors on an isotopic ratio in the mixture of two components, as a function of the analytical errors or the total errors of geological field sampling and analytical errors. Two typical cases (``Small errors'' and ``Large errors'') are illustrated for mixing of Sr isotopes. Similar examples can be formulated for the other radiogenic isotopic ratios. Actual isotopic data for sediment and basalt samples from the Cocos plate are also included to further illustrate the use of these equations. The isotopic compositions of the predicted mixtures can be used to constrain the origin of magmas in the central part of the Mexican Volcanic Belt. These examples show the need of high quality experimental data for them to be useful in geochemical modeling of magmatic processes.
Receptor domains of two-component signal transduction systems.
Perry, Julie; Koteva, Kalinka; Wright, Gerard
2011-05-01
Two-component signal transduction systems are found ubiquitously in prokaryotes, and in archaea, fungi, yeast and some plants, where they regulate physiologic and molecular processes at both transcriptional and post-transcriptional levels. Two-component systems sense changes in environmental conditions when a specific ligand binds to the receptor domain of the histidine kinase sensory component. The structures of many histidine kinase receptors are known, including those which sense extracellular and cytoplasmic signals. In this review, we discuss the basic architecture of two-component signalling circuits, including known system ligands, structure and function of both receptor and signalling domains, the chemistry of phosphotransfer, and cross-talk between different two-component pathways. Given the importance of these systems in regulating cellular responses, many biochemical techniques have been developed for their study and analysis. We therefore also review current methods used to study two-component signalling, including a new affinity-based proteomics approach used to study inducible resistance to the antibiotic vancomycin through the VanSR two-component signal transduction system.
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
We re-examine the ten Reverberation Mapping(RM) sources with public data based on the two-component model of the Broad Line Region(BLR).In fitting their broad Hβ Mlines,six of them only need one Gaussian component,one of them has a double-peak profile,one has an irregular profile,and only two of them need two components,i.e.,a Very Broad Gaussian Component(VBGC) and an Inter-Mediate Gaussian Component(IMGC).The Gaussian components are assumed to come from two distinct regions in the two-component model;they are the Very Broad Line Region(VBLR) and the Inter-Mediate Line region(IMLR).The two sources with a two-component profile are Mrk 509 and NGC 4051.The time lags of the two components of both sources satisfy tIMLR/tVBLR=V 2VBLR/V 2IMLR,where tIMLR and tVBLR are the lags of the two components while VIMLR and VVBLR represent the mean gas velocities of the two regions,supporting the two-component model of the BLR of Active Galactic Nuclei(AGNs).The fact that most of these ten sources only have the VBGC confirms the assumption that RM mainly measures the radius of the VBLR;consequently,the radius obtained from the R-L relationship mainly represents the radius of VBLR.Moreover,NGC 4051,with a lag of about 5 days in the one component model,is an outlier on the R-L relationship as shown in Kaspi et al.(2005);however this problem disappears in our two-component model with lags of about 2 and 6 days for the VBGC and IMGC,respectively.
Light-induced thermodiffusion in two-component media
Ivanov, V.; Ivanova, G.; Okishev, K.; Khe, V.
2017-01-01
We have theoretically studied the optical transmittance response of thin cell with liquid containing absorbing nanoparticles in a Gaussian beam field. The transmittance spatial changing is caused by thermal diffusion phenomenon (Soret effect) which produces the variations of concentration of absorbing nanoparticles. The thickness of optical cell (including windows) is significantly less than the size of the beam. As a result, an exact analytical expression for the one dimensional thermal task is derived, taking into account the Soret feedback that leads to the temperature rising on the axis of a Gaussian beam. We have experimentally studied this phenomenon in carbon nanosuspension.
Circulation Condition of Two-component Bose-Einstein Condensate
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In the report we point out that there exists an intrinsic difference in the internal symmetry of the two components spin-1/2 Bose condensates from that of spinor Bose condensates of the atoms with hyperfine states of nonzero integer-spins,which gives rise to a new topological constrain on the circulation for this two-component spin-1/2 Bose condensates.It is shown that the SU(2) symmetry of the spin-1/2 Bose condensate implies a
Two-component membrane material properties and domain formation from dissipative particle dynamics.
Illya, G; Lipowsky, R; Shillcock, J C
2006-09-21
The material parameters (area stretch modulus and bending rigidity) of two-component amphiphilic membranes are determined from dissipative particle dynamics simulations. The preferred area per molecule for each species is varied so as to produce homogeneous mixtures or nonhomogeneous mixtures that form domains. If the latter mixtures are composed of amphiphiles with the same tail length, but different preferred areas per molecule, their material parameters increase monotonically as a function of composition. By contrast, mixtures of amphiphiles that differ in both tail length and preferred area per molecule form both homogeneous and nonhomogeneous mixtures that both exhibit smaller values of their material properties compared to the corresponding pure systems. When the same nonhomogeneous mixtures of amphiphiles are assembled into planar membrane patches and vesicles, the resulting domain shapes are different when the bending rigidities of the domains are sufficiently different. Additionally, both bilayer and monolayer domains are observed in vesicles. We conclude that the evolution of the domain shapes is influenced by the high curvature of the vesicles in the simulation, a result that may be relevant for biological vesicle membranes.
Two component permeation through thin zeolite MFI membranes
Keizer, K.; Burggraaf, A.J.; Vroon, Z.A.E.P.; Verweij, H.
1998-01-01
Two component permeation measurements have been performed by the Wicke-Kallenbach method on a thin (3 μm) zeolite MFI (Silicalite-1) membrane with molecules of different kinetic diameters, d(k). The membrane was supported by a flat porous α-Al2O3 substrate. The results obtained could be classified i
two component permeation through thin zeolite MFI membranes
Keizer, Klaas; Burggraaf, Anthonie; Burggraaf, A.J.; Vroon, Z.A.E.P.; Vroon, Z.A.E.P.; Verweij, H.
1998-01-01
Two component permeation measurements have been performed by the Wicke–Kallenbach method on a thin (3 μm) zeolite MFI (Silicalite-1) membrane with molecules of different kinetic diameters, dk. The membrane was supported by a flat porous -Al2O3 substrate. The results obtained could be classified in s
TWO-COMPONENT JETS AND THE FANAROFF-RILEY DICHOTOMY
Meliani, Z.; Keppens, R.; Sauty, C.
2010-01-01
Transversely stratified jets are observed in many classes of astrophysical objects, ranging from young stellar objects, mu-quasars, to active galactic nuclei and even in gamma-ray bursts. Theoretical arguments support this transverse stratification of jets with two components induced by intrinsic fe
Two component injection moulding: Present and future perspectives
DEFF Research Database (Denmark)
Islam, Aminul; Hansen, Hans Nørgaard
2009-01-01
Two component injection moulding has widespread industrial applications. Still the technology is yet to gain its full potential in highly demanding and technically challenging applications areas. The smart use of this technology can open the doors for cost effective and convergent manufacturing...
Entanglement Properties in Two-Component Bose-Einstein Condensate
Jiang, Di-You
2016-10-01
We investigate entanglement inseparability and bipartite entanglement of in two-component Bose-Einstein condensate in the presence of the nonlinear interatomic interaction, interspecies interaction. Entanglement inseparability and bipartite entanglement have the similar properties. More entanglement can be generated by adjusting the nonlinear interatomic interaction and control the time interval of the entanglement by adjusting interspecies interaction.
Goal-Directed Aiming: Two Components but Multiple Processes
Elliott, Digby; Hansen, Steve; Grierson, Lawrence E. M.; Lyons, James; Bennett, Simon J.; Hayes, Spencer J.
2010-01-01
This article reviews the behavioral literature on the control of goal-directed aiming and presents a multiple-process model of limb control. The model builds on recent variants of Woodworth's (1899) two-component model of speed-accuracy relations in voluntary movement and incorporates ideas about dynamic online limb control based on prior…
Gaussian Sum PHD Filtering Algorithm for Nonlinear Non-Gaussian Models
Institute of Scientific and Technical Information of China (English)
Yin Jianjun; Zhang Jianqiu; Zhuang Zesen
2008-01-01
A new multi-target filtering algorithm, termed as the Gaussian sum probability hypothesis density (GSPHD) filter, is proposed for nonlinear non-Gaussian tracking models. Provided that the initial prior intensity of the states is Gaussian or can be identified as a Gaussiaa sum, the analytical results of the algorithm show that the posterior intensity at any subsequent time step remains a Gaussian sum under the assumption that the state noise, the measurement noise, target spawn intensity, new target birth intensity, target survival probability, and detection probability are all Gaussian sums. The analysis also shows that the existing Gaassian mixture probability hypothesis density (GMPHD) filter, which is unsuitable for handling the non-Gaussian noise cases, is no more than a special ease of the proposed algorithm, which fills the shortage of incapability of treating non-Gaussian noise. The multi-target tracking simulation results verify the effectiveness of the proposed GSPHD.
Kox, Linda F.F.; Wösten, Marc M. S. M.; Groisman, Eduardo A.
2000-01-01
The PmrA–PmrB two-component system of Salmonella enterica controls resistance to the peptide antibiotic polymyxin B and to several antimicrobial proteins from human neutrophils. Transcription of PmrA-activated genes is induced by high iron, but can also be promoted by growth in low magnesium in a process that requires another two-component system, PhoP–PhoQ. Here, we define the genetic basis for the interaction between the PhoP–PhoQ and PmrA–PmrB systems. We have identified pmrD as a PhoP-act...
Institute of Scientific and Technical Information of China (English)
奚玲; 平西建; 张昊
2012-01-01
Aiming at the security problem of adaptive steganography, the analysis method based on Gaussian mixture model(GMM) of real image is proposed. Compared the stego random characteristic function of probability density function between the adaptive Spread Spectrum Image Steganography(SSIS) and the general non adaptive one under the condition that the total embedding intensity is equal, it demonstrates that the security of adaptive SSIS is higher than that of non-adaptive schemes. Analysis result shows that the method provides theoretical evidence for using adaptive scheme to improve statistical imperceptibility of steganography.%对自适应隐写的安全性问题进行分析,提出一种基于自然图像的高斯混合模型分析方法.在总嵌入强度相同的条件下,比较自适应和非自适应扩频隐写载密随机变量概率密度函数的特征函数,验证自适应扩频隐写的统计安全性高于等嵌入强度下非自适应扩频隐写.分析结果表明,该方法能为提升信息隐藏系统的抗统计分析性能提供理论依据.
Cluster Sampling Filters for Non-Gaussian Data Assimilation
2016-01-01
This paper presents a fully non-Gaussian version of the Hamiltonian Monte Carlo (HMC) sampling filter. The Gaussian prior assumption in the original HMC filter is relaxed. Specifically, a clustering step is introduced after the forecast phase of the filter, and the prior density function is estimated by fitting a Gaussian Mixture Model (GMM) to the prior ensemble. Using the data likelihood function, the posterior density is then formulated as a mixture density, and is sampled using a HMC appr...
A two-component NZRI metamaterial based rectangular cloak
Islam, Sikder Sunbeam; Faruque, Mohammd Rashed Iqbal; Islam, Mohammad Tariqul
2015-10-01
A new two-component, near zero refractive index (NZRI) metamaterial is presented for electromagnetic rectangular cloaking operation in the microwave range. In the basic design a pi-shaped, metamaterial was developed and its characteristics were investigated for the two major axes (x and z-axis) wave propagation through the material. For the z-axis wave propagation, it shows more than 2 GHz bandwidth and for the x-axis wave propagation; it exhibits more than 1 GHz bandwidth of NZRI property. The metamaterial was then utilized in designing a rectangular cloak where a metal cylinder was cloaked perfectly in the C-band area of microwave regime. The experimental result was provided for the metamaterial and the cloak and these results were compared with the simulated results. This is a novel and promising design for its two-component NZRI characteristics and rectangular cloaking operation in the electromagnetic paradigm.
On a periodic two-component Hunter-Saxton equation
Kohlmann, Martin
2011-01-01
We determine the solution of the geodesic equation associated with a periodic two-component Hunter-Saxton system on a semidirect product obtained from the diffeomorphism group of the circle, modulo rigid rotations, and a space of scalar functions. In particular, we compute the time of breakdown of the geodesic flow. As a further goal, we establish a local well-posedness result for the two-component Hunter-Saxton system in the smooth category. The paper gets in line with some recent results for the generalized Hunter-Saxton equation provided by Escher, Wu and Wunsch in [J. Escher, Preprint 2010] and [H. Wu, M. Wunsch, arXiv:1009.1688v1 [math.AP
Two Component Injection Moulding for Moulded Interconnect Devices
DEFF Research Database (Denmark)
Islam, Aminul
The moulded interconnect devices (MIDs) contain huge possibilities for many applications in micro electro-mechanical-systems because of their potential in reducing the number of components, process steps and finally in miniaturization of the product. Among the available MID process chains, two...... component (2k) injection moulding is one of the most industrially adaptive processes. However, the use of two component injection moulding for MID fabrication, with circuit patterns in sub-millimeter range, is still a big challenge. This book searches for the technical difficulties associated...... with the process and makes attempts to overcome those challenges. In search of suitable polymer materials for MID applications, potential materials are characterized in terms of polymer-polymer bond strength, polymer-polymer interface quality and selective metallization. The experimental results find the factors...
Two-component microinjection moulding for MID fabrication
DEFF Research Database (Denmark)
Islam, Aminul; Hansen, Hans Nørgaard; Tang, Peter Torben
2010-01-01
Moulded interconnect devices (MIDs) are plastic substrates with electrical infrastructure. The fabrication of MIDs is usually based on injection moulding, and different process chains may be identified from this starting point. The use of MIDs has been driven primarily by the automotive sector......, but recently, the medical sector seems more and more interested. In particular, the possibility of miniaturisation of three-dimensional components with electrical infrastructure is attractive. The present paper describes possible manufacturing routes and challenges of miniaturised MIDs based on two......-component injection moulding and subsequent metallisation. This technology promises cost effective and convergent manufacturing approaches for both macro- and microapplications. This paper presents the results of industrial MID production based on two-component injection moulding and discusses the important issues...
Packing characteristics of two-component bilayers composed of ester- and ether-linked phospholipids.
Batenjany, M M; O'Leary, T J; Levin, I W; Mason, J T
1997-01-01
The miscibility properties of ether- and ester-linked phospholipids in two-component, fully hydrated bilayers have been studied by differential scanning calorimetry (DSC) and Raman spectroscopy. Mixtures of 1,2-di-O-hexadecyl-rac-glycero-3-phosphocholine (DHPC) with 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine (DHPE) and of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) with 1,2-di-O-hexadecyl-sn-glycero-3-phosphoethanolamine (DHPE) have been investigated. The phase diagram for the DPPC/DHPE mixtures indicates that these two phospholipids are miscible in all proportions in the nonrippled bilayer gel phase. In contrast, the DHPC/DPPE mixtures display two regions of gel phase immiscibility between 10 and 30 mol% DPPE. Raman spectroscopic measurements of DHPC/DPPE mixtures in the C-H stretching mode region suggest that this immiscibility arises from the formation of DHPC-rich interdigitated gel phase domains with strong lateral chain packing interactions at temperatures below 27 degrees C. However, in the absence of interdigitation, our findings, and those of others, lead to the conclusion that the miscibility properties of mixtures of ether- and ester-linked phospholipids are determined by the nature of the phospholipid headgroups and are independent of the character of the hydrocarbon chain linkages. Thus it seems unlikely that the ether linkage has any significant effect on the miscibility properties of phospholipids in biological membranes. PMID:9083673
Interaction Analysis of a Two-Component System Using Nanodiscs.
Directory of Open Access Journals (Sweden)
Patrick Hörnschemeyer
Full Text Available Two-component systems are the major means by which bacteria couple adaptation to environmental changes. All utilize a phosphorylation cascade from a histidine kinase to a response regulator, and some also employ an accessory protein. The system-wide signaling fidelity of two-component systems is based on preferential binding between the signaling proteins. However, information on the interaction kinetics between membrane embedded histidine kinase and its partner proteins is lacking. Here, we report the first analysis of the interactions between the full-length membrane-bound histidine kinase CpxA, which was reconstituted in nanodiscs, and its cognate response regulator CpxR and accessory protein CpxP. Using surface plasmon resonance spectroscopy in combination with interaction map analysis, the affinity of membrane-embedded CpxA for CpxR was quantified, and found to increase by tenfold in the presence of ATP, suggesting that a considerable portion of phosphorylated CpxR might be stably associated with CpxA in vivo. Using microscale thermophoresis, the affinity between CpxA in nanodiscs and CpxP was determined to be substantially lower than that between CpxA and CpxR. Taken together, the quantitative interaction data extend our understanding of the signal transduction mechanism used by two-component systems.
Rewiring the specificity of two-component signal transduction systems.
Skerker, Jeffrey M; Perchuk, Barrett S; Siryaporn, Albert; Lubin, Emma A; Ashenberg, Orr; Goulian, Mark; Laub, Michael T
2008-06-13
Two-component signal transduction systems are the predominant means by which bacteria sense and respond to environmental stimuli. Bacteria often employ tens or hundreds of these paralogous signaling systems, comprised of histidine kinases (HKs) and their cognate response regulators (RRs). Faithful transmission of information through these signaling pathways and avoidance of detrimental crosstalk demand exquisite specificity of HK-RR interactions. To identify the determinants of two-component signaling specificity, we examined patterns of amino acid coevolution in large, multiple sequence alignments of cognate kinase-regulator pairs. Guided by these results, we demonstrate that a subset of the coevolving residues is sufficient, when mutated, to completely switch the substrate specificity of the kinase EnvZ. Our results shed light on the basis of molecular discrimination in two-component signaling pathways, provide a general approach for the rational rewiring of these pathways, and suggest that analyses of coevolution may facilitate the reprogramming of other signaling systems and protein-protein interactions.
Directory of Open Access Journals (Sweden)
César Soto-Valero
2017-07-01
Full Text Available The generation and availability of football data has increased considerably last decades, mostly due to its popularity and also because of technological advances. Gaussian mixture clustering models represents a novel approach to exploring and analyzing performance data in sports. In this paper, we use principal components analysis in conjunction with a model-based Gaussian clustering method with the purpose of characterizing professional football players. Our model approach is tested using 40 attributes from EA Sports' FIFA video game series system, corresponding to 7705 European players. Clustering results reveal a clear distinction among different performance indicators, representing four different roles in the team. Players were labeled according to these roles and a gradient tree boosting model was used for ranking attributes regarding to its importance. We found that the dribbling skill is the most discriminating variable among the different clustered players’ profiles. Resumen En las últimas décadas se ha visto un incremento considerable en la generación y disponibilidad de datos de fútbol, esto se debe fundamentalmente a la popularidad de este deporte así como a los avances tecnológicos realizados en este campo. Los modelos de agrupamiento basados en mixturas Gaussianas representan un enfoque novedoso para explorar y analizar datos de desempeño deportivo. En el presente trabajo, se lleva a cabo una caracterización de jugadores profesionales de fútbol utilizando técnicas de análisis de componentes principales y agrupamiento basados en mixturas Gaussianas. El modelo presentado es comprobado utilizando datos del sistema de videojuegos FIFA de EA Sports, dichos datos representan 40 atributos correspondientes a 7705 futbolistas europeos. Los resultados del agrupamiento revelan una clara distinción entre algunos indicadores de desempeño, los cuales corresponden a cuatro roles diferentes en el equipo. Consecuentemente, los
Institute of Scientific and Technical Information of China (English)
肖涵; 李友荣; 吕勇
2011-01-01
In order to overcome the shortcoming of recurrence plot that can only supply the qualitative analysis to signals, the recurrence quantification analysis is used to analysis different fault modes gear's vibration signal. The gear fault pattern recognition method that combined the gaussian mixture model with the feature vector that consists of determinism and laminarity is proposed. Based on the signals that acquired form gear fault experiment table, the proposed method is compared with RBF artificial neural network classification method by Re-substitution test, Jackknife test and Independent data set test respectively. The classification results show that the higher discrimination can be achieved by the proposed method.%针对递归图只能对信号进行定性分析,不利于其深入应用的缺点,应用递归定量分析方法对各种故障模式振动信号进行定量分析.采用确定率和层流率组成齿轮故障识别的特征向量,并结合高斯混合模型实现齿轮故障模式识别.以齿轮故障实验台上所测取的实验数据为对象,分别采用Re-substitution检验法,Jackknife检验法和Independent dataset检验法对提出的方法和RBF人工神经网络分类算法进行检验.结果表明,递归定量分析与高斯混合模型相结合应用于齿轮故障模式识别具有更高的识别率.
Music Emotion Four Classification Research Based on Gaussian Mixture Model%基于高斯混合模型的音乐情绪四分类研究
Institute of Scientific and Technical Information of China (English)
陆阳; 郭滨; 白雪梅
2015-01-01
针对音乐情感复杂难以归类的问题,提出了一种在四分类坐标下建立高斯混合模型进行音乐信号归类的研究方法.在建立模型的基础上,创新地为表示情绪特性的轴两端建立模型使其转换成二层分类器进行加权判别.结果表明,为表示情绪特性的轴建立模型且权值分配在0.7和0.3的条件下,音乐的分类工作可以取得最优结果,其结果明显优于直接为每类情绪建立模型的结果.%For the problem of music emotional complexity and difficult to categorize, we proposed a method to estab-lish Gaussian mixture models in four classifications. On the basis of establish models, we innovated established GMM for shaft at both ends of the emotional model and converted it into two-layer weighted classifier discrimination. The re-sults shows that the GMM for shaft models and weight distribution under the condition of 0.7 and 0.3, the musical work can obtain the best classification result, and the result is better than the result of directly establish models for each type of emotion.
Two-Component Multi-Parameter Time-Frequency Electromagnetics
Institute of Scientific and Technical Information of China (English)
HuangZhou; DongWeibin; HeTiezhi
2003-01-01
The two-component multi-parameter time-frequency electromagnetic method, used for the development of oilfields,makes use of both the traditional individual conductivity parameters of oil-producing layers and the dispersion information of the conductivity, i.e., the induced polarization parameter. The frequency-domain dispersion data is used to delineate the contacts between oil and water and the time domain dBz/dt component is used to estimate the depths to the un-known reservoirs so as to offer significant data in many aspects for oil exploration and detection.
A polaritonic two-component Bose-Hubbard model
Energy Technology Data Exchange (ETDEWEB)
Hartmann, M J; Brandao, F G S L; Plenio, M B [Institute for Mathematical Sciences, Imperial College London, 53 Exhibition Road, SW7 2PE (United Kingdom)], E-mail: m.hartmann@imperial.ac.uk
2008-03-15
We demonstrate that polaritons in an array of interacting micro-cavities with strong atom-photon coupling can form a two-component Bose-Hubbard model in which both polariton species are protected against spontaneous emission as their atomic part is stored in two ground states of the atoms. The parameters of the effective model can be tuned via the driving strength of external lasers and include attractive and repulsive polariton interactions. We also describe a method to measure the number statistics in one cavity for each polariton species independently.
Two component micro injection moulding for moulded interconnect devices
DEFF Research Database (Denmark)
Islam, Aminul
2008-01-01
Moulded interconnect devices (MIDs) contain huge possibilities for many applications in micro electro-mechanical-systems because of their capability of reducing the number of components, process steps and finally in miniaturization of the product. Among the available MID process chains, two...... and a reasonable adhesion between them. • Selective metallization of the two component plastic part (coating one polymer with metal and leaving the other one uncoated) To overcome these two main issues in MID fabrication for micro applications, the current Ph.D. project explores the technical difficulties...
Interaction potentials and thermodynamic properties of two component semiclassical plasma
Energy Technology Data Exchange (ETDEWEB)
Ramazanov, T. S.; Moldabekov, Zh. A.; Ismagambetova, T. N. [Al-Farabi Kazakh National University, IETP, 71 al-Farabi Av., Almaty 050040 (Kazakhstan); Gabdullin, M. T. [Al-Farabi Kazakh National University, NNLOT, 71 al-Farabi Av., Almaty 050040 (Kazakhstan)
2014-01-15
In this paper, the effective interaction potential in two component semiclassical plasma, taking into account the long-range screening and the quantum-mechanical diffraction effects at short distances, is obtained on the basis of dielectric response function method. The structural properties of the semiclassical plasma are considered. The thermodynamic characteristics (the internal energy and the equation of state) are calculated using two methods: the method of effective potentials and the method of micropotentials with screening effect taken into account by the Ornstein-Zernike equation in the HNC approximation.
Two component micro injection molding for MID fabrication
DEFF Research Database (Denmark)
Islam, Mohammad Aminul; Hansen, Hans Nørgaard; Tang, Peter Torben
2009-01-01
Molded Interconnect Devices (MIDs) are plastic substrates with electrical infrastructure. The fabrication of MIDs is usually based on injection molding and different process chains may be identified from this starting point. The use of MIDs has been driven primarily by the automotive sector......, but recently the medical sector seems more and more interested. In particular the possibility of miniaturization of 3D components with electrical infrastructure is attractive. The paper describes possible manufacturing routes and challenges of miniaturized MIDs based on two component micro injection molding...
Statistical Compressive Sensing of Gaussian Mixture Models
2010-10-01
the algorithm iterates [18] (refer to [18] Sec. 2 for more details). The dictionary for conventional CS is learned with K- SVD [1] from 720,000 image...framework for solving inverse problems. VII. REFERENCES [1] M. Aharon, M. Elad, and A. Bruckstein. K- SVD : An algorithm for designing overcomplete...In Proc. ICCV, 2001. [16] M. Talagrand. A new look at independence. Ann. Prob., 24:1, 1996. [17] G. Yu, S. Mallat, and E. Bacry. Audio denoising by
Graphene Oxide: A One- versus Two-Component Material.
Naumov, Anton; Grote, Fabian; Overgaard, Marc; Roth, Alexandra; Halbig, Christian E; Nørgaard, Kasper; Guldi, Dirk M; Eigler, Siegfried
2016-09-14
The structure of graphene oxide (GO) is a matter of discussion. While established GO models are based on functional groups attached to the carbon framework, another frequently used model claims that GO consists of two components, a slightly oxidized graphene core and highly oxidized molecular species, oxidative debris (OD), adsorbed on it. Those adsorbents are claimed to be the origin for optical properties of GO. Here, we examine this model by preparing GO with a low degree of functionalization, combining it with OD and studying the optical properties of both components and their combination in an artificial two-component system. The analyses of absorption and emission spectra as well as lifetime measurements reveal that properties of the combined system are distinctly different from those of GO. That confirms structural models of GO as a separate oxygenated hexagonal carbon framework with optical properties governed by its internal structure rather than the presence of OD. Understanding the structure of GO allows further reliable interpretation of its optical and electronic properties and enables controlled processing of GO.
Evolution of two-component signal transduction systems.
Capra, Emily J; Laub, Michael T
2012-01-01
To exist in a wide range of environmental niches, bacteria must sense and respond to a variety of external signals. A primary means by which this occurs is through two-component signal transduction pathways, typically composed of a sensor histidine kinase that receives the input stimuli and then phosphorylates a response regulator that effects an appropriate change in cellular physiology. Histidine kinases and response regulators have an intrinsic modularity that separates signal input, phosphotransfer, and output response; this modularity has allowed bacteria to dramatically expand and diversify their signaling capabilities. Recent work has begun to reveal the molecular basis by which two-component proteins evolve. How and why do orthologous signaling proteins diverge? How do cells gain new pathways and recognize new signals? What changes are needed to insulate a new pathway from existing pathways? What constraints are there on gene duplication and lateral gene transfer? Here, we review progress made in answering these questions, highlighting how the integration of genome sequence data with experimental studies is providing major new insights.
The Evolution of Two-Component Signal Transduction Systems
Capra, Emily J.; Laub, Michael T.
2014-01-01
To exist in a wide range of environmental niches, bacteria must sense and respond to a myriad of external signals. A primary means by which this occurs is through two-component signal transduction pathways, typically comprised of a histidine kinase that receives the input stimuli and a response regulator that effects an appropriate change in cellular physiology. Histidine kinases and response regulators have an intrinsic modularity that separates signal input, phosphotransfer, and output response; this modularity has allowed bacteria to dramatically expand and diversify their signaling capabilities. Recent work has begun to reveal the molecular basis by which two-component proteins evolve. How and why do orthologous signaling proteins diverge? How do cells gain new pathways and recognize new signals? What changes are needed to insulate a new pathway from existing pathways? What constraints are there on gene duplication and lateral gene transfer? Here, we review progress made in answering these questions, highlighting how the integration of genome sequence data with experimental studies is providing major new insights. PMID:22746333
Energy Technology Data Exchange (ETDEWEB)
Hoejstrup, J. [NEG Micon Project Development A/S, Randers (Denmark); Hansen, K.S. [Denmarks Technical Univ., Dept. of Energy Engineering, Lyngby (Denmark); Pedersen, B.J. [VESTAS Wind Systems A/S, Lem (Denmark); Nielsen, M. [Risoe National Lab., Wind Energy and Atmospheric Physics, Roskilde (Denmark)
1999-03-01
The pdf`s of atmospheric turbulence have somewhat wider tails than a Gaussian, especially regarding accelerations, whereas velocities are close to Gaussian. This behaviour is being investigated using data from a large WEB-database in order to quantify the amount of non-Gaussianity. Models for non-Gaussian turbulence have been developed, by which artificial turbulence can be generated with specified distributions, spectra and cross-correlations. The artificial time series will then be used in load models and the resulting loads in the Gaussian and the non-Gaussian cases will be compared. (au)
Two-component systems and toxinogenesis regulation in Clostridium botulinum.
Connan, Chloé; Popoff, Michel R
2015-05-01
Botulinum neurotoxins (BoNTs) are the most potent toxins ever known. They are mostly produced by Clostridium botulinum but also by other clostridia. BoNTs associate with non-toxic proteins (ANTPs) to form complexes of various sizes. Toxin production is highly regulated through complex networks of regulatory systems involving an alternative sigma factor, BotR, and at least 6 recently described two-component systems (TCSs). TCSs allow bacteria to sense environmental changes and to respond to various stimuli by regulating the expression of specific genes at a transcriptional level. Several environmental stimuli have been identified to positively or negatively regulate toxin synthesis; however, the link between environmental stimuli and TCSs is still elusive. This review aims to highlight the role of TCSs as a central point in the regulation of toxin production in C. botulinum.
Exact two-component relativistic energy band theory and application
Energy Technology Data Exchange (ETDEWEB)
Zhao, Rundong; Zhang, Yong; Xiao, Yunlong; Liu, Wenjian, E-mail: liuwj@pku.edu.cn [Beijing National Laboratory for Molecular Sciences, Institute of Theoretical and Computational Chemistry, State Key Laboratory of Rare Earth Materials Chemistry and Applications, College of Chemistry and Molecular Engineering, and Center for Computational Science and Engineering, Peking University, Beijing 100871 (China)
2016-01-28
An exact two-component (X2C) relativistic density functional theory in terms of atom-centered basis functions is proposed for relativistic calculations of band structures and structural properties of periodic systems containing heavy elements. Due to finite radial extensions of the local basis functions, the periodic calculation is very much the same as a molecular calculation, except only for an Ewald summation for the Coulomb potential of fluctuating periodic monopoles. For comparison, the nonrelativistic and spin-free X2C counterparts are also implemented in parallel. As a first and pilot application, the band gaps, lattice constants, cohesive energies, and bulk moduli of AgX (X = Cl, Br, I) are calculated to compare with other theoretical results.
Dynamics of two-component membranes surrounded by viscoelastic media.
Komura, Shigeyuki; Yasuda, Kento; Okamoto, Ryuichi
2015-11-01
We discuss the dynamics of two-component fluid membranes which are surrounded by viscoelastic media. We assume that membrane-embedded proteins can diffuse laterally and induce a local membrane curvature. The mean squared displacement of a tagged membrane segment is obtained as a generalized Einstein relation. When the elasticity of the surrounding media obeys a power-law behavior in frequency, an anomalous diffusion of the membrane segment is predicted. We also consider the situation where the proteins generate active non-equilibrium forces. The generalized Einstein relation is further modified by an effective temperature that depends on the force dipole energy. The obtained generalized Einstein relations are useful for membrane microrheology experiments.
Two-component jet simulations: Combining analytical and numerical approaches
Matsakos, T; Trussoni, E; Tsinganos, K; Vlahakis, N; Sauty, C; Mignone, A
2009-01-01
Recent observations as well as theoretical studies of YSO jets suggest the presence of two steady components: a disk wind type outflow needed to explain the observed high mass loss rates and a stellar wind type outflow probably accounting for the observed stellar spin down. In this framework, we construct numerical two-component jet models by properly mixing an analytical disk wind solution with a complementary analytically derived stellar outflow. Their combination is controlled by both spatial and temporal parameters, in order to address different physical conditions and time variable features. We study the temporal evolution and the interaction of the two jet components on both small and large scales. The simulations reach steady state configurations close to the initial solutions. Although time variability is not found to considerably affect the dynamics, flow fluctuations generate condensations, whose large scale structures have a strong resemblance to observed YSO jet knots.
Exact two-component relativistic energy band theory and application.
Zhao, Rundong; Zhang, Yong; Xiao, Yunlong; Liu, Wenjian
2016-01-28
An exact two-component (X2C) relativistic density functional theory in terms of atom-centered basis functions is proposed for relativistic calculations of band structures and structural properties of periodic systems containing heavy elements. Due to finite radial extensions of the local basis functions, the periodic calculation is very much the same as a molecular calculation, except only for an Ewald summation for the Coulomb potential of fluctuating periodic monopoles. For comparison, the nonrelativistic and spin-free X2C counterparts are also implemented in parallel. As a first and pilot application, the band gaps, lattice constants, cohesive energies, and bulk moduli of AgX (X = Cl, Br, I) are calculated to compare with other theoretical results.
Recent advances in description of few two-component fermions
Kartavtsev, O I
2012-01-01
Overview of the recent advances in description of the few two-component fermions is presented. The zero-range interaction limit is generally considered to discuss the principal aspects of the few-body dynamics. Significant attention is paid to detailed description of two identical fermions of mass $m$ and a distinct particle of mass $m_1$; two universal $L^P = 1^-$ bound states arise for mass ratio $m/m_1$ increasing up to the critical value $\\mu_c \\approx 13.607$, beyond which the Efimov effect takes place. The topics considered include rigorous treatment of the few-fermion problem in the zero-range interaction limit, low-dimensional results, the four-body energy spectrum, crossover of the energy spectra for $m/m_1$ near the critical value $\\mu_c $, and properties of potential-dependent states. At last, enlisted are the problems, whose solution is in due course.
Molecular Mechanisms of Two-Component Signal Transduction.
Zschiedrich, Christopher P; Keidel, Victoria; Szurmant, Hendrik
2016-09-25
Two-component systems (TCS) comprising sensor histidine kinases and response regulator proteins are among the most important players in bacterial and archaeal signal transduction and also occur in reduced numbers in some eukaryotic organisms. Given their importance to cellular survival, virulence, and cellular development, these systems are among the most scrutinized bacterial proteins. In the recent years, a flurry of bioinformatics, genetic, biochemical, and structural studies have provided detailed insights into many molecular mechanisms that underlie the detection of signals and the generation of the appropriate response by TCS. Importantly, it has become clear that there is significant diversity in the mechanisms employed by individual systems. This review discusses the current knowledge on common themes and divergences from the paradigm of TCS signaling. An emphasis is on the information gained by a flurry of recent structural and bioinformatics studies.
Bond strength of two component injection moulded MID
DEFF Research Database (Denmark)
Islam, Mohammad Aminul; Hansen, Hans Nørgaard; Tang, Peter Torben
2006-01-01
Most products of the future will require industrially adapted, cost effective production processes and on this issue two-component (2K) injection moulding is a potential candidate for MID manufacturing. MID based on 2k injection moulded plastic part with selectively metallised circuit tracks allows...... the integration of electrical and mechanical functionalities in a real 3D structure. If 2k injection moulding is applied with two polymers, of which one is plateable and the other is not, it will be possible to make 3D electrical structures directly on the component. To be applicable in the real engineering field...... the two different plastic materials in the MID structure require good bonding between them. This paper finds suitable combinations of materials for MIDs from both bond strength and metallisation view-point. Plastic parts were made by two-shot injection moulding and the effects of some important process...
Efficient two-component relativistic method for large systems
Energy Technology Data Exchange (ETDEWEB)
Nakai, Hiromi [Department of Chemitsry and Biochemistry, School of Advanced Science and Engineering, Waseda University, Tokyo 169-8555 (Japan); Research Institute for Science and Engineering, Waseda University, Tokyo 169-8555 (Japan); CREST, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Elements Strategy Initiative for Catalysts and Batteries (ESICB), Kyoto University, Katsura, Kyoto 615-8520 (Japan)
2015-12-31
This paper reviews a series of theoretical studies to develop efficient two-component (2c) relativistic method for large systems by the author’s group. The basic theory is the infinite-order Douglas-Kroll-Hess (IODKH) method for many-electron Dirac-Coulomb Hamiltonian. The local unitary transformation (LUT) scheme can effectively produce the 2c relativistic Hamiltonian, and the divide-and-conquer (DC) method can achieve linear-scaling of Hartree-Fock and electron correlation methods. The frozen core potential (FCP) theoretically connects model potential calculations with the all-electron ones. The accompanying coordinate expansion with a transfer recurrence relation (ACE-TRR) scheme accelerates the computations of electron repulsion integrals with high angular momenta and long contractions.
No electrostatic supersolitons in two-component plasmas
Energy Technology Data Exchange (ETDEWEB)
Verheest, Frank, E-mail: frank.verheest@ugent.be [Sterrenkundig Observatorium, Universiteit Gent, Krijgslaan 281, B–9000 Gent (Belgium); School of Chemistry and Physics, University of KwaZulu-Natal, Durban 4000 (South Africa); Lakhina, Gurbax S., E-mail: lakhina@iigm.iigs.res.in [Indian Institute of Geomagnetism, New Panvel (W), Navi Mumbai (India); Hellberg, Manfred A., E-mail: hellberg@ukzn.ac.za [School of Chemistry and Physics, University of KwaZulu-Natal, Durban 4000 (South Africa)
2014-06-15
The concept of acoustic supersolitons was introduced for a very specific plasma with five constituents, and discussed only for a single set of plasma parameters. Supersolitons are characterized by having subsidiary extrema on the sides of a typical bipolar electric field signature, or by association with a root beyond double layers in the fully nonlinear Sagdeev pseudopotential description. It was subsequently found that supersolitons could exist in several plasma models having three constituent species, rather than four or five. In the present paper, it is proved that standard two-component plasma models cannot generate supersolitons, by recalling and extending results already in the literature, and by establishing the necessary properties of a more recent model.
Budding Transition of Asymmetric Two-component Lipid Domains
Wolff, Jean; Andelman, David
2016-01-01
We propose a model that accounts for the budding transition of asymmetric two-component lipid domains, where the two monolayers (leaflets) have different average compositions controlled by independent chemical potentials. Assuming a coupling between the local curvature and local lipid composition in each of the leaflets, we discuss the morphology and thermodynamic behavior of asymmetric lipid domains. The membrane free-energy contains three contributions: the bending energy, the line tension, and a Landau free-energy for a lateral phase separation. Within a mean-field treatment, we obtain various phase diagrams containing fully budded, dimpled, and flat states as a function of the two leaflet compositions. The global phase behavior is analyzed, and depending on system parameters, the phase diagrams include one-phase, two-phase and three-phase regions. In particular, we predict various phase coexistence regions between different morphologies of domains, which may be observed in multi-component membranes or ves...
The mechanism of signal transduction by two-component systems.
Casino, Patricia; Rubio, Vicente; Marina, Alberto
2010-12-01
Two-component systems, composed of a homodimeric histidine kinase (HK) and a response regulator (RR), are major signal transduction devices in bacteria. Typically the signal triggers HK autophosphorylation at one His residue, followed by phosphoryl transfer from the phospho-His to an Asp residue in the RR. Signal extinction frequently involves phospho-RR dephosphorylation by a phosphatase activity of the HK. Our understanding of these reactions and of the determinants of partner specificity among HK-RR couples has been greatly increased by recent crystal structures and biochemical experiments on HK-RR complexes. Cis-autophosphorylation (one subunit phosphorylates itself) occurs in some HKs while trans-autophosphorylation takes place in others. We review and integrate this new information, discuss the mechanism of the three reactions and propose a model for transmembrane signaling by these systems. Copyright © 2010 Elsevier Ltd. All rights reserved.
Determinants of specificity in two-component signal transduction.
Podgornaia, Anna I; Laub, Michael T
2013-04-01
Maintaining the faithful flow of information through signal transduction pathways is critical to the survival and proliferation of organisms. This problem is particularly challenging as many signaling proteins are part of large, paralogous families that are highly similar at the sequence and structural levels, increasing the risk of unwanted cross-talk. To detect environmental signals and process information, bacteria rely heavily on two-component signaling systems comprised of sensor histidine kinases and their cognate response regulators. Although most species encode dozens of these signaling pathways, there is relatively little cross-talk, indicating that individual pathways are well insulated and highly specific. Here, we review the molecular mechanisms that enforce this specificity. Further, we highlight recent studies that have revealed how these mechanisms evolve to accommodate the introduction of new pathways by gene duplication. Copyright © 2013 Elsevier Ltd. All rights reserved.
Rewiring two-component signal transduction with small RNAs.
Göpel, Yvonne; Görke, Boris
2012-04-01
Bacterial two-component systems (TCSs) and small regulatory RNAs (sRNAs) form densely interconnected networks that integrate and transduce information from the environment into fine-tuned changes of gene expression. Many TCSs control target genes indirectly through regulation of sRNAs, which in turn regulate gene expression by base-pairing with mRNAs or targeting a protein. Conversely, sRNAs may control TCS synthesis, thereby recruiting the TCS regulon to other regulatory networks. Several TCSs control expression of multiple homologous sRNAs providing the regulatory networks with further flexibility. These sRNAs act redundantly, additively or hierarchically on targets. The regulatory speed of sRNAs and their unique features in gene regulation make them ideal players extending the flexibility, dynamic range or timing of TCS signaling. Copyright © 2011 Elsevier Ltd. All rights reserved.
Auxiliary phosphatases in two-component signal transduction.
Silversmith, Ruth E
2010-04-01
Signal termination in two-component systems occurs by loss of the phosphoryl group from the response regulator protein. This review explores our current understanding of the structures, catalytic mechanisms and means of regulation of the known families of phosphatases that catalyze response regulator dephosphorylation. The CheZ and CheC/CheX/FliY families, despite different overall structures, employ identical catalytic strategies using an amide side chain to orient a water molecule for in-line attack of the aspartyl phosphate. Spo0E phosphatases contain sequence and structural features that suggest a strategy similar to the chemotaxis phosphatases but the mechanism used by the Rap phosphatases is not yet elucidated. Identification of features shared by phosphatase families may aid in the identification of currently unrecognized classes of response regulator phosphatases. Copyright 2010 Elsevier Ltd. All rights reserved.
How insects overcome two-component plant chemical defence
DEFF Research Database (Denmark)
Pentzold, Stefan; Zagrobelny, Mika; Rook, Frederik;
2014-01-01
Insect herbivory is often restricted by glucosylated plant chemical defence compounds that are activated by plant β-glucosidases to release toxic aglucones upon plant tissue damage. Such two-component plant defences are widespread in the plant kingdom and examples of these classes of compounds...... are alkaloid, benzoxazinoid, cyanogenic and iridoid glucosides as well as glucosinolates and salicinoids. Conversely, many insects have evolved a diversity of counteradaptations to overcome this type of constitutive chemical defence. Here we discuss that such counter-adaptations occur at different time points......-component chemical defence. These adaptations include host plant choice, non-disruptive feeding guilds and various physiological adaptations as well as metabolic enzymatic strategies of the insect’s digestive system. Furthermore, insect adaptations often act in combination, may exist in both generalists...
Parallel TREE code for two-component ultracold plasma analysis
Jeon, Byoungseon; Kress, Joel D.; Collins, Lee A.; Grønbech-Jensen, Niels
2008-02-01
The TREE method has been widely used for long-range interaction N-body problems. We have developed a parallel TREE code for two-component classical plasmas with open boundary conditions and highly non-uniform charge distributions. The program efficiently handles millions of particles evolved over long relaxation times requiring millions of time steps. Appropriate domain decomposition and dynamic data management were employed, and large-scale parallel processing was achieved using an intermediate level of granularity of domain decomposition and ghost TREE communication. Even though the computational load is not fully distributed in fine grains, high parallel efficiency was achieved for ultracold plasma systems of charged particles. As an application, we performed simulations of an ultracold neutral plasma with a half million particles and a half million time steps. For the long temporal trajectories of relaxation between heavy ions and light electrons, large configurations of ultracold plasmas can now be investigated, which was not possible in past studies.
Institute of Scientific and Technical Information of China (English)
张虎; 方华; 李春贵
2014-01-01
There are often the cases in road video surveillance systems that the vehicles are slowly moving or in short stay.In view of the problems that the background subtraction method of traditional Gaussian mixture model is sensitive to abrupt changes in environment and has information loss on slow moving target,we propose an improved adaptive vehicle detection algorithm.First,in order to restrain the foreground of slow movement to be trained to the background,the present pixel-values are classified before updating the parameters,and the models are set different replacement rates according to classification results.Secondly,for removing the interference of environmental changes,a metric factor that tracks environmental changes is introduced to realise the adaptive switch between the background subtraction and the inter-frame difference algorithm when abrupt environmental change occurs.Finally the more accurate object is gotten by ecological filtering.Experiments show that this algorithm can get better detection effect for moving vehicles in daytime real-time traffic video.%道路视频监控中经常存在车辆缓慢运动或短暂停留的情况。针对传统混合高斯模型背景减除法对环境突变敏感和对缓慢运动目标丢失信息的问题，提出一种改进的自适应车辆检测方法。首先，在参数更新前对像素值分类并根据分类结果设置模型更新率，抑制缓慢运动前景被训练成背景；引入一个跟踪环境变化的度量因子，当环境突变时实现背景减除和帧差法的自适应切换，滤除环境变化的干扰；最后通过生态学滤波得到准确的运动目标。实验表明，该算法对白天实时路况视频中的运动车辆具有较好的检测效果。
DEFF Research Database (Denmark)
Højstrup, Jørgen; Hansen, Kurt S.; Pedersen, Bo Juul;
1999-01-01
The pdf's of atmosperic turbulence have somewhat wider tails than a Gaussian, especially regarding accelerations, whereas velocities are close to Gaussian. This behaviour has been investigated using data from a large WEB-database in order to quantify the amount of non-gaussianity. Models for non-...
Implementation of Two Component Advective Flow Solution in XSPEC
Debnath, Dipak; Mondal, Santanu
2014-01-01
Spectral and Temporal properties of black hole candidates can be explained reasonably well using Chakrabarti-Titarchuk solution of two component advective flow (TCAF). This model requires two accretion rates, namely, the Keplerian disk accretion rate and the halo accretion rate, the latter being composed of a sub-Keplerian, low angular momentum flow which may or may not develop a shock. In this solution, the relevant parameter is the relative importance of the halo (which creates the Compton cloud region) rate with respect to the Keplerian disk rate (soft photon source). Though this model has been used earlier to manually fit data of several black hole candidates quite satisfactorily, for the first time, we made it user friendly by implementing it into XSPEC software of GSFC/NASA. This enables any user to extract physical parameters of the accretion flows, such as two accretion rates, the shock location, the shock strength etc. for any black hole candidate. We provide some examples of fitting a few cases usin...
Dynamical principles of two-component genetic oscillators.
Directory of Open Access Journals (Sweden)
Raúl Guantes
2006-03-01
Full Text Available Genetic oscillators based on the interaction of a small set of molecular components have been shown to be involved in the regulation of the cell cycle, the circadian rhythms, or the response of several signaling pathways. Uncovering the functional properties of such oscillators then becomes important for the understanding of these cellular processes and for the characterization of fundamental properties of more complex clocks. Here, we show how the dynamics of a minimal two-component oscillator is drastically affected by its genetic implementation. We consider a repressor and activator element combined in a simple logical motif. While activation is always exerted at the transcriptional level, repression is alternatively operating at the transcriptional (Design I or post-translational (Design II level. These designs display differences on basic oscillatory features and on their behavior with respect to molecular noise or entrainment by periodic signals. In particular, Design I induces oscillations with large activator amplitudes and arbitrarily small frequencies, and acts as an "integrator" of external stimuli, while Design II shows emergence of oscillations with finite, and less variable, frequencies and smaller amplitudes, and detects better frequency-encoded signals ("resonator". Similar types of stimulus response are observed in neurons, and thus this work enables us to connect very different biological contexts. These dynamical principles are relevant for the characterization of the physiological roles of simple oscillator motifs, the understanding of core machineries of complex clocks, and the bio-engineering of synthetic oscillatory circuits.
Hamiltonian of a homogeneous two-component plasma.
Essén, Hanno; Nordmark, A
2004-03-01
The Hamiltonian of one- and two-component plasmas is calculated in the negligible radiation Darwin approximation. Since the Hamiltonian is the phase space energy of the system its form indicates, according to statistical mechanics, the nature of the thermal equilibrium that plasmas strive to attain. The main issue is the length scale of the magnetic interaction energy. In the past a screening length lambda=1/square root of r(e)n], with n number density and r(e) classical electron radius, has been derived. We address the question whether the corresponding longer screening range obtained from the classical proton radius is physically relevant and the answer is affirmative. Starting from the Darwin Lagrangian it is nontrivial to find the Darwin Hamiltonian of a macroscopic system. For a homogeneous system we resolve the difficulty by temporarily approximating the particle number density by a smooth constant density. This leads to Yukawa-type screened vector potential. The nontrivial problem of finding the corresponding, divergence free, Coulomb gauge version is solved.
A minimal model for two-component dark matter
Energy Technology Data Exchange (ETDEWEB)
Esch, Sonja; Klasen, Michael; Yaguna, Carlos E. [Institut fuer theoretische Physik, Universitaet Muenster, Wilhelm-Klemm-Strasse 9,D-48149 Muenster (Germany)
2015-07-01
We propose and study a new minimal model for two-component dark matter. The model contains only three additional fields, one fermion and two scalars, all singlets under the Standard Model gauge group. Two of these fields, one fermion and one scalar, are odd under a Z{sub 2} symmetry that renders them simultaneously stable. Thus, both particles contribute to the observed dark matter density. This model resembles the union of the singlet scalar and the singlet fermionic models but it contains some new features of its own. We analyze in some detail its dark matter phenomenology. Regarding the relic density, the main novelty is the possible annihilation of one dark matter particle into the other, which can affect the predicted relic density in a significant way. Regarding dark matter detection, we identify a new contribution that can lead either to an enhancement or to a suppression of the spin-independent cross section for the scalar dark matter particle. Finally, we define a set of five benchmarks models compatible with all present bounds and examine their direct detection prospects at planned experiments. A generic feature of this model is that both particles give rise to observable signals in 1-ton direct detection experiments. In fact, such experiments will be able to probe even a subdominant dark matter component at the percent level.
A minimal model for two-component dark matter
Esch, Sonja; Yaguna, Carlos E
2014-01-01
We propose and study a new minimal model for two-component dark matter. The model contains only three additional fields, one fermion and two scalars, all singlets under the Standard Model gauge group. Two of these fields, one fermion and one scalar, are odd under a $Z_2$ symmetry that renders them simultaneously stable. Thus, both particles contribute to the observed dark matter density. This model resembles the union of the singlet scalar and the singlet fermionic models but it contains some new features of its own. We analyze in some detail its dark matter phenomenology. Regarding the relic density, the main novelty is the possible annihilation of one dark matter particle into the other, which can affect the predicted relic density in a significant way. Regarding dark matter detection, we identify a new contribution that can lead either to an enhancement or to a suppression of the spin-independent cross section for the scalar dark matter particle. Finally, we define a set of five benchmarks models compatibl...
A minimal model for two-component dark matter
Esch, Sonja; Klasen, Michael; Yaguna, Carlos E.
2014-09-01
We propose and study a new minimal model for two-component dark matter. The model contains only three additional fields, one fermion and two scalars, all singlets under the Standard Model gauge group. Two of these fields, one fermion and one scalar, are odd under a Z 2 symmetry that renders them simultaneously stable. Thus, both particles contribute to the observed dark matter density. This model resembles the union of the singlet scalar and the singlet fermionic models but it contains some new features of its own. We analyze in some detail its dark matter phenomenology. Regarding the relic density, the main novelty is the possible annihilation of one dark matter particle into the other, which can affect the predicted relic density in a significant way. Regarding dark matter detection, we identify a new contribution that can lead either to an enhancement or to a suppression of the spin-independent cross section for the scalar dark matter particle. Finally, we define a set of five benchmarks models compatible with all present bounds and examine their direct detection prospects at planned experiments. A generic feature of this model is that both particles give rise to observable signals in 1-ton direct detection experiments. In fact, such experiments will be able to probe even a subdominant dark matter component at the percent level.
Two-component perfect fluid in FRW universe
,
2012-01-01
We propose the cosmological model which allows to describe on equal footing the evolution of matter in the universe on the time interval from the inflation till the domination of dark energy. The matter is considered as a two-component perfect fluid imitated by homogeneous scalar fields between which there is energy exchange. Dark energy is represented by the cosmological constant, which is supposed invariable during the whole evolution of the universe. The matter changes its equation of state with time, so that the era of radiation domination in the early universe smoothly passes into the era of a pressureless gas, which then passes into the late-time epoch, when the matter is represented by a gas of low-velocity cosmic strings. The inflationary phase is described as an analytic continuation of the energy density in the very early universe into the region of small negative values of the parameter which characterizes typical time of energy transfer from one matter component to another. The Hubble expansion ra...
Optimality of Gaussian discord.
Pirandola, Stefano; Spedalieri, Gaetana; Braunstein, Samuel L; Cerf, Nicolas J; Lloyd, Seth
2014-10-03
In this Letter we exploit the recently solved conjecture on the bosonic minimum output entropy to show the optimality of Gaussian discord, so that the computation of quantum discord for bipartite Gaussian states can be restricted to local Gaussian measurements. We prove such optimality for a large family of Gaussian states, including all two-mode squeezed thermal states, which are the most typical Gaussian states realized in experiments. Our family also includes other types of Gaussian states and spans their entire set in a suitable limit where they become Choi matrices of Gaussian channels. As a result, we completely characterize the quantum correlations possessed by some of the most important bosonic states in quantum optics and quantum information.
Two component systems: physiological effect of a third component.
Directory of Open Access Journals (Sweden)
Baldiri Salvado
Full Text Available Signal transduction systems mediate the response and adaptation of organisms to environmental changes. In prokaryotes, this signal transduction is often done through Two Component Systems (TCS. These TCS are phosphotransfer protein cascades, and in their prototypical form they are composed by a kinase that senses the environmental signals (SK and by a response regulator (RR that regulates the cellular response. This basic motif can be modified by the addition of a third protein that interacts either with the SK or the RR in a way that could change the dynamic response of the TCS module. In this work we aim at understanding the effect of such an additional protein (which we call "third component" on the functional properties of a prototypical TCS. To do so we build mathematical models of TCS with alternative designs for their interaction with that third component. These mathematical models are analyzed in order to identify the differences in dynamic behavior inherent to each design, with respect to functionally relevant properties such as sensitivity to changes in either the parameter values or the molecular concentrations, temporal responsiveness, possibility of multiple steady states, or stochastic fluctuations in the system. The differences are then correlated to the physiological requirements that impinge on the functioning of the TCS. This analysis sheds light on both, the dynamic behavior of synthetically designed TCS, and the conditions under which natural selection might favor each of the designs. We find that a third component that modulates SK activity increases the parameter space where a bistable response of the TCS module to signals is possible, if SK is monofunctional, but decreases it when the SK is bifunctional. The presence of a third component that modulates RR activity decreases the parameter space where a bistable response of the TCS module to signals is possible.
The Fractional Virial Potential Energy in Two-Component Systems
Directory of Open Access Journals (Sweden)
Caimmi, R.
2008-12-01
Full Text Available Two-component systems are conceived as macrogases, and the related equation of state is expressed using the virial theorem for subsystems, under the restriction of homeoidally striated density profiles. Explicit calculations are performed for a useful reference case and a few cases of astrophysical interest, both with and without truncation radius. Shallower density profiles are found to yield an equation of state, $phi=phi(y,m$, characterized (for assigned values of the fractional mass, $m=M_j/ M_i$ by the occurrence of two extremum points, a minimum and a maximum, as found in an earlier attempt. Steeper density profiles produce a similar equation of state, which implies that a special value of $m$ is related to a critical curve where the above mentioned extremum points reduce to a single horizontal inflexion point, and curves below the critical one show no extremum points. The similarity of the isofractional mass curves to van der Waals' isothermal curves, suggests the possibility of a phase transition in a bell-shaped region of the $({sf O}yphi$ plane, where the fractional truncation radius along a selected direction is $y=R_j/R_i$, and the fractional virial potential energy is $phi=(E_{ji}_mathrm{vir}/(E_{ij}_mathrm{vir}$. Further investigation is devoted to mass distributions described by Hernquist (1990 density profiles, for which an additional relation can be used to represent a sample of $N=16$ elliptical galaxies (EGs on the $({sf O}yphi$ plane. Even if the evolution of elliptical galaxies and their hosting dark matter (DM haloes, in the light of the model, has been characterized by equal fractional mass, $m$, and equal scaled truncation radius, or concentration, $Xi_u=R_u/r_u^dagger$, $u=i,j$, still it cannot be considered as strictly homologous, due to different values of fractional truncation radii, $y$, or fractional scaling radii, $y^dagger=r_j^dagger/r_i^dagger$, deduced from sample objects.
Gaussian Intrinsic Entanglement
Mišta, Ladislav; Tatham, Richard
2016-12-01
We introduce a cryptographically motivated quantifier of entanglement in bipartite Gaussian systems called Gaussian intrinsic entanglement (GIE). The GIE is defined as the optimized mutual information of a Gaussian distribution of outcomes of measurements on parts of a system, conditioned on the outcomes of a measurement on a purifying subsystem. We show that GIE vanishes only on separable states and exhibits monotonicity under Gaussian local trace-preserving operations and classical communication. In the two-mode case, we compute GIE for all pure states as well as for several important classes of symmetric and asymmetric mixed states. Surprisingly, in all of these cases, GIE is equal to Gaussian Rényi-2 entanglement. As GIE is operationally associated with the secret-key agreement protocol and can be computed for several important classes of states, it offers a compromise between computable and physically meaningful entanglement quantifiers.
CSIR Research Space (South Africa)
Roux, FS
2009-01-01
Full Text Available . Gaussian beams with vortex dipoles CSIR National Laser Centre – p.2/30 Gaussian beam notation Gaussian beam in normalised coordinates: g(u, v, t) = exp ( −u 2 + v2 1− it ) u = xω0 v = yω0 t = zρ ρ = piω20 λ ω0 — 1/e2 beam waist radius; ρ— Rayleigh range ω ω...(z) 0 x z Rayleigh range Beam waist ρ ρ Rayleigh range CSIR National Laser Centre – p.3/30 Gaussian beam Gaussian beam in terms of amplitude and phase g(u, v, t) = exp ( −u 2 + v2 1 + t2 ) exp ( − it(u 2 + v2) 1 + t2 ) Normalised beam radius: √ 1 + t2...
On bosonic non-Gaussian processes: photon-added Gaussian channels
Sabapathy, Krishna Kumar
2016-01-01
We present a framework for systematically studying linear bosonic non-Gaussian channels. Our emphasis is on a class of channels that we call as photon-added Gaussian channels and these are experimentally viable with current quantum-optical technologies. These channels are obtained by extending Gaussian channels with photon addition applied to the environment state (in its respective Stinespring unitary representation) giving rise to a one-parameter family of non-Gaussian channels indexed by photon number $n$ with $n=0$ corresponding to the underlying Gaussian channel. We then derive the corresponding operator-sum representation and observe that these channels are Fock-preserving, i.e., coherence non-generating on incoherent states in the Fock basis. Furthermore, noisy Gaussian channels can be expressed as a convex mixture of these non-Gaussian channels analogous to the Fock basis representation of a thermal state. We then report examples of activation of nonclassicality, using this method of photon-addition, ...
Non-Gaussian operations on bosonic modes of light: Photon-added Gaussian channels
Sabapathy, Krishna Kumar; Winter, Andreas
2017-06-01
We present a framework for studying bosonic non-Gaussian channels of continuous-variable systems. Our emphasis is on a class of channels that we call photon-added Gaussian channels, which are experimentally viable with current quantum-optical technologies. A strong motivation for considering these channels is the fact that it is compulsory to go beyond the Gaussian domain for numerous tasks in continuous-variable quantum information processing such as entanglement distillation from Gaussian states and universal quantum computation. The single-mode photon-added channels we consider are obtained by using two-mode beam splitters and squeezing operators with photon addition applied to the ancilla ports giving rise to families of non-Gaussian channels. For each such channel, we derive its operator-sum representation, indispensable in the present context. We observe that these channels are Fock preserving (coherence nongenerating). We then report two examples of activation using our scheme of photon addition, that of quantum-optical nonclassicality at outputs of channels that would otherwise output only classical states and of both the quantum and private communication capacities, hinting at far-reaching applications for quantum-optical communication. Further, we see that noisy Gaussian channels can be expressed as a convex mixture of these non-Gaussian channels. We also present other physical and information-theoretic properties of these channels.
Gaussian and Non-Gaussian operations on non-Gaussian state: engineering non-Gaussianity
Directory of Open Access Journals (Sweden)
Olivares Stefano
2014-03-01
Full Text Available Multiple photon subtraction applied to a displaced phase-averaged coherent state, which is a non-Gaussian classical state, produces conditional states with a non trivial (positive Glauber-Sudarshan Prepresentation. We theoretically and experimentally demonstrate that, despite its simplicity, this class of conditional states cannot be fully characterized by direct detection of photon numbers. In particular, the non-Gaussianity of the state is a characteristics that must be assessed by phase-sensitive measurements. We also show that the non-Gaussianity of conditional states can be manipulated by choosing suitable conditioning values and composition of phase-averaged states.
Direct molecular dynamics simulation of liquid-solid phase equilibria for two-component plasmas.
Schneider, A S; Hughto, J; Horowitz, C J; Berry, D K
2012-06-01
We determine the liquid-solid phase diagram for carbon-oxygen and oxygen-selenium plasma mixtures using two-phase molecular dynamics simulations. We identify liquid, solid, and interface regions using a bond angle metric. To study finite-size effects, we perform 27,648- and 55,296-ion simulations. To help monitor nonequilibrium effects, we calculate diffusion constants D(i). For the carbon-oxygen system we find that D(O) for oxygen ions in the solid is much smaller than D(C) for carbon ions and that both diffusion constants are 80 or more times smaller than diffusion constants in the liquid phase. There is excellent agreement between our carbon-oxygen phase diagram and that predicted by Medin and Cumming. This suggests that errors from finite-size and nonequilibrium effects are small and that the carbon-oxygen phase diagram is now accurately known. The oxygen-selenium system is a simple two-component model for more complex rapid proton capture nucleosynthesis ash compositions for an accreting neutron star. Diffusion of oxygen, in a predominantly selenium crystal, is remarkably fast, comparable to diffusion in the liquid phase. We find a somewhat lower melting temperature for the oxygen-selenium system than that predicted by Medin and Cumming. This is probably because of electron screening effects.
Adhesion-induced phase behavior of two-component membranes and vesicles.
Rouhiparkouhi, Tahereh; Weikl, Thomas R; Discher, Dennis E; Lipowsky, Reinhard
2013-01-22
The interplay of adhesion and phase separation is studied theoretically for two-component membranes that can phase separate into two fluid phases such as liquid-ordered and liquid-disordered phases. Many adhesion geometries provide two different environments for these membranes and then partition the membranes into two segments that differ in their composition. Examples are provided by adhering vesicles, by hole- or pore-spanning membranes, and by membranes supported by chemically patterned surfaces. Generalizing a lattice model for binary mixtures to these adhesion geometries, we show that the phase behavior of the adhering membranes depends, apart from composition and temperature, on two additional parameters, the area fraction of one membrane segment and the affinity contrast between the two segments. For the generic case of non-vanishing affinity contrast, the adhering membranes undergo two distinct phase transitions and the phase diagrams in the composition/temperature plane have a generic topology that consists of two two-phase coexistence regions separated by an intermediate one-phase region. As a consequence, phase separation and domain formation is predicted to occur separately in each of the two membrane segments but not in both segments simultaneously. Furthermore, adhesion is also predicted to suppress the phase separation process for certain regions of the phase diagrams. These generic features of the adhesion-induced phase behavior are accessible to experiment.
Autonomous Gaussian Decomposition
Lindner, Robert R; Murray, Claire E; Stanimirović, Snežana; Babler, Brian L; Heiles, Carl; Hennebelle, Patrick; Goss, W M; Dickey, John
2014-01-01
We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21cm absorption spectra from the 21cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the HI line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the up...
Broadcasting Correlated Gaussians
Bross, Shraga; Tinguely, Stephan
2007-01-01
We consider the transmission of a bi-variate Gaussian source over a one-to-two power-limited Gaussian broadcast channel. Receiver 1 observes the transmitted signal corrupted by Gaussian noise and wishes to estimate the first component of the source. Receiver 2 observes the transmitted signal in larger Gaussian noise and wishes to estimate the second component. We seek to characterize the pairs of mean squared-error distortions that are simultaneously achievable at the two receivers. Our result is that below a certain SNR-threshold an "uncoded scheme" that sends a linear combination of the source components is optimal. The SNR-theshold can be expressed as a function of the source correlation and the distortion at Receiver 1.
Hammouda, Boualem
2014-01-01
It is common practice to assume that Bragg scattering peaks have Gaussian shape. The Gaussian shape function is used to perform most instrumental smearing corrections. Using Monte Carlo ray tracing simulation, the resolution of a realistic small-angle neutron scattering (SANS) instrument is generated reliably. Including a single-crystal sample with large d-spacing, Bragg peaks are produced. Bragg peaks contain contributions from the resolution function and from spread in the sample structure. Results show that Bragg peaks are Gaussian in the resolution-limited condition (with negligible sample spread) while this is not the case when spread in the sample structure is non-negligible. When sample spread contributes, the exponentially modified Gaussian function is a better account of the Bragg peak shape. This function is characterized by a non-zero third moment (skewness) which makes Bragg peaks asymmetric for broad neutron wavelength spreads. PMID:26601025
Learning conditional Gaussian networks
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....
On Gaussian random supergravity
Bachlechner, Thomas C.
2014-01-01
We study the distribution of metastable vacua and the likelihood of slow roll inflation in high dimensional random landscapes. We consider two examples of landscapes: a Gaussian random potential and an effective supergravity potential defined via a Gaussian random superpotential and a trivial K\\"ahler potential. To examine these landscapes we introduce a random matrix model that describes the correlations between various derivatives and we propose an efficient algorithm that allows for a nume...
Semiparametric Gaussian copula classification
Zhao, Yue; Wegkamp, Marten
2014-01-01
This paper studies the binary classification of two distributions with the same Gaussian copula in high dimensions. Under this semiparametric Gaussian copula setting, we derive an accurate semiparametric estimator of the log density ratio, which leads to our empirical decision rule and a bound on its associated excess risk. Our estimation procedure takes advantage of the potential sparsity as well as the low noise condition in the problem, which allows us to achieve faster convergence rate of...
Directory of Open Access Journals (Sweden)
Youbo Di
2013-01-01
Full Text Available We reported here the gelation behaviors of two-component organogel system based on different acids and aminobenzothiazole derivatives in various organic solvents. Their gelation behaviors in 20 solvents were tested as new organic gelators. It was shown that the molecular skeletons and substituted groups in these compounds played a crucial role in the gelation behavior of the mixtures. Only the binary mixture of 2-aminobenzothiazole and trigonal 1,3,5-benzenetricarboxylic acid with aromatic core could form organogels in ethanol and acetone. Morphological observations reveal that the microstructures of both xerogels showed similar wrinkle-shaped domains composed of sheet-like aggregates with many holes. Spectral studies reveal the hydrogen bonding interaction between the amide of the gelator and lamellar-like structure of the aggregates in both gels. The present investigation is a perspective to provide new clues for the design of new nanomaterials and functional textile materials with special microstructures.
Ferreira, P G; Ferreira, Pedro G.; Magueijo, Joao
1997-01-01
Gaussian cosmic microwave background skies are fully specified by the power spectrum. The conventional method of characterizing non-Gaussian skies is to evaluate higher order moments, the n-point functions and their Fourier transforms. We argue that this method is inefficient, due to the redundancy of information existing in the complete set of moments. In this paper we propose a set of new statistics or non-Gaussian spectra to be extracted out of the angular distribution of the Fourier transform of the temperature anisotropies in the small field limit. These statistics complement the power spectrum and act as localization, shape, and connectedness statistics. They quantify generic non-Gaussian structure, and may be used in more general image processing tasks. We concentrate on a subset of these statistics and argue that while they carry no information in Gaussian theories they may be the best arena for making predictions in some non-Gaussian theories. As examples of applications we consider superposed Gaussi...
Blind source separation based on generalized gaussian model
Institute of Scientific and Technical Information of China (English)
YANG Bin; KONG Wei; ZHOU Yue
2007-01-01
Since in most blind source separation (BSS) algorithms the estimations of probability density function (pdf) of sources are fixed or can only switch between one sup-Gaussian and other sub-Gaussian model,they may not be efficient to separate sources with different distributions. So to solve the problem of pdf mismatch and the separation of hybrid mixture in BSS, the generalized Gaussian model (GGM) is introduced to model the pdf of the sources since it can provide a general structure of univariate distributions. Its great advantage is that only one parameter needs to be determined in modeling the pdf of different sources, so it is less complex than Gaussian mixture model. By using maximum likelihood (ML) approach, the convergence of the proposed algorithm is improved. The computer simulations show that it is more efficient and valid than conventional methods with fixed pdf estimation.
Initial data problems for the two-component Camassa-Holm system
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Xiaohuan Wang
2014-06-01
Full Text Available This article concerns the study of some properties of the two-component Camassa-Holm system. By constructing two sequences of solutions of the two-component Camassa-Holm system, we prove that the solution map of the Cauchy problem of the two-component Camassa-Holm system is not uniformly continuous in $H^s(\\mathbb{R}$, $s>5/2$.
Analytical method for yrast line states in the interacting two-component Bose-Einstein condensate
Institute of Scientific and Technical Information of China (English)
解炳昊; 景辉
2002-01-01
The yrast spectrum for the harmonically trapped two-component Bose-Einstein condensate (BEC), omitting thedifference between the two components, has been studied using an analytical method. The energy eigenstates andeigenvalues for L＝0,1,2,3 are given. We illustrate that there are different eigenstate behaviours between the even Land odd L cases for the two-component BEC in two dimensions. Except for symmetric states, there are antisymmetricstates for the permutation of the two components, which cannot reduce to those in a single condensate case when thevalue of L is odd.
Ultrawide Bandwidth Receiver Based on a Multivariate Generalized Gaussian Distribution
Ahmed, Qasim Zeeshan
2015-04-01
Multivariate generalized Gaussian density (MGGD) is used to approximate the multiple access interference (MAI) and additive white Gaussian noise in pulse-based ultrawide bandwidth (UWB) system. The MGGD probability density function (pdf) is shown to be a better approximation of a UWB system as compared to multivariate Gaussian, multivariate Laplacian and multivariate Gaussian-Laplacian mixture (GLM). The similarity between the simulated and the approximated pdf is measured with the help of modified Kullback-Leibler distance (KLD). It is also shown that MGGD has the smallest KLD as compared to Gaussian, Laplacian and GLM densities. A receiver based on the principles of minimum bit error rate is designed for the MGGD pdf. As the requirement is stringent, the adaptive implementation of the receiver is also carried out in this paper. Training sequence of the desired user is the only requirement when implementing the detector adaptively. © 2002-2012 IEEE.
Deblured Gaussian Blurred Images
Al-amri, Salem Saleh; D, Khamitkar S
2010-01-01
This paper attempts to undertake the study of Restored Gaussian Blurred Images. by using four types of techniques of deblurring image as Wiener filter, Regularized filter, Lucy Richardson deconvlutin algorithm and Blind deconvlution algorithm with an information of the Point Spread Function (PSF) corrupted blurred image with Different values of Size and Alfa and then corrupted by Gaussian noise. The same is applied to the remote sensing image and they are compared with one another, So as to choose the base technique for restored or deblurring image.This paper also attempts to undertake the study of restored Gaussian blurred image with no any information about the Point Spread Function (PSF) by using same four techniques after execute the guess of the PSF, the number of iterations and the weight threshold of it. To choose the base guesses for restored or deblurring image of this techniques.
Generalized Gaussian Error Calculus
Grabe, Michael
2010-01-01
For the first time in 200 years Generalized Gaussian Error Calculus addresses a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing the consequences of random errors alone turned out to be obsolete. As a matter of course, the error calculus to-be, treating random and unknown systematic errors side by side, should ensure the consistency and traceability of physical units, physical constants and physical quantities at large. The generalized Gaussian error calculus considers unknown systematic errors to spawn biased estimators. Beyond, random errors are asked to conform to the idea of what the author calls well-defined measuring conditions. The approach features the properties of a building kit: any overall uncertainty turns out to be the sum of a contribution due to random errors, to be taken from a confidence inter...
Low temperatures shear viscosity of a two-component dipolar Fermi gas with unequal population
Darsheshdar, E.; Yavari, H.; Zangeneh, Z.
2016-07-01
By using the Green's functions method and linear response theory we calculate the shear viscosity of a two-component dipolar Fermi gas with population imbalance (spin polarized) in the low temperatures limit. In the strong-coupling Bose-Einstein condensation (BEC) region where a Feshbach resonance gives rise to tightly bound dimer molecules, a spin-polarized Fermi superfluid reduces to a simple Bose-Fermi mixture of Bose-condensed dimers and the leftover unpaired fermions (atoms). The interactions between dimer-atom, dimer-dimer, and atom-atom take into account to the viscous relaxation time (τη) . By evaluating the self-energies in the ladder approximation we determine the relaxation times due to dimer-atom (τDA) , dimer-dimer (τcDD ,τdDD) , and atom-atom (τAA) interactions. We will show that relaxation rates due to these interactions τDA-1 ,τcDD-1, τdDD-1, and τAA-1 have T2, T4, e - E /kB T (E is the spectrum of the dimer atoms), and T 3 / 2 behavior respectively in the low temperature limit (T → 0) and consequently, the atom-atom interaction plays the dominant role in the shear viscosity in this rang of temperatures. For small polarization (τDA ,τAA ≫τcDD ,τdDD), the low temperatures shear viscosity is determined by contact interaction between dimers and the shear viscosity varies as T-5 which has the same behavior as the viscosity of other superfluid systems such as superfluid neutron stars, and liquid helium.
Two-Component Super AKNS Equations and Their Finite-Dimensional Integrable Super Hamiltonian System
Jing Yu; Jingwei Han
2014-01-01
Starting from a matrix Lie superalgebra, two-component super AKNS system is constructed. By making use of monononlinearization technique of Lax pairs, we find that the obtained two-component super AKNS system is a finite-dimensional integrable super Hamiltonian system. And its Lax representation and $r$ -matrix are also given in this paper.
TASI 2011 lectures notes: two-component fermion notation and supersymmetry
Martin, Stephen P.
2012-01-01
These notes, based on work with Herbi Dreiner and Howie Haber, discuss how to do practical calculations of cross sections and decay rates using two-component fermion notation, as appropriate for supersymmetry and other beyond-the-Standard-Model theories. Included are a list of two-component fermion Feynman rules for the Minimal Supersymmetric Standard Model, and some example calculations.
Relativistic two-component jet evolutions in 2D and 3D
Meliani, Z.; Keppens, R.
2009-01-01
Observations of astrophysical jets and theoretical arguments suggest a transverse stratification with two components induced by intrinsic features of the central engine (accretion disk + black hole). We study two-component jet dynamics for an inner fast low density jet, surrounded by a slower, dense
Two-Component Super AKNS Equations and Their Finite-Dimensional Integrable Super Hamiltonian System
Directory of Open Access Journals (Sweden)
Jing Yu
2014-01-01
Full Text Available Starting from a matrix Lie superalgebra, two-component super AKNS system is constructed. By making use of monononlinearization technique of Lax pairs, we find that the obtained two-component super AKNS system is a finite-dimensional integrable super Hamiltonian system. And its Lax representation and r-matrix are also given in this paper.
The Escherichia coli BarA-UvrY two-component system is a virulence determinant in the urinary tract
Directory of Open Access Journals (Sweden)
Georgellis Dimitris
2006-03-01
Full Text Available Abstract Background The Salmonella enterica BarA-SirA, the Erwinia carotovora ExpS-ExpA, the Vibrio cholerae BarA-VarA and the Pseudomonas spp GacS-GacA all belong to the same orthologous family of two-component systems as the Escherichia coli BarA-UvrY. In the first four species it has been demonstrated that disruption of this two-component system leads to a clear reduction in virulence of the bacteria. Our aim was to determine if the Escherichia coli BarA-UvrY two-component system is connected with virulence using a monkey cystitis model. Results Cystitis was generated in Macaque fascularis monkeys by infecting the bladder with a 1:1 mixture of the uropathogenic Escherichia coli isolate DS17 and a derivative where the uvrY gene had been disrupted with a kanamycin resistance gene. Urine was collected through bladder punctuation at subsequent time intervals and the relative amount of uvrY mutant was determined. This showed that inactivation of the UvrY response regulator leads to a reduced fitness. In similar competitions in culture flasks with Luria Broth (LB the uvrY mutant rather had a higher fitness than the wild type. When the competitions were done in flasks with human urine the uvrY mutant initially had a lower fitness. This was followed by a fluctuation in the level of mutant in the long-term culture, with a pattern that was specific for the individual urines that were tested. Addition of LB to the different urine competition cultures however clearly led to a consistently higher fitness of the uvrY mutant. Conclusion This paper demonstrates that the BarA-UvrY two-component system is a determinant for virulence in a monkey cystitis model. The observed competition profiles strengthen our previous hypothesis that disruption of the BarA-UvrY two-component system impairs the ability of the bacteria to switch between different carbon sources. The urine in the bladder contains several different carbon sources and its composition changes over
Trofimov, M Yu; Kozitskiy, S B
2015-01-01
An adiabatic mode Helmholtz equation for 3D underwater sound propagation is developed. The Gaussian beam tracing in this case is constructed. The test calculations are carried out for the crosswedge benchmark and proved an excellent agreement with the source images method.
AUTONOMOUS GAUSSIAN DECOMPOSITION
Energy Technology Data Exchange (ETDEWEB)
Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.; Stanimirović, Snežana; Babler, Brian [Department of Astronomy, University of Wisconsin, 475 North Charter Street, Madison, WI 53706 (United States); Heiles, Carl [Radio Astronomy Lab, UC Berkeley, 601 Campbell Hall, Berkeley, CA 94720 (United States); Hennebelle, Patrick [Laboratoire AIM, Paris-Saclay, CEA/IRFU/SAp-CNRS-Université Paris Diderot, F-91191 Gif-sur Yvette Cedex (France); Goss, W. M. [National Radio Astronomy Observatory, P.O. Box O, 1003 Lopezville, Socorro, NM 87801 (United States); Dickey, John, E-mail: rlindner@astro.wisc.edu [University of Tasmania, School of Maths and Physics, Private Bag 37, Hobart, TAS 7001 (Australia)
2015-04-15
We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocity width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes.
Institute of Scientific and Technical Information of China (English)
陈阳; 杨绿溪; 何振亚
2000-01-01
The problem of blind separation of signals in post-nonlinear mixture is addressed in this paper.The post-nonlinear mixture is formed by a component wise nonlinear distortion after the linear mixture.Hence a nonlinear adjusting part placed in front of the linear separation structure is needed to compensate for the distortion in separating such signals.The learning rules for the post-nonlinear separation structure are derived by a maximum likelihood approach.An algorithm for blind separation of post-nonlinearly mixed sub- and super-Gaussian signals is proposed based on some previous work.Multilayer perceptrons are used in this algorithm to model the nonlinear part of the separation structure.The algorithm switches between sub- and super-Gaussian probability models during learning according to a stability condition and operates in a block-adaptive manner.The effectiveness of the algorithm is verified by experiments on simulated and real-world signals.%本文研究了后非线性混合信号的盲分离.后非线性混合信号是由线性混合的每一路信号分别经过一个非线性畸变产生的.因此分离这种信号需要在适用于线性混合的线性分离结构前放置一个用于补偿非线性畸变的非线性校正部分.本文用一种最大似然方法推导了一般后非线性分离结构的学习公式.在前人一些工作的基础上，提出了一种用于亚、超高斯信号后非线性混合的盲分离算法.该算法用多层感知器对分离结构的非线性校正部分进行建模，迭代过程中根据一稳定性条件在分别适用于亚、超高斯信号的概率模型间进行切换并以块自适应方式工作.通过对模拟信号及实际信号(图像和语音)的实验证明了该算法的有效性.
Preparation and frictional investigation of the two-components silanes deposited on alumina surface
Energy Technology Data Exchange (ETDEWEB)
Kośla, K.; Grobelny, J.; Cichomski, M., E-mail: mcichom@uni.lodz.pl
2014-09-30
Highlights: • The two-component silane films on the alumina surface were obtained by a combination of soft lithography and vapor phase deposition method. • The effectiveness of modification procedure was monitored by AFM topography images. • By using gas phase deposition method succeeded in obtaining a good reproduction of pattern. • Silane films with low surface free energy and coefficient of friction values were obtained. • The frictional performance in milli-Newton load range of one- and two-component films was investigated by microtribometry. - Abstract: Functionalization and pattering technique that permits two-component pattern-specific modification of alumina surface with silanes molecules are reported. The method relies on a two-component molecular system that simultaneously decreases coefficient of friction of the alumina surface and provides uniform chemical functionality suitable for further elaboration. Pattern/two-component modification is achieved via gas-phase deposition of the silanes using polydimethylsiloxane stamp. The frictional behaviors of the two-component films of the silane molecules with different chain length covalently absorbed on alumina surfaces, were characterized by the ball-disk (microtribometer) tester. The surfaces of the substrate modified by two-component molecular films were examined by atomic force microscopy (AFM). The measured tribological results showed that the mixing of the fluoroalkylsilane and alkylsilane enhance the lubrication and decrease the friction compared to the one-component thin films.
Methods of producing epoxides from alkenes using a two-component catalyst system
Kung, Mayfair C.; Kung, Harold H.; Jiang, Jian
2013-07-09
Methods for the epoxidation of alkenes are provided. The methods include the steps of exposing the alkene to a two-component catalyst system in an aqueous solution in the presence of carbon monoxide and molecular oxygen under conditions in which the alkene is epoxidized. The two-component catalyst system comprises a first catalyst that generates peroxides or peroxy intermediates during oxidation of CO with molecular oxygen and a second catalyst that catalyzes the epoxidation of the alkene using the peroxides or peroxy intermediates. A catalyst system composed of particles of suspended gold and titanium silicalite is one example of a suitable two-component catalyst system.
Two-component generalizations of the periodic Camassa-Holm and Degasperis-Procesi equations
Escher, Joachim; Lenells, Jonatan
2010-01-01
We use geometric methods to study two natural two-component generalizations of the periodic Camassa-Holm and Degasperis-Procesi equations. We show that these generalizations can be regarded as geodesic equations on the semidirect product of the diffeomorphism group of the circle $\\Diff(S^1)$ with some space of sufficiently smooth functions on the circle. Our goals are to understand the geometric properties of these two-component systems and to prove local well-posedness in various function spaces. Furthermore, we perform some explicit curvature calculations for the two-component Camassa-Holm equation, giving explicit examples of large subspaces of positive curvature.
Evolution and phyletic distribution of two-component signal transduction systems.
Wuichet, Kristin; Cantwell, Brian J; Zhulin, Igor B
2010-04-01
Two-component signal transduction systems are abundant in prokaryotes. They enable cells to adjust multiple cellular functions in response to changing environmental conditions. These systems are also found, although in much smaller numbers, in lower eukaryotes and plants, where they appear to control a few very specific functions. Two-component systems have evolved in Bacteria from much simpler one-component systems bringing about the benefit of extracellular versus intracellular sensing. We review reports establishing the origins of two-component systems and documenting their occurrence in major lineages of Life. Copyright 2010 Elsevier Ltd. All rights reserved.
Travelling wave solutions for some two-component shallow water models
Dutykh, Denys; Ionescu-Kruse, Delia
2016-07-01
In the present study we perform a unified analysis of travelling wave solutions to three different two-component systems which appear in shallow water theory. Namely, we analyze the celebrated Green-Naghdi equations, the integrable two-component Camassa-Holm equations and a new two-component system of Green-Naghdi type. In particular, we are interested in solitary and cnoidal-type solutions, as two most important classes of travelling waves that we encounter in applications. We provide a complete phase-plane analysis of all possible travelling wave solutions which may arise in these models. In particular, we show the existence of new type of solutions.
Two-Component Wadati-Konno-Ichikawa Equation and Its Symmetry Reductions
Institute of Scientific and Technical Information of China (English)
QU Chang-Zheng; YAO Ruo-Xia; LI Zhi-Bin
2004-01-01
@@ It is shown that two-component Wadati-Konno-Ichikawa (WKI) equation, i.e. a generalization of the well-known WKI equation, is obtained from the motion of space curves in Euclidean geometry, and it is exactly a system for the graph of the curves when the curve motion is governed by the two-component modified Korteweg-de Vries flow. Group-invariant solutions of the two-component WKI equation which corresponds to an optimal system of its Lie point symmetry groups are obtained, and its similarity reductions to systems of ordinary differential equations are also given.
Multipole invariants and non-Gaussianity
Land, K; Land, Kate; Magueijo, Joao
2004-01-01
We propose a framework for separating the information contained in the CMB multipoles, $a_{\\ell m}$, into its algebraically independent components. Thus we cleanly separate information pertaining to the power spectrum, non-Gaussianity and preferred axis effects. The formalism builds upon the recently proposed multipole vectors (Copi, Huterer & Starkman 2003; Schwarz & al 2004; Katz & Weeks 2004), and we elucidate a few features regarding these vectors, namely their lack of statistical independence for a Gaussian random process. In a few cases we explicitly relate our proposed invariants to components of the $n$-point correlation function (power spectrum, bispectrum). We find the invariants' distributions using a mixture of analytical and numerical methods. We also evaluate them for the co-added WMAP first year map.
DEFF Research Database (Denmark)
Kaasgaard, Thomas; Leidy, Chad; Crowe, J.H.
2003-01-01
ripples was seen. From height profiles of the AFM images, estimates of the amplitudes of the different ripple phases are reported. To elucidate the processes of ripple formation and disappearance, a ripple-phase DPPC lipid bilayer was taken through the pretransition in the cooling and the heating...... was heated from the ripple phase and into the ripple-phase/fluid-phase coexistence temperature region, the AFM images revealed that several dynamic properties of the ripple phase are important for the melting behavior of the lipid mixture. Onset of melting is observed at grain boundaries between different......Temperature-controlled atomic force microscopy (AFM) has been used to visualize and study the structure and kinetics of ripple phases in one-component dipalmitoylphosphaticlylcholine (DPPC) and two-component dimyristoylphosphatidylcholine-distearoylphosphatidylcholine (DMPC-DSPC) lipid bilayers...
Horner, Jonathan S
2013-01-01
The Hamilton-Jacobi (HJ) approach for exploring inflationary trajectories is employed in the generation of generalised inflationary non-Gaussian signals arising from single field inflation. Scale dependent solutions for $f_{NL}$ are determined via the numerical integration of the three--point function in the curvature perturbation. This allows the full exploration of single field inflationary dynamics in the out-of-slow-roll regime and opens up the possibility of using future observations of non-Gaussianity to constraint the inflationary potential using model-independent methods. The distribution of `equilateral' $f_{NL}$ arising from single field inflation with both canonical and non-canonical kinetic terms are show as an example of the application of this procedure.
Gaussian quantum marginal problem
Eisert, J; Sanders, B C; Tyc, T
2007-01-01
The quantum marginal problem asks what local spectra are consistent with a given state of a composite quantum system. This setting, also referred to as the question of the compatibility of local spectra, has several applications in quantum information theory. Here, we introduce the analogue of this statement for Gaussian states for any number of modes, and solve it in generality, for pure and mixed states, both concerning necessary and sufficient conditions. Formally, our result can be viewed as an analogue of the Sing-Thompson Theorem (respectively Horn's Lemma), characterizing the relationship between main diagonal elements and singular values of a complex matrix: We find necessary and sufficient conditions for vectors (d1, ..., dn) and (c1, ..., cn) to be the symplectic eigenvalues and symplectic main diagonal elements of a strictly positive real matrix, respectively. More physically speaking, this result determines what local temperatures or entropies are consistent with a pure or mixed Gaussian state of ...
On Gaussian random supergravity
Energy Technology Data Exchange (ETDEWEB)
Bachlechner, Thomas C. [Department of Physics, Cornell University,Physical Sciences Building 428, Ithaca, NY 14853 (United States)
2014-04-08
We study the distribution of metastable vacua and the likelihood of slow roll inflation in high dimensional random landscapes. We consider two examples of landscapes: a Gaussian random potential and an effective supergravity potential defined via a Gaussian random superpotential and a trivial Kähler potential. To examine these landscapes we introduce a random matrix model that describes the correlations between various derivatives and we propose an efficient algorithm that allows for a numerical study of high dimensional random fields. Using these novel tools, we find that the vast majority of metastable critical points in N dimensional random supergravities are either approximately supersymmetric with |F|≪M{sub susy} or supersymmetric. Such approximately supersymmetric points are dynamical attractors in the landscape and the probability that a randomly chosen critical point is metastable scales as log (P)∝−N. We argue that random supergravities lead to potentially interesting inflationary dynamics.
On Gaussian random supergravity
Bachlechner, Thomas C.
2014-04-01
We study the distribution of metastable vacua and the likelihood of slow roll inflation in high dimensional random landscapes. We consider two examples of landscapes: a Gaussian random potential and an effective supergravity potential defined via a Gaussian random superpotential and a trivial Kähler potential. To examine these landscapes we introduce a random matrix model that describes the correlations between various derivatives and we propose an efficient algorithm that allows for a numerical study of high dimensional random fields. Using these novel tools, we find that the vast majority of metastable critical points in N dimensional random supergravities are either approximately supersymmetric with | F| ≪ M susy or supersymmetric. Such approximately supersymmetric points are dynamical attractors in the landscape and the probability that a randomly chosen critical point is metastable scales as log( P ) ∝ - N. We argue that random supergravities lead to potentially interesting inflationary dynamics.
On Gaussian Random Supergravity
Bachlechner, Thomas C
2014-01-01
We study the distribution of metastable vacua and the likelihood of slow roll inflation in high dimensional random landscapes. We consider two examples of landscapes: a Gaussian random potential and an effective supergravity potential defined via a Gaussian random superpotential and a trivial Kahler potential. To examine these landscapes we introduce a random matrix model that describes the correlations between various derivatives and we propose an efficient algorithm that allows for a numerical study of high dimensional random fields. Using these novel tools, we find that the vast majority of metastable critical points in N dimensional random supergravities are either approximately supersymmetric with |F|<< M_{susy} or supersymmetric. Such approximately supersymmetric points are dynamical attractors in the landscape and the probability that a randomly chosen critical point is metastable scales as log(P)\\propto -N. We argue that random supergravities lead to potentially interesting inflationary dynamics...
Scale and Contour: Two Components of a Theory of Memory for Melodies.
Dowling, W. Jay
1978-01-01
The author concentrates on two components of memory which contribute to the reproduction and recognition of melodies, namely, melodic contour and musical scale. A new experiment is reported that shows the interdependence of both components. (Author/RK)
Laser controlling chaotic region of a two-component Bose-Einstein condensate
Institute of Scientific and Technical Information of China (English)
Boli Xia; Wenhua Hai
2005-01-01
@@ For a weakly and periodically driven two-component Bose-Einstein condensate (BEC) the Melnikov chaotic solution and boundedness conditions are derived from a direct perturbation theory that leads to the chaotic regions in the parameter space.
Role of functionality in two-component signal transduction: A stochastic study
Maity, Alok Kumar; Bandyopadhyay, Arnab; Chaudhury, Pinaki; Banik, Suman K.
2014-03-01
We present a stochastic formalism for signal transduction processes in a bacterial two-component system. Using elementary mass action kinetics, the proposed model takes care of signal transduction in terms of a phosphotransfer mechanism between the cognate partners of a two-component system, viz., the sensor kinase and the response regulator. Based on the difference in functionality of the sensor kinase, the noisy phosphotransfer mechanism has been studied for monofunctional and bifunctional two-component systems using the formalism of the linear noise approximation. Steady-state analysis of both models quantifies different physically realizable quantities, e.g., the variance, the Fano factor (variance/mean), and mutual information. The resultant data reveal that both systems reliably transfer information of extracellular environment under low external stimulus and in a high-kinase-and-phosphatase regime. We extend our analysis further by studying the role of the two-component system in downstream gene regulation.
Two component injection moulding: an interface quality and bond strength dilemma
DEFF Research Database (Denmark)
Islam, Mohammad Aminul; Hansen, Hans Nørgaard; Tang, Peter Torben
2008-01-01
Two component injection moulding is a special branch of injection moulding where two different polymers are combined in to a single part to exploit the different material properties in the final product. Considering the technical and economical importance of the process, this paper investigates...... on quality parameters of the two component parts. Most engineering applications of two component injection moulding calls for high bond strength between the two polymers, on the other hand a sharp and well-defined interface between the two polymers are required for applications like selective metallization...... conditions for a sharp and well-defined interface are exactly the opposite of what is congenial for higher bond strength. So in the production of two component injection moulded parts, there is a compromise to make between the interface quality and the bond strength of the two polymers. Also the injection...
ZHAO, Haiyan; Tang, Liang
2009-01-01
The multidomain cytoplasmic portion of the histidine protein kinase from an essential two-component signal transduction system has been crystallized and X-ray data have been collected to 2.8 Å resolution.
Scaled unscented transform Gaussian sum filter: theory and application
Luo, Xiaodong; Hoteit, Ibrahim
2010-01-01
In this work we consider the state estimation problem in nonlinear/non-Gaussian systems. We introduce a framework, called the scaled unscented transform Gaussian sum filter (SUT-GSF), which combines two ideas: the scaled unscented Kalman filter (SUKF) based on the concept of scaled unscented transform (SUT), and the Gaussian mixture model (GMM). The SUT is used to approximate the mean and covariance of a Gaussian random variable which is transformed by a nonlinear function, while the GMM is adopted to approximate the probability density function (pdf) of a random variable through a set of Gaussian distributions. With these two tools, a framework can be set up to assimilate nonlinear systems in a recursive way. Within this framework, one can treat a nonlinear stochastic system as a mixture model of a set of sub-systems, each of which takes the form of a nonlinear system driven by a known Gaussian random process. Then, for each sub-system, one applies the SUKF to estimate the mean and covariance of the underlyi...
Trofimov, M. Yu.; Zakharenko, A. D.; Kozitskiy, S. B.
2016-10-01
A mode parabolic equation in the ray centered coordinates for 3D underwater sound propagation is developed. The Gaussian beam tracing in this case is constructed. The test calculations are carried out for the ASA wedge benchmark and proved an excellent agreement with the source images method in the case of cross-slope propagation. But in the cases of wave propagation at some angles to the cross-slope direction an account of mode interaction becomes necessary.
Cao, Xinhua; Liu, Xue; Chen, Liming; Mao, Yueyuan; Lan, Haichuang; Yi, Tao
2015-11-15
A two-component gel containing long chain alkylated gallic acid (GA) and photochromic phenazopyridine (PAP) was prepared. The gel was thoroughly characterized by UV-visible and IR spectra, SEM and POM images, XRD diffraction and dynamic oscillatory measurements. The structure and transparency of the two-component gel can be reversibly changed by alternative UV light irradiation and warming in the palm of the hand. This kind of soft material has potential application in upscale surface functional materials.
Competitive Adsorption of a Two-Component Gas on a Deformable Adsorbent
Usenko, A. S.
2013-01-01
We investigate the competitive adsorption of a two-component gas on the surface of an adsorbent whose adsorption properties vary in adsorption due to the adsorbent deformation. The essential difference of adsorption isotherms for a deformable adsorbent both from the classical Langmuir adsorption isotherms of a two-component gas and from the adsorption isotherms of a one-component gas taking into account variations in adsorption properties of the adsorbent in adsorption is obtained. We establi...
Evolution and phyletic distribution of two-component signal transduction systems
Wuichet, Kristin; Cantwell, Brian J.; Zhulin, Igor B.
2010-01-01
Two-component signal transduction systems are abundant in prokaryotes. They enable cells to adjust multiple cellular functions in response to changing environmental conditions. These systems are also found, although in much smaller numbers, in lower eukaryotes and plants, where they appear to control a few very specific functions. Two-component systems have evolved in Bacteria from much simpler one-component systems bringing about the benefit of extracellular versus intracellular sensing. We ...
Variational derivation of two-component Camassa-Holm shallow water system
Ionescu-Kruse, Delia
2012-01-01
By a variational approach in the Lagrangian formalism, we derive the nonlinear integrable two-component Camassa-Holm system (1). We show that the two-component Camassa-Holm system (1) with the plus sign arises as an approximation to the Euler equations of hydrodynamics for propagation of irrotational shallow water waves over a flat bed. The Lagrangian used in the variational derivation is not a metric.
Chloroplast two-component systems: evolution of the link between photosynthesis and gene expression
Puthiyaveetil, Sujith; Allen, John F.
2009-01-01
Two-component signal transduction, consisting of sensor kinases and response regulators, is the predominant signalling mechanism in bacteria. This signalling system originated in prokaryotes and has spread throughout the eukaryotic domain of life through endosymbiotic, lateral gene transfer from the bacterial ancestors and early evolutionary precursors of eukaryotic, cytoplasmic, bioenergetic organelles—chloroplasts and mitochondria. Until recently, it was thought that two-component systems i...
Two-component mediated peroxide sensing and signal transduction in fission yeast.
Quinn, Janet; Malakasi, Panagiota; Smith, Deborah A; Cheetham, Jill; Buck, Vicky; Millar, Jonathan B A; Morgan, Brian A
2011-07-01
Two-component related proteins play a major role in regulating the oxidative stress response in the fission yeast, Schizosaccharomyces pombe. For example, the peroxide-sensing Mak2 and Mak3 histidine kinases regulate H(2)O(2)-induced activation of the Sty1 stress-activated protein kinase pathway, and the Skn7-related response regulator transcription factor, Prr1, is essential for activation of the core oxidative stress response genes. Here, we investigate the mechanism by which the S. pombe two-component system senses H(2)O(2), and the potential role of two-component signaling in the regulation of Prr1. Significantly, we demonstrate that PAS and GAF domains present in the Mak2 histidine kinase are essential for redox-sensing and activation of Sty1. In addition, we find that Prr1 is required for the transcriptional response to a wide range of H(2)O(2) concentrations and, furthermore, that two-component regulation of Prr1 is specifically required for the response of cells to high levels of H(2)O(2). Significantly, this provides the first demonstration that the conserved two-component phosphorylation site on Skn7-related proteins influences resistance to oxidative stress and oxidative stress-induced gene expression. Collectively, these data provide new insights into the two-component mediated sensing and signaling mechanisms underlying the response of S. pombe to oxidative stress.
Christensen, Steen; Serbus, Laura Renee
2015-03-24
Two-component regulatory systems are commonly used by bacteria to coordinate intracellular responses with environmental cues. These systems are composed of functional protein pairs consisting of a sensor histidine kinase and cognate response regulator. In contrast to the well-studied Caulobacter crescentus system, which carries dozens of these pairs, the streamlined bacterial endosymbiont Wolbachia pipientis encodes only two pairs: CckA/CtrA and PleC/PleD. Here, we used bioinformatic tools to compare characterized two-component system relays from C. crescentus, the related Anaplasmataceae species Anaplasma phagocytophilum and Ehrlichia chaffeensis, and 12 sequenced Wolbachia strains. We found the core protein pairs and a subset of interacting partners to be highly conserved within Wolbachia and these other Anaplasmataceae. Genes involved in two-component signaling were positioned differently within the various Wolbachia genomes, whereas the local context of each gene was conserved. Unlike Anaplasma and Ehrlichia, Wolbachia two-component genes were more consistently found clustered with metabolic genes. The domain architecture and key functional residues standard for two-component system proteins were well-conserved in Wolbachia, although residues that specify cognate pairing diverged substantially from other Anaplasmataceae. These findings indicate that Wolbachia two-component signaling pairs share considerable functional overlap with other α-proteobacterial systems, whereas their divergence suggests the potential for regulatory differences and cross-talk.
Bessel-Gaussian entanglement; presentation
CSIR Research Space (South Africa)
Mclaren, M
2013-07-01
Full Text Available GAUSSIAN BEAM LAGUERRE-GAUSSIAN BEAM 15 Page 5 Higher-order Bessel-Gaussian beams carry OAM Page 6 © CSIR 2013 www.csir.co.za Generating Bessel-Gaussian beams using spatial light modulators (SLMs) Blazed axicon Binary axicon... stream_source_info McLaren_2013.pdf.txt stream_content_type text/plain stream_size 2915 Content-Encoding UTF-8 stream_name McLaren_2013.pdf.txt Content-Type text/plain; charset=UTF-8 Bessel-Gaussian entanglement M. Mc...
Mapder, Tarunendu; Banik, Suman K
2016-01-01
Studies on the role of fluctuations in signal propagation and on gene regulation in monoclonal bacterial population have been extensively pursued based on the machinery of two-component system. The bacterial two-component system shows noise utilisation through its inherent plasticity. The fluctuations propagation takes place using the phosphotransfer module and the feedback mechanism during gene regulation. To delicately observe the noisy kinetics the generic cascade needs stochastic investigation at the mRNA and protein levels. To this end, we propose a theoretical framework to investigate the noisy signal transduction in a generic two-component system. The model shows reliability in information transmission through quantification of several statistical measures. We further extend our analysis to observe the protein distribution in a population of cells. Through numerical simulation, we identify the regime of the kinetic parameter set that generates a stability switch in the steady state distribution of prot...
Two-Component Signal Transduction Systems in the Cyanobacterium Synechocystis sp. PCC 6803
Institute of Scientific and Technical Information of China (English)
LIU Xingguo; HUANG Wei; WU Qingyu
2006-01-01
Two-component systems are signal transduction systems which enable bacteria to regulate cellular functions in response to changing environmental conditions. The unicellular Synechocystis sp. PCC 6803 has become a model organism for a range of biochemical and molecular biology studies aiming at investigating environmental stress response. The publication of the complete genome sequence of the cyanobacterium Synechocystis sp. PCC 6803 provided a tremendous stimulus for research in this field, and at least 80 open reading frames were identified as members of the two-component signal transduction systems in this single species of cyanobacteria. To date, functional roles have been determined for only a limited number of such proteins. This review summarizes our current knowledge about the two-component signal transduction systems in Synechocystis sp. PCC 6803 and describes recent achievements in elucidating the functional roles of these systems.
Non-Gaussian entanglement swapping
Dell'Anno, F; Nocerino, G; De Siena, S; Illuminati, F
2016-01-01
We investigate the continuous-variable entanglement swapping protocol in a non-Gaussian setting, with non- Gaussian states employed either as entangled inputs and/or as swapping resources. The quality of the swapping protocol is assessed in terms of the teleportation fidelity achievable when using the swapped states as shared entangled resources in a teleportation protocol. We thus introduce a two-step cascaded quantum communication scheme that includes a swapping protocol followed by a teleportation protocol. The swapping protocol is fed by a general class of tunable non-Gaussian states, the squeezed Bell states, which, by means of controllable free parameters, allows for a continuous morphing from Gaussian twin beams up to maximally non-Gaussian squeezed number states. In the realistic instance, taking into account the effects of losses and imperfections, we show that as the input two-mode squeezing increases, optimized non-Gaussian swapping resources allow for a monotonically increasing enhancement of the ...
Meisner, Aaron M.; Finkbeiner, Douglas P.
2015-01-01
We apply the Finkbeiner et al. two-component thermal dust emission model to the Planck High Frequency Instrument maps. This parameterization of the far-infrared dust spectrum as the sum of two modified blackbodies (MBBs) serves as an important alternative to the commonly adopted single-MBB dust emission model. Analyzing the joint Planck/DIRBE dust spectrum, we show that two-component models provide a better fit to the 100-3000 GHz emission than do single-MBB models, though by a lesser margin than found by Finkbeiner et al. based on FIRAS and DIRBE. We also derive full-sky 6.'1 resolution maps of dust optical depth and temperature by fitting the two-component model to Planck 217-857 GHz along with DIRBE/IRAS 100 μm data. Because our two-component model matches the dust spectrum near its peak, accounts for the spectrum's flattening at millimeter wavelengths, and specifies dust temperature at 6.'1 FWHM, our model provides reliable, high-resolution thermal dust emission foreground predictions from 100 to 3000 GHz. We find that, in diffuse sky regions, our two-component 100-217 GHz predictions are on average accurate to within 2.2%, while extrapolating the Planck Collaboration et al. single-MBB model systematically underpredicts emission by 18.8% at 100 GHz, 12.6% at 143 GHz, and 7.9% at 217 GHz. We calibrate our two-component optical depth to reddening, and compare with reddening estimates based on stellar spectra. We find the dominant systematic problems in our temperature/reddening maps to be zodiacal light on large angular scales and the cosmic infrared background anisotropy on small angular scales.
Domain Walls and Textured Vortices in a Two-Component Ginzburg-Landau Model
DEFF Research Database (Denmark)
Madsen, Søren Peder; Gaididei, Yu. B.; Christiansen, Peter Leth
2005-01-01
We look for domain wall and textured vortex solutions in a two-component Ginzburg-Landau model inspired by two-band superconductivity. The two-dimensional two-component model, with equal coherence lengths and no magnetic field, shows some interesting properties. In the absence of a Josephson type...... coupling between the two order parameters a ''textured vortex'' is found by analytical and numerical solution of the Ginzburg-Landau equations. With a Josephson type coupling between the two order parameters we find the system to split up in two domains separated by a domain wall, where the order parameter...
Block algebra in two-component BKP and D type Drinfeld-Sokolov hierarchies
Li, Chuanzhong; He, Jingsong
2013-11-01
We construct generalized additional symmetries of a two-component BKP hierarchy defined by two pseudo-differential Lax operators. These additional symmetry flows form a Block type algebra with some modified (or additional) terms because of a B type reduction condition of this integrable hierarchy. Further we show that the D type Drinfeld-Sokolov hierarchy, which is a reduction of the two-component BKP hierarchy, possess a complete Block type additional symmetry algebra. That D type Drinfeld-Sokolov hierarchy has a similar algebraic structure as the bigraded Toda hierarchy which is a differential-discrete integrable system.
Rabi Oscillations in Two-Component Bose-Einstein Condensates with a Coupling Drive
Institute of Scientific and Technical Information of China (English)
LI Wei-Dong; FAN Wen-Bing; ZHOU Xiao-Ji; WANG Yi-Qiu; LIANG Jiu-Qing
2002-01-01
The Rabi oscillations in two-component Bose-Einstein condensates with a coupling drive are studiedby means of a pair of bosonic operators. The coupling drive and initial phase difference will affect the amplitudeand the period of the Rabi oscillations. The Rabi oscillations will vanish in the evolution of the condensate densityfor some special initial phase differences (ψ = 0 or π). Our theory provides not only an analytical framework forquantitative predictions for two-component condensates, but also gives an intuitive understanding of some mysteriousfeatures observed in experiments and numerical. simulations.
Targeting two-component signal transduction: a novel drug discovery system.
Okada, Ario; Gotoh, Yasuhiro; Watanabe, Takafumi; Furuta, Eiji; Yamamoto, Kaneyoshi; Utsumi, Ryutaro
2007-01-01
We have developed two screening systems for isolating inhibitors that target bacterial two-component signal transduction: (1) a differential growth assay using a temperature-sensitive yycF mutant (CNM2000) of Bacillus subtilis, which is supersensitive to histidine kinase inhibitors, and (2) a high-throughput genetic system for targeting the homodimerization of histidine kinases essential for the bacterial two-component signal transduction. By using these methods, we have been able to identify various types of inhibitors that block the autophosphorylation of histidine kinases with different modes of actions.
Modulational instability of two-component Bose-Einstein condensates in an optical lattice
Jin, G R; Nahm, K; Jin, Guang-Ri; Kim, Chul Koo; Nahm, Kyun
2004-01-01
We study modulational instability of two-component Bose-Einstein condensates in a deep optical lattice, which is modelled as a coupled discrete nonlinear Schr\\"{o}dinger equation. The excitation spectrum and the modulational instability condition of the total system are presented analytically. In the long-wavelength limit, our results agree with the homogeneous two-component Bose-Einstein condensates case. The discreteness effects result in the appearance of the modulational instability for the condensates in miscible region. The numerical calculations confirm our analytical results and show that the interspecies coupling can transfer the instability from one component to another.
Domain Walls and Textured Vortices in a Two-Component Ginzburg-Landau Model
DEFF Research Database (Denmark)
Madsen, Søren Peder; Gaididei, Yu. B.; Christiansen, Peter Leth
2005-01-01
We look for domain wall and textured vortex solutions in a two-component Ginzburg-Landau model inspired by two-band superconductivity. The two-dimensional two-component model, with equal coherence lengths and no magnetic field, shows some interesting properties. In the absence of a Josephson type...... coupling between the two order parameters a ''textured vortex'' is found by analytical and numerical solution of the Ginzburg-Landau equations. With a Josephson type coupling between the two order parameters we find the system to split up in two domains separated by a domain wall, where the order parameter...
Block algebra in two-component BKP and D type Drinfeld-Sokolov hierarchies
Energy Technology Data Exchange (ETDEWEB)
Li, Chuanzhong, E-mail: lichuanzhong@nbu.edu.cn; He, Jingsong, E-mail: hejingsong@nbu.edu.cn [Department of Mathematics, Ningbo University, Ningbo 315211 (China)
2013-11-15
We construct generalized additional symmetries of a two-component BKP hierarchy defined by two pseudo-differential Lax operators. These additional symmetry flows form a Block type algebra with some modified (or additional) terms because of a B type reduction condition of this integrable hierarchy. Further we show that the D type Drinfeld-Sokolov hierarchy, which is a reduction of the two-component BKP hierarchy, possess a complete Block type additional symmetry algebra. That D type Drinfeld-Sokolov hierarchy has a similar algebraic structure as the bigraded Toda hierarchy which is a differential-discrete integrable system.
Experimental Investigation of the Evolution of Gaussian Quantum Discord in an Open System
DEFF Research Database (Denmark)
Madsen, Lars S.; Berni, Adriano; Lassen, Mikael;
2012-01-01
Gaussian quantum discord is a measure of quantum correlations in Gaussian systems. Using Gaussian discord, we quantify the quantum correlations of a bipartite entangled state and a separable two-mode mixture of coherent states. We experimentally analyze the effect of noise addition and dissipatio...... on Gaussian discord and show that the former noise degrades the discord, while the latter noise for some states leads to an increase of the discord. In particular, we experimentally demonstrate the near death of discord by noisy evolution and its revival through dissipation....
Three-wave interaction in two-component quadratic nonlinear lattices
DEFF Research Database (Denmark)
Konotop, V. V.; Cunha, M. D.; Christiansen, Peter Leth
1999-01-01
We investigate a two-component lattice with a quadratic nonlinearity and find with the multiple scale technique that integrable three-wave interaction takes place between plane wave solutions when these fulfill resonance conditions. We demonstrate that. energy conversion and pulse propagation kno...
A novel two-component system found in Mycobacterium tuberculosis
DEFF Research Database (Denmark)
Morth, J. P.; Gosmann, S.; Nowak, E.;
2005-01-01
We report the identification of a novel two-component system in Mycobacterium tuberculosis. We show that the putative histidine kinase with the genomic locus tag Rv3220c is able to self-phosphorylate in the presence of Mg2+/ATP and subsequently transfer the phosphoryl group to a novel response...
Light Responsive Two-Component Supramolecular Hydrogel: A Sensitive Platform for Humidity Sensors
Samai, Suman
2016-02-15
The supramolecular assembly of anionic azobenzene dicarboxylate and cationic cetyltrimethylammonium bromide (CTAB) formed a stimuli responsive hydrogel with a critical gelation concentration (CGC) of 0.33 wt%. This self-sustainable two-component system was able to repair damage upon light irradiation. Moreover, it was successfully employed in the fabrication of highly sensitive humidity sensors for the first time.
A Two-Component Generalization of Burgers' Equation with Quasi-Periodic Solution
Pan, Hongfei; Xia, Tiecheng; Chen, Dengyuan
2014-10-01
In this paper, we aim for the theta function representation of quasi-periodic solution and related crucial quantities for a two-component generalization of Burgers' equation. Our tools include the theory of algebraic curves, meromorphic functions, Baker-Akhiezer functions and the Dubrovin-type equations for auxiliary divisor. Eith these tools, the explicit representations for above quantities are obtained.
Two-component Brownian coagulation: Monte Carlo simulation and process characterization
Institute of Scientific and Technical Information of China (English)
Haibo Zhao; Chu guang Zheng
2011-01-01
The compositional distribution within aggregates of a given size is essential to the functionality of composite aggregates that are usually enlarged by rapid Brownian coagulation.There is no analytical solution for the process of such two-component systems.Monte Carlo method is an effective numerical approach for two-component coagulation.In this paper,the differentially weighted Monte Carlo method is used to investigate two-component Brownian coagulation,respectively,in the continuum regime,the freemolecular regime and the transition regime.It is found that ( 1 ) for Brownian coagulation in the continuum regime and in the free-molecular regime,the mono-variate compositional distribution,i.e.,the number density distribution function of one component amount (in the form of volume of the component in aggregates) satisfies self-preserving form the same as particle size distribution in mono-component Brownian coagulation; (2) however,for Brownian coagulation in the transition regime the mono-variate compositional distribution cannot reach self-similarity; and (3) the bivariate compositional distribution,i.e.,the combined number density distribution function of two component amounts in the three regimes satisfies a semi self-preserving form.Moreover,other new features inherent to aggregative mixing are also demonstrated; e.g.,the degree of mixing between components,which is largely controlled by the initial compositional mass fraction,improves as aggregate size increases.
The Integrability of New Two-Component KdV Equation
Directory of Open Access Journals (Sweden)
Ziemowit Popowicz
2010-02-01
Full Text Available We consider the bi-Hamiltonian representation of the two-component coupled KdV equations discovered by Drinfel'd and Sokolov and rediscovered by Sakovich and Foursov. Connection of this equation with the supersymmetric Kadomtsev-Petviashvilli-Radul-Manin hierarchy is presented. For this new supersymmetric equation the Lax representation and odd Hamiltonian structure is given.
The Qualitative Analysis of a Solution of a Series Maintenance System with Two Components
Institute of Scientific and Technical Information of China (English)
GUOWei-hua; YANGMing-zeng
2003-01-01
In this paper, firstly we study the series maintenance system with two components, obtain its exsistence and uniqueness of a dynamic state nonnegative solution by strongly continuous semigroups of operators theory. Then we prove that 0 is the eigenvalue of the system's host operators, and finally we study the eigenvector of the eigenvalue 0.
A novel two-component system involved in secretion stress response in Streptomyces lividans.
Directory of Open Access Journals (Sweden)
Sonia Gullón
Full Text Available BACKGROUND: Misfolded proteins accumulating outside the bacterial cytoplasmic membrane can interfere with the secretory machinery, hence the existence of quality factors to eliminate these misfolded proteins is of capital importance in bacteria that are efficient producers of secretory proteins. These bacteria normally use a specific two-component system to respond to the stress produced by the accumulation of the misfolded proteins, by activating the expression of HtrA-like proteases to specifically eliminate the incorrectly folded proteins. METHODOLOGY/PRINCIPAL FINDINGS: Overproduction of alpha-amylase in S. lividans causing secretion stress permitted the identification of a two-component system (SCO4156-SCO4155 that regulates three HtrA-like proteases which appear to be involved in secretion stress response. Mutants in each of the genes forming part of the two-genes operon that encodes the sensor and regulator protein components accumulated misfolded proteins outside the cell, strongly suggesting the involvement of this two-component system in the S. lividans secretion stress response. CONCLUSIONS/SIGNIFICANCE: To our knowledge this is the first time that a specific secretion stress response two-component system is found to control the expression of three HtrA-like protease genes in S. lividans, a bacterium that has been repeatedly used as a host for the synthesis of homologous and heterologous secretory proteins of industrial application.
Impacts of photon bending on observational aspects of Two Component Advective Flow
Chatterjee, Arka
2016-01-01
Nature of photon trajectories in a curved spacetime around black holes are studied without constraining their motion to any plane. Impacts of photon bending are separately scrutinized for Keplerian and CENBOL components of Two Component Advective Flow (TCAF) model. Parameters like Red shift, Bolometric Flux, temperature profile and time of arrival of photons are also computed.
The essential YycFG two-component system controls cell wall metabolism in Bacillus subtilis
DEFF Research Database (Denmark)
Bisicchia, Paola; Noone, David; Lioliou, Efthimia
2007-01-01
Adaptation of bacteria to the prevailing environmental and nutritional conditions is often mediated by two-component signal transduction systems (TCS). The Bacillus subtilis YycFG TCS has attracted special attention as it is essential for viability and its regulon is poorly defined. Here we show...
Modeling Thermal Dust Emission with Two Components: Application to the Planck HFI Maps
Meisner, Aaron
2014-01-01
We apply the Finkbeiner et al. (1999) two-component thermal dust emission model to the Planck HFI maps. This parametrization of the far-infrared dust spectrum as the sum of two modified blackbodies serves as an important alternative to the commonly adopted single modified blackbody (MBB) dust emission model. Analyzing the joint Planck/DIRBE dust spectrum, we show that two-component models provide a better fit to the 100-3000 GHz emission than do single-MBB models, though by a lesser margin than found by Finkbeiner et al. (1999) based on FIRAS and DIRBE. We also derive full-sky 6.1' resolution maps of dust optical depth and temperature by fitting the two-component model to Planck 217-857 GHz along with DIRBE/IRAS 100 micron data. Because our two-component model matches the dust spectrum near its peak, accounts for the spectrum's flattening at millimeter wavelengths, and specifies dust temperature at 6.1' FWHM, our model provides reliable, high-resolution thermal dust emission foreground predictions from 100 to...
Global dissipative solutions for the two-component Camassa-Holm shallow water system
Directory of Open Access Journals (Sweden)
Yujuan Wang
2015-01-01
Full Text Available This article presents a continuous semigroup of globally defined weak dissipative solutions for the two-component Camassa-Holm system. Such solutions are established by using a new approach based on characteristics a set of new variables overcoming the difficulties inherent in multi-component systems.
Phase separation and dynamics of two-component Bose-Einstein condensates
DEFF Research Database (Denmark)
Lee, Kean Loon; Jørgensen, Nils Byg; Liu, I-Kang;
2016-01-01
The miscibility of two interacting quantum systems is an important testing ground for the understanding of complex quantum systems. Two-component Bose-Einstein condensates enable the investigation of this scenario in a particularly well controlled setting. In a homogeneous system, the transition...
Phase of Two-Component Bose-Einstein Condensates with a Coupling Drive
Institute of Scientific and Technical Information of China (English)
YU Zhao-Xian; JIN Shuo; JIAO Zhi-Yong; WANG Ji-Suo
2007-01-01
By using the invariant theory, we study the phases of two-component Bose-Einstein condensates with a coupling drive under the case that the strength of the interatomic interaction in each condensate equals the interspecies interaction. The dynamical and geometric phases are presented respectively. The Aharonov-Anandan phase is also obtained under the cyclical evolution.
The dynamics of nonstationary solutions in one-dimensional two-component Bose-Einstein condensates
Institute of Scientific and Technical Information of China (English)
Lü Bin-Bin; Hao Xue; Tian Qiang
2011-01-01
This paper investigates the dynamical properties of nonstationary solutions in one-dimensional two-component Bose-Einstein condensates. It gives three kinds of stationary solutions to this model and develops a general method of constructing nonstationary solutions. It obtains the unique features about general evolution and soliton evolution of nonstationary solutions in this model.
Instabilities on crystal surfaces: The two-component body-centered solid-on-solid model
Carlon, E.; van Beijeren, H.; Mazzeo, G.
1996-01-01
The free energy of crystal surfaces that can be described by the two-component body-centered solid-on-solid model has been calculated in a mean-field approximation. The system may model ionic crystals with a bcc lattice structure (for instance CsCl). Crossings between steps are energetically favored
Geometric Integrability of Two-Component Camassa-Holm and Hunter-Saxton Systems
Institute of Scientific and Technical Information of China (English)
SONG Juu-Feng; QU Chang-Zheng
2011-01-01
It is shown that the two-component Camassa-Holm and Hunter-Saxton systems are geometrically integrable, namely they describe pseudo-spherical surfaces. As a consequence, their infinite number o, conservation laws are directly constructed. In addition, a class of nonlocal symmetries depending on the pseudo-potentials are obtained.
Duvenaud, David; Rasmussen, Carl Edward
2011-01-01
We introduce a Gaussian process model of functions which are additive. An additive function is one which decomposes into a sum of low-dimensional functions, each depending on only a subset of the input variables. Additive GPs generalize both Generalized Additive Models, and the standard GP models which use squared-exponential kernels. Hyperparameter learning in this model can be seen as Bayesian Hierarchical Kernel Learning (HKL). We introduce an expressive but tractable parameterization of the kernel function, which allows efficient evaluation of all input interaction terms, whose number is exponential in the input dimension. The additional structure discoverable by this model results in increased interpretability, as well as state-of-the-art predictive power in regression tasks.
Multilevel Mixture Kalman Filter
Directory of Open Access Journals (Sweden)
Xiaodong Wang
2004-11-01
Full Text Available The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS and integrates out the linear and Gaussian state variables conditioned on these indicators. Due to the marginalization process, the complexity of the mixture Kalman filter is quite high if the dimension of the indicator sampling space is high. In this paper, we address this difficulty by developing a new Monte Carlo sampling scheme, namely, the multilevel mixture Kalman filter. The basic idea is to make use of the multilevel or hierarchical structure of the space from which the indicator variables take values. That is, we draw samples in a multilevel fashion, beginning with sampling from the highest-level sampling space and then draw samples from the associate subspace of the newly drawn samples in a lower-level sampling space, until reaching the desired sampling space. Such a multilevel sampling scheme can be used in conjunction with the delayed estimation method, such as the delayed-sample method, resulting in delayed multilevel mixture Kalman filter. Examples in wireless communication, specifically the coherent and noncoherent 16-QAM over flat-fading channels, are provided to demonstrate the performance of the proposed multilevel mixture Kalman filter.
Entangled Bessel-Gaussian beams
CSIR Research Space (South Africa)
McLaren, M
2012-10-01
Full Text Available Orbital angular momentum (OAM) entanglement is investigated in the Bessel-Gaussian (BG) basis. Having a readily adjustable radial scale, BG modes provide an alternative basis for OAM entanglement over Laguerre-Gaussian modes. We show that the OAM...
Gaussian Fibonacci Circulant Type Matrices
Directory of Open Access Journals (Sweden)
Zhaolin Jiang
2014-01-01
Full Text Available Circulant matrices have become important tools in solving integrable system, Hamiltonian structure, and integral equations. In this paper, we prove that Gaussian Fibonacci circulant type matrices are invertible matrices for n>2 and give the explicit determinants and the inverse matrices. Furthermore, the upper bounds for the spread on Gaussian Fibonacci circulant and left circulant matrices are presented, respectively.
Bandwidth of Gaussian weighted Chirp
DEFF Research Database (Denmark)
Wilhjelm, Jens E.
1993-01-01
Four major time duration and bandwidth expressions are calculated for a linearly frequency modulated sinusoid with Gaussian shaped envelope. This includes a Gaussian tone pulse. The bandwidth is found to be a nonlinear function of nominal time duration and nominal frequency excursion of the chirp...
Spectral representation of Gaussian semimartingales
DEFF Research Database (Denmark)
Basse-O'Connor, Andreas
2009-01-01
The aim of the present paper is to characterize the spectral representation of Gaussian semimartingales. That is, we provide necessary and sufficient conditions on the kernel K for X t =∫ K t (s) dN s to be a semimartingale. Here, N denotes an independently scattered Gaussian random measure...
Scaled unscented transform Gaussian sum filter: Theory and application
Luo, Xiaodong
2010-05-01
In this work we consider the state estimation problem in nonlinear/non-Gaussian systems. We introduce a framework, called the scaled unscented transform Gaussian sum filter (SUT-GSF), which combines two ideas: the scaled unscented Kalman filter (SUKF) based on the concept of scaled unscented transform (SUT) (Julier and Uhlmann (2004) [16]), and the Gaussian mixture model (GMM). The SUT is used to approximate the mean and covariance of a Gaussian random variable which is transformed by a nonlinear function, while the GMM is adopted to approximate the probability density function (pdf) of a random variable through a set of Gaussian distributions. With these two tools, a framework can be set up to assimilate nonlinear systems in a recursive way. Within this framework, one can treat a nonlinear stochastic system as a mixture model of a set of sub-systems, each of which takes the form of a nonlinear system driven by a known Gaussian random process. Then, for each sub-system, one applies the SUKF to estimate the mean and covariance of the underlying Gaussian random variable transformed by the nonlinear governing equations of the sub-system. Incorporating the estimations of the sub-systems into the GMM gives an explicit (approximate) form of the pdf, which can be regarded as a "complete" solution to the state estimation problem, as all of the statistical information of interest can be obtained from the explicit form of the pdf (Arulampalam et al. (2002) [7]). In applications, a potential problem of a Gaussian sum filter is that the number of Gaussian distributions may increase very rapidly. To this end, we also propose an auxiliary algorithm to conduct pdf re-approximation so that the number of Gaussian distributions can be reduced. With the auxiliary algorithm, in principle the SUT-GSF can achieve almost the same computational speed as the SUKF if the SUT-GSF is implemented in parallel. As an example, we will use the SUT-GSF to assimilate a 40-dimensional system due to
Shandarin, S F; Xu, Y; Tegmark, M; Shandarin, Sergei F.; Feldman, Hume A.; Xu, Yongzhong; Tegmark, Max
2001-01-01
We test degree-scale cosmic microwave background (CMB) anisotropy for Gaussianity by studying the \\qmask map that was obtained from combining the QMAP and Saskatoon data. We compute seven morphological functions $M_i(\\dt)$, $i=1,...,7$: six \\mf and the number of regions $N_c$ at a hundred $\\dt$ levels. We also introduce a new parameterization of the morphological functions $M_i(A)$ in terms of the total area $A$ of the excursion set. We show that the latter considerably decorrelates the morphological statistics. We compare these results with those from 1000 Gaussian Monte Carlo maps with the same power spectrum, and conclude that the \\qmask map is neither a very typical nor a very exceptional realization of a Gaussian field. Roughly 20% of the 1000 Gaussian Monte Carlo maps differ more than the \\qmask map from the mean morphological parameters of the Gaussian fields.
Nonlinear Approximation Using Gaussian Kernels
Hangelbroek, Thomas
2009-01-01
It is well-known that non-linear approximation has an advantage over linear schemes in the sense that it provides comparable approximation rates to those of the linear schemes, but to a larger class of approximands. This was established for spline approximations and for wavelet approximations, and more recently for homogeneous radial basis function (surface spline) approximations. However, no such results are known for the Gaussian function. The crux of the difficulty lies in the necessity to vary the tension parameter in the Gaussian function spatially according to local information about the approximand: error analysis of Gaussian approximation schemes with varying tension are, by and large, an elusive target for approximators. We introduce and analyze in this paper a new algorithm for approximating functions using translates of Gaussian functions with varying tension parameters. Our scheme is sophisticated to a degree that it employs even locally Gaussians with varying tensions, and that it resolves local ...
Normal form decomposition for Gaussian-to-Gaussian superoperators
Energy Technology Data Exchange (ETDEWEB)
De Palma, Giacomo [NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR, I-56126 Pisa (Italy); INFN, Pisa (Italy); Mari, Andrea; Giovannetti, Vittorio [NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR, I-56126 Pisa (Italy); Holevo, Alexander S. [Steklov Mathematical Institute, 119991 Moscow, Russia and National Research University Higher School of Economics (HSE), 101000 Moscow (Russian Federation)
2015-05-15
In this paper, we explore the set of linear maps sending the set of quantum Gaussian states into itself. These maps are in general not positive, a feature which can be exploited as a test to check whether a given quantum state belongs to the convex hull of Gaussian states (if one of the considered maps sends it into a non-positive operator, the above state is certified not to belong to the set). Generalizing a result known to be valid under the assumption of complete positivity, we provide a characterization of these Gaussian-to-Gaussian (not necessarily positive) superoperators in terms of their action on the characteristic function of the inputs. For the special case of one-mode mappings, we also show that any Gaussian-to-Gaussian superoperator can be expressed as a concatenation of a phase-space dilatation, followed by the action of a completely positive Gaussian channel, possibly composed with a transposition. While a similar decomposition is shown to fail in the multi-mode scenario, we prove that it still holds at least under the further hypothesis of homogeneous action on the covariance matrix.
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.
2007-12-01
A mixture experiment involves combining two or more components in various proportions or amounts and then measuring one or more responses for the resulting end products. Other factors that affect the response(s), such as process variables and/or the total amount of the mixture, may also be studied in the experiment. A mixture experiment design specifies the combinations of mixture components and other experimental factors (if any) to be studied and the response variable(s) to be measured. Mixture experiment data analyses are then used to achieve the desired goals, which may include (i) understanding the effects of components and other factors on the response(s), (ii) identifying components and other factors with significant and nonsignificant effects on the response(s), (iii) developing models for predicting the response(s) as functions of the mixture components and any other factors, and (iv) developing end-products with desired values and uncertainties of the response(s). Given a mixture experiment problem, a practitioner must consider the possible approaches for designing the experiment and analyzing the data, and then select the approach best suited to the problem. Eight possible approaches include 1) component proportions, 2) mathematically independent variables, 3) slack variable, 4) mixture amount, 5) component amounts, 6) mixture process variable, 7) mixture of mixtures, and 8) multi-factor mixture. The article provides an overview of the mixture experiment designs, models, and data analyses for these approaches.
Missing data reconstruction using Gaussian mixture models for fingerprint images
Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary
2016-05-01
Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.
Gaussian Mixture Reduction for Bayesian Target Tracking in Clutter
2005-12-22
IEEE Transactions on Automatic Control, AC-17(4):439–448, August 1972. 3. Arfken , George B. and Hans J. Weber. Mathematical Methods for Physicists...developed this method in a more formal mathematical manner. As their work popu- larized the method of maximum likelihood, it became commonly known as...Brooks/Cole Publish- ing Company, Belmont, CA, 1990. 10. Cramér, Harald. Mathematical Methods of Statistics. Princeton University Press, Princeton
Geotail observations of temperature anisotropy of the two-component protons in the dusk plasma sheet
Directory of Open Access Journals (Sweden)
M. N. Nishino
2007-03-01
Full Text Available In search for clues towards the understanding of the cold plasma sheet formation under northward IMF, we study the temperature anisotropy of the two-component protons in the plasma sheet near the dusk low-latitude boundary observed by the Geotail spacecraft. The two-component protons result from mixing of the cold component from the solar wind and the hot component of the magnetospheric origin, and may be the most eloquent evidence for the transport process across the magnetopause. The cold component occasionally has a strong anisotropy in the dusk flank, and the sense of the anisotropy depends on the observed locations: the parallel temperature is enhanced in the tail flank while the perpendicular temperature is enhanced on the dayside. The hot component is nearly isotropic in the tail while the perpendicular temperature is enhanced on the dayside. We discuss possible mechanism that can lead to the observed temperature anisotropies.
Trapping of two-component matter-wave solitons by mismatched optical lattices
Energy Technology Data Exchange (ETDEWEB)
Shi, Z.; Law, K.J.H. [Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01003-4515 (United States); Kevrekidis, P.G. [Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01003-4515 (United States)], E-mail: kevrekid@gmail.com; Malomed, B.A. [Department of Physical Electronics, School of Electrical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv 69978 (Israel)
2008-05-26
We consider a one-dimensional model of a two-component Bose-Einstein condensate in the presence of periodic external potentials of opposite signs, acting on the two species. The interaction between the species is attractive, while intra-species interactions may be attractive too [the system of the bright-bright (BB) type], or of opposite signs in the two components [the gap-bright (GB) type]. We identify the existence and stability domains for soliton complexes of the BB and GB types. The evolution of unstable solitons leads to the establishment of oscillatory states. The increase of the strength of the nonlinear attraction between the species results in symbiotic stabilization of the complexes, despite the fact that one component is centered around a local maximum of the respective periodic potential.
Peng, Daoling; Weigend, Florian; Reiher, Markus
2013-01-01
We present an efficient algorithm for one- and two-component relativistic exact-decoupling calculations. The spin-orbit coupling was taken into account for the evaluation of relativistically transformed Hamiltonian. The relativistic decoupling transformation has to be evaluated with primitive functions so that the construction of the relativistic one-electron Hamiltonian becomes the bottleneck of the whole calculation for large molecules. We apply our recently developed local DLU scheme [J. Chem. Phys. 136 (2012) 244108] to accelerate this step. With our new implementation two-component relativistic density functional calculations can be performed invoking the resolution-of-identity density-fitting approximation and (Abelian as well as non-Abelian) point group symmetries to accelerate both the exact-decoupling and the two-electron part. The capability of our implementation is illustrated at the example of silver clusters with up to 309 atoms, for which the cohesive energy is calculated and extrapolated to the...
Two-component Fermi-liquid theory - Equilibrium properties of liquid metallic hydrogen
Oliva, J.; Ashcroft, N. W.
1981-01-01
It is reported that the transition of condensed hydrogen from an insulating molecular crystal phase to a metallic liquid phase, at zero temperature and high pressure, appears possible. Liquid metallic hydrogen (LMH), comprising interpenetrating proton and electron fluids, would constitute a two-component Fermi liquid with both a very high component-mass ratio and long-range, species-dependent bare interactions. The low-temperature equilibrium properties of LMH are examined by means of a generalization to the case of two components of the phenomenological Landau Fermi-liquid theory, and the low-temperature specific heat, compressibility, thermal expansion coefficient and spin susceptibility are given. It is found that the specific heat and the thermal expansion coefficient are vastly greater in the liquid than in the corresponding solid, due to the presence of proton quasiparticle excitations in the liquid.
Use of two-component signal transduction systems in the construction of synthetic genetic networks.
Ninfa, Alexander J
2010-04-01
Two-component signal transduction systems are a common type of signaling system in prokaryotes; the typical cell has dozens of systems regulating aspects of physiology and controlling responses to environmental conditions. In this review, I consider how these systems may be useful for engineering novel cell functions. Examples of successful incorporation of two-component systems into engineered systems are noted, and features of the systems that favor or hinder potential future use of these signaling systems for synthetic biology applications are discussed. The focus will be on the engineering of novel couplings of sensory functions to signaling outputs. Recent successes in this area are noted, such as the development of light-sensitive transmitter proteins and chemotactic receptors responsive to nitrate. Copyright 2010 Elsevier Ltd. All rights reserved.
Lou, Qiang; Qi, Yijun; Ma, Yuanfang; Qu, Di
2014-01-01
Staphylococcus epidermidis, which is a causative pathogen of nosocomial infection, expresses its virulent traits such as biofilm and autolysis regulated by two-component signal transduction system SaeRS. In this study, we performed a proteomic analysis of differences in expression between the S. epidermidis 1457 wild-type and saeRS mutant to identify candidates regulated by saeRS using two-dimensional gel electrophoresis (2-DE) combined with matrix-assisted laser desorption/lonization mass spectrometry (MALDI-TOF-MS). Of 55 identified proteins that significantly differed in expression between the two strains, 15 were upregulated and 40 were downregulated. The downregulated proteins included enzymes related to glycolysis and TCA cycle, suggesting that glucose is not properly utilized in S. epidermidis when saeRS was deleted. The study will be helpful for treatment of S. epidermidis infection from the viewpoint of metabolic modulation dependent on two-component signal transduction system SaeRS.
Casino, Patricia; Rubio, Vicente; Marina, Alberto
2009-10-16
The chief mechanism used by bacteria for sensing their environment is based on two conserved proteins: a sensor histidine kinase (HK) and an effector response regulator (RR). The signal transduction process involves highly conserved domains of both proteins that mediate autokinase, phosphotransfer, and phosphatase activities whose output is a finely tuned RR phosphorylation level. Here, we report the structure of the complex between the entire cytoplasmic portion of Thermotoga maritima class I HK853 and its cognate, RR468, as well as the structure of the isolated RR468, both free and BeF(3)(-) bound. Our results provide insight into partner specificity in two-component systems, recognition of the phosphorylation state of each partner, and the catalytic mechanism of the phosphatase reaction. Biochemical analysis shows that the HK853-catalyzed autokinase reaction proceeds by a cis autophosphorylation mechanism within the HK subunit. The results suggest a model for the signal transduction mechanism in two-component systems.
A hydrodynamic scheme for two-component winds from hot stars
Votruba, V; Kubát, J; Rätzel, D
2007-01-01
We have developed a time-dependent two-component hydrodynamics code to simulate radiatively-driven stellar winds from hot stars. We use a time-explicit van Leer scheme to solve the hydrodynamic equations of a two-component stellar wind. Dynamical friction due to Coulomb collisions between the passive bulk plasma and the line-scattering ions is treated by a time-implicit, semi-analytic method using a polynomial fit to the Chandrasekhar function. This gives stable results despite the stiffness of the problem. This method was applied to model stars with winds that are both poorly and well-coupled. While for the former case we reproduce the mCAK solution, for the latter case our solution leads to wind decoupling.
Atomic Tunneling Effect in Two-Component Bose-Einstein Condensates with a Coupling Drive
Institute of Scientific and Technical Information of China (English)
JIAOZhi-Yong; YUZhao-Xian; YANGXin-Jian
2004-01-01
In this paper, we have studied the atomic population difference and the atomic tunneling current of two-component Bose-Einstein condensates with a coupling drive. It is found that when the two-component Bose Einstein condensates are initially in the coherent states, the atomic population difference may exhibit the step structure, in which the numbers of the step increase with the decrease of the Rabi frequency and with the increment of the initial phase difference. The atomic population difference may exhibit collapses, and revivals, in which their periods are affected dramatically by the Rabi frequency and the initial phase difference. The atomic tunneling current may exhibit damping oscillation behaviors, and exist the step structure for the time range of 10-10 ～ 10-9 second.
Two-component Fermi-liquid theory - Equilibrium properties of liquid metallic hydrogen
Oliva, J.; Ashcroft, N. W.
1981-01-01
It is reported that the transition of condensed hydrogen from an insulating molecular crystal phase to a metallic liquid phase, at zero temperature and high pressure, appears possible. Liquid metallic hydrogen (LMH), comprising interpenetrating proton and electron fluids, would constitute a two-component Fermi liquid with both a very high component-mass ratio and long-range, species-dependent bare interactions. The low-temperature equilibrium properties of LMH are examined by means of a generalization to the case of two components of the phenomenological Landau Fermi-liquid theory, and the low-temperature specific heat, compressibility, thermal expansion coefficient and spin susceptibility are given. It is found that the specific heat and the thermal expansion coefficient are vastly greater in the liquid than in the corresponding solid, due to the presence of proton quasiparticle excitations in the liquid.
Engineering bacterial two-component system PmrA/PmrB to sense lanthanide ions.
Liang, Haihua; Deng, Xin; Bosscher, Mike; Ji, Quanjiang; Jensen, Mark P; He, Chuan
2013-02-13
The Salmonella PmrA/PmrB two-component system uses an iron(III)-binding motif on the cell surface to sense the environmental or host ferric level and regulate PmrA-controlled gene expression. We replaced the iron(III)-binding motif with a lanthanide-binding peptide sequence that is known to selectively recognize trivalent lanthanide ions. The newly engineered two-component system (PmrA/PmrB) can effectively sense lanthanide ion and regulate gene expression in E. coli . This work not only provides the first known lanthanide-based sensing and response in live cells but also demonstrates that the PmrA/PmrB system is a suitable template for future synthetic biology efforts to construct bacteria that can sense and respond to other metal ions in remediation or sequestration.
A two-component Frenkel-Kontorowa model for surface alloy formation
Daruka, I
2003-01-01
It has been shown by recent experiments that bulk immiscible metals (e.g. Ag/Cu, Ag/Co and Au/Ni) can form binary alloys on certain surfaces where the substrate mediates the elastic misfits between the two components, thus relieving the elastic strain in the overlayer. These novel surface alloys exhibit a rich phase structure. We formulate a two-component Frenkel-Kontorova model in one dimension to study surface alloy formation. This model can naturally incorporate dislocation formation that plays a crucial role in determining the actual structure of the system. Using energy minimization calculations we provide a phase diagram in terms of average alloy composition and the energy of mixing. Monte Carlo simulations were also performed to study the structure and interaction of the emerging dislocations.
Energy Technology Data Exchange (ETDEWEB)
Xu, Fei [Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070 (China); Huang, Jiahao, E-mail: hjiahao@mail2.sysu.edu.cn [TianQin Research Center & School of Physics and Astronomy, Sun Yat-Sen University, SYSU Zhuhai Campus, Zhuhai 519082 (China); Liu, Quan [Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070 (China)
2017-03-03
Highlights: • A scheme for detecting magnetic field gradients via a double-well two-component Bose–Einstein condensate interferometer. • The magnetic field gradient can be extracted by either the spin population or the external state. • Our proposal is potentially sensitive to weak magnetic field inhomogeneity due to its small sensor size. - Abstract: We have proposed a scheme to detect magnetic field gradients via an interferometer based on a double-well two-component Bose–Einstein condensate (BEC). Utilizing a sequence of quantum control operations on both external and internal degree of the BEC, one can extract the magnetic field gradients by measuring either the population in one component or the fidelity between the final external state and the initial ground state. Our scheme can be implemented by current experimental techniques of manipulating ultracold atoms.
Kinetics and mechanism of the oxidation process of two-component Fe-Al alloys
Przewlocka, H.; Siedlecka, J.
1982-01-01
The oxidation process of two-component Fe-Al alloys containing up to 7.2% Al and from 18 to 30% Al was studied. Kinetic measurements were conducted using the isothermal gravimetric method in the range of 1073-1223 K and 1073-1373 K for 50 hours. The methods used in studies of the mechanism of oxidation included: X-ray microanalysis, X-ray structural analysis, metallographic analysis and marker tests.
In vivo study of the two-component signaling network in Escherichia coli
Sommer, Erik
2012-01-01
Microorganisms commonly use ‘two-component’ signaling systems for sensing environmental conditions, with members being present in nearly all bacterial and archaeal genomes in different numbers. Prototypical two-component systems are comprised of a sensory histidine kinase and a response regulator protein that is phosphorylated by the kinase. The regulator typically acts as a transcription factor regulating gene expression. Due to their prevalence in microorganisms, a basic understanding of th...
Directory of Open Access Journals (Sweden)
Christian H Bell
2010-02-01
Full Text Available Two-component signal transduction pathways comprising histidine protein kinases (HPKs and their response regulators (RRs are widely used to control bacterial responses to environmental challenges. Some bacteria have over 150 different two-component pathways, and the specificity of the phosphotransfer reactions within these systems is tightly controlled to prevent unwanted crosstalk. One of the best understood two-component signalling pathways is the chemotaxis pathway. Here, we present the 1.40 A crystal structure of the histidine-containing phosphotransfer domain of the chemotaxis HPK, CheA(3, in complex with its cognate RR, CheY(6. A methionine finger on CheY(6 that nestles in a hydrophobic pocket in CheA(3 was shown to be important for the interaction and was found to only occur in the cognate RRs of CheA(3, CheY(6, and CheB(2. Site-directed mutagenesis of this methionine in combination with two adjacent residues abolished binding, as shown by surface plasmon resonance studies, and phosphotransfer from CheA(3-P to CheY(6. Introduction of this methionine and an adjacent alanine residue into a range of noncognate CheYs, dramatically changed their specificity, allowing protein interaction and rapid phosphotransfer from CheA(3-P. The structure presented here has allowed us to identify specificity determinants for the CheA-CheY interaction and subsequently to successfully reengineer phosphotransfer signalling. In summary, our results provide valuable insight into how cells mediate specificity in one of the most abundant signalling pathways in biology, two-component signal transduction.
Two-component model of the interaction of an interstellar cloud with surrounding hot plasma
Provornikova, E. A.; Izmodenov, V. V.; Lallement, R.
2011-01-01
We present a two-component gasdynamic model of an interstellar cloud embedded in a hot plasma. It is assumed that the cloud consists of atomic hydrogen gas, interstellar plasma is quasineutral. Hydrogen atoms and plasma protons interact through a charge exchange process. Magnetic felds and radiative processes are ignored in the model. The influence of heat conduction within plasma on the interaction between a cloud and plasma is studied. We consider the extreme case and assume that hot plasma...
General aspects of two-component regulatory circuits in bacteria: Domains, signals and roles.
Padilla-Vaca, Felipe; Mondragón-Jaimes, Verónica; Franco, Bernardo
2016-08-09
All living organisms are subject to changing environments, which must be sensed in order to respond swiftly and efficiently. Two-component systems (TCS) are signal transduction regulatory circuits based typically on a membrane bound sensor kinase and a cytoplasmic response regulator, that is activated through a histidine to aspartate phosphorelay reactions. Activated response regulator acts usually as a transcription factor. The best known examples were identified in bacteria, but they are also found in fungi, algae and plants. Thus far, they are not found in mammals. Regulatory circuits coupled to two-component systems exhibit a myriad of responses to environmental stimuli such as: redox potential, pH, specific metabolites, pressure, light and more recently to specific antimicrobial peptides that activate a sensor kinase responsible for expressing virulence factors through the active response regulator. In this review we explore general aspects on two-component systems that ultimately can play a role on virulence regulation, also the intriguing domain properties of the sensor kinases that can be a potential target for antimicrobial compounds. Only a handful of sensor kinases are extensively characterized, the vast majority belong to what we call 'the dark matter of bacterial signal transduction' since no known signal, structure and biochemical properties are available. Regulatory circuits from vertebrate pathogenic organisms can explain virulence in terms of either response to environmental factors or specific niche occupancy. Hopefully, knowledge on these signal transduction systems can lead to identify novel molecules that target two-component systems, since the increase of drug resistant microorganisms is worrisome.
Histidine Phosphotransfer Proteins in Fungal Two-Component Signal Transduction Pathways
2013-01-01
The histidine phosphotransfer (HPt) protein Ypd1 is an important participant in the Saccharomyces cerevisiae multistep two-component signal transduction pathway and, unlike the expanded histidine kinase gene family, is encoded by a single gene in nearly all model and pathogenic fungi. Ypd1 is essential for viability in both S. cerevisiae and in Cryptococcus neoformans. These and other aspects of Ypd1 biology, combined with the availability of structural and mutational data in S. cerevisiae, s...
Institute of Scientific and Technical Information of China (English)
Zhang Xiao-Fei; Zhang Pei; He Wan-Quan; Liu Xun-Xu
2011-01-01
By using a unified theory of the formation of various types of vector-solitons in two-component Bose-Einstein condensates with tunable interactions, we obtain a family of exact vector-soliton solutions for the coupled nonlinear Schr(o)dinger equations. Moreover, the Bogoliubov equation shows that there exists stable dark soliton in specific situations. Our results open up new ways in considerable experimental interest for the quantum control of multi-component Bose-Einstein condensates.
Bloch Oscillations of Two-Component Bose-Einstein Condensates in Optical Lattices
Institute of Scientific and Technical Information of China (English)
GU Huai-Qiang; WANG Zhi-Cheng; JIN Kang; TAN Lei
2006-01-01
@@ We study the Bloch oscillations of two-component Bose-Einstein condensates trapped in spin-dependent optical lattices. The influence of the intercomponent atom interaction on the system is discussed in detail Accelerated breakdown of the Bloch oscillations and revival phenomena are found respectively for the repulsive and attractive case. For both the cases, the system will finally be set in a quantum self-trapping state due to dynamical instability.
The CpxRA two-component system is essential for Citrobacter rodentium virulence.
Thomassin, Jenny-Lee; Giannakopoulou, Natalia; Zhu, Lei; Gross, Jeremy; Salmon, Kristiana; Leclerc, Jean-Mathieu; Daigle, France; Le Moual, Hervé; Gruenheid, Samantha
2015-05-01
Citrobacter rodentium is a murine intestinal pathogen used as a model for the foodborne human pathogens enterohemorrhagic Escherichia coli and enteropathogenic E. coli. During infection, these pathogens use two-component signal transduction systems to detect and adapt to changing environmental conditions. In E. coli, the CpxRA two-component signal transduction system responds to envelope stress by modulating the expression of a myriad of genes. Quantitative real-time PCR showed that cpxRA was expressed in the colon of C57BL/6J mice infected with C. rodentium. To determine whether CpxRA plays a role during C. rodentium infection, a cpxRA deletion strain was generated and found to have a colonization defect during infection. This defect was independent of an altered growth rate or a defective type III secretion system, and single-copy chromosomal complementation of cpxRA restored virulence. The C. rodentium strains were then tested in C3H/HeJ mice, a lethal intestinal infection model. Mice infected with the ΔcpxRA strain survived infection, whereas mice infected with the wild-type or complemented strains succumbed to infection. Furthermore, we found that the cpxRA expression level was higher during early infection than at a later time point. Taken together, these data demonstrate that the CpxRA two-component signal transduction system is essential for the in vivo virulence of C. rodentium. In addition, these data suggest that fine-tuned cpxRA expression is important for infection. This is the first study that identifies a C. rodentium two-component transduction system required for pathogenesis. This study further indicates that CpxRA is an interesting target for therapeutics against enteric pathogens.
A Possible Two-Component Structure of the Non-Perturbative Pomeron
Gauron, P; Gauron, Pierre; Nicolescu, Basarab
2000-01-01
We propose a QCD-inspired two-component Pomeron form which gives an excellent description of the proton-proton, pi-proton, kaon-proton, gamma-proton and gamma-gamma total cross sections. Our fit has a better CHI2/dof for a smaller number of parameters as compared with the PDG fit. Our 2-Pomeron form is fully compatible with weak Regge exchange-degeneracy, universality, Regge factorization and the generalized vector dominance model.
Different electronic charges in two-component superconductor by coherent state
Energy Technology Data Exchange (ETDEWEB)
Shi, Xuguang, E-mail: shixg@bjfu.edu.cn
2015-07-17
Recently, the different electronic charges, which are related to the different coupling constants with magnetic field, in the two-component superconductor have been studied in the frame of Ginzburg–Landau theory. In order to study the electronic charges in detail we suggest the wave function in the two-component superconductor to be in the coherent state. We find the different electronic charges exist not only in the coherent state but also in the incoherent state. But the ratio of the different charges in the coherent state is different from the ratio in the incoherence. The expressions of the coupling constants are given directly based on the coherence effects. We also discuss the winding number in such a system. - Highlights: • Suggest the wave function in two-component superconductor is coherent. • Interpret the existence of different electric charges by the coherent states. • Derive a new expression for the supercurrent. • Reveal the relation between different electric charges and winding number.
Indian Academy of Sciences (India)
K V Srividhya; S Krishnaswamy
2007-08-01
Bacteriophage induced lysis of host bacterial cell is mediated by a two component cell lysis cassette comprised of holin and lysozyme. Prophages are integrated forms of bacteriophages in bacterial genomes providing a repertoire for bacterial evolution. Analysis using the prophage database (http://bicmku.in:8082) constructed by us showed 47 prophages were associated with putative two component cell lysis genes. These proteins cluster into four different subgroups. In this process, a putative holin (essd) and endolysin (ybcS), encoded by the defective lambdoid prophage DLP12 was found to be similar to two component cell lysis genes in functional bacteriophages like p21 and P1. The holin essd was found to have a characteristic dual start motif with two transmembrane regions and C-terminal charged residues as in class II holins. Expression of a fusion construct of essd in Escherichia coli showed slow growth. However, under appropriate conditions, this protein could be over expressed and purified for structure function studies. The second component of the cell lysis cassette, ybcS, was found to have an N-terminal SAR (Signal Arrest Release) transmembrane domain. The construct of ybcS has been over expressed in E. coli and the purified protein was functional, exhibiting lytic activity against E. coli and Salmonella typhi cell wall substrate. Such targeted sequence-structure-function characterization of proteins encoded by cryptic prophages will help understand the contribution of prophage proteins to bacterial evolution.
Design of Novel Mixer and Applicator for Two-Component Surgical Adhesives
Go, Kevin; Kim, Yeong; Lee, Andy H.; Staricha, Kelly; Messersmith, Phillip; Glucksberg, Matthew
2015-01-01
Current mixer and applicator devices on the market are not able to properly and efficiently mix two-component surgical adhesives in small volumes necessary to achieve economic viability. Furthermore, in these devices a significant amount of adhesive is wasted during the application process, as material within the dead space of the mixing chamber must be discarded. We have designed and demonstrated a new active mixer and applicator system capable of rapidly and efficiently mixing two components of an adhesive and applying it to the surgical site. Recently, Messersmith et al. have developed a tissue adhesive inspired by the mussel byssus and have shown that it is effective as a surgical sealant, and is especially suited for wet environments such as in fetal surgery. Like some other tissue sealants, this one requires that two components of differing viscosities be thoroughly mixed within a specified and short time period. Through a combination of compression and shear testing, we demonstrated that our device could effectively mix the adhesive developed by Messersmith et al. and improve its shear strength to significantly higher values than what has been reported for vortex mixing. Overall, our mixer and applicator system not only has potential applications in mixing and applying various adhesives in multiple surgical fields but also makes this particular adhesive viable for clinical use. PMID:26421090
Real time propagation of the exact two component time-dependent density functional theory
Goings, Joshua J.; Kasper, Joseph M.; Egidi, Franco; Sun, Shichao; Li, Xiaosong
2016-09-01
We report the development of a real time propagation method for solving the time-dependent relativistic exact two-component density functional theory equations (RT-X2C-TDDFT). The method is fundamentally non-perturbative and may be employed to study nonlinear responses for heavy elements which require a relativistic Hamiltonian. We apply the method to several group 12 atoms as well as heavy-element hydrides, comparing with the extensive theoretical and experimental studies on this system, which demonstrates the correctness of our approach. Because the exact two-component Hamiltonian contains spin-orbit operators, the method is able to describe the non-zero transition moment of otherwise spin-forbidden processes in non-relativistic theory. Furthermore, the two-component approach is more cost effective than the full four-component approach, with similar accuracy. The RT-X2C-TDDFT will be useful in future studies of systems containing heavy elements interacting with strong external fields.
Bioinformatics analysis of two-component regulatory systems in Staphylococcus epidermidis
Institute of Scientific and Technical Information of China (English)
QIN Zhiqiang; ZHONG Yang; ZHANG Jian; HE Youyu; WU Yang; JIANG Juan; CHEN Jiemin; LUO Xiaomin; QU Di
2004-01-01
Sixteen pairs of two-component regulatory systems are identified in the genome of Staphylococcus epidermidis ATCC12228 strain, which is newly sequenced by our laboratory for Medical Molecular Virology and Chinese National Human Genome Center at Shanghai, by using bioinformatics analysis. Comparative analysis of the twocomponent regulatory systems in S. epidermidis and that of S.aureus and Bacillus subtilis shows that these systems may regulate some important biological functions, e.g. growth,biofilm formation, and expression of virulence factors in S.epidermidis. Two conserved domains, i.e. HATPase_c and REC domains, are found in all 16 pairs of two-component proteins.Homologous modelling analysis indicates that there are 4similar HATPase_c domain structures of histidine kinases and 13 similar REC domain structures of response regulators,and there is one AMP-PNP binding pocket in the HATPase_c domain and three active aspartate residues in the REC domain. Preliminary experiment reveals that the bioinformatics analysis of the conserved domain structures in the two-component regulatory systems in S. epidermidis may provide useful information for discovery of potential drug target.
Multiple extended target tracking algorithm based on Gaussian surface matrix
Institute of Scientific and Technical Information of China (English)
Jinlong Yang; Peng Li; Zhihua Li; Le Yang
2016-01-01
In this paper, we consider the problem of irregular shapes tracking for multiple extended targets by introducing the Gaussian surface matrix (GSM) into the framework of the random finite set (RFS) theory. The Gaussian surface function is constructed first by the measurements, and it is used to define the GSM via a mapping function. We then integrate the GSM with the probability hypothesis density (PHD) filter, the Bayesian recursion formulas of GSM-PHD are derived and the Gaussian mixture implementation is employed to obtain the closed-form solutions. Moreover, the estimated shapes are designed to guide the measurement set sub-partition, which can cope with the problem of the spatialy close target tracking. Simulation results show that the proposed algorithm can effectively estimate irregular target shapes and exhibit good robustness in cross extended target tracking.
Muzamal, Uzma; Gomez, Daniel; Kapadia, Fenika; Golemi-Kotra, Dasantila
2014-01-01
The response to cationic antimicrobial peptides (CAMPs) in Staphylococcus aureus relies on a two-component system (TCS), GraSR, an auxiliary protein GraX and an ATP-binding cassette (ABC) transporter, VraF/G. To understand the signal transduction mechanism by GraSR, we investigated the kinase activity of the cytoplasmic domain of histidine kinase GraS and the interaction with its cognate response regulator GraR. We also investigated interactions among the auxiliary protein GraX, GraS/R and the ATPase protein of the ABC transporter, VraF. We found that GraS lacks autophosphorylation activity, unlike a similar histidine kinase, BceS, of Bacillus subtilis. In addition, the interaction between GraS and GraR is very weak in comparison to the stronger interaction observed between BceS and its conjugated response regulator, BceR, suggesting that CAMP signaling may not flow directly from GraS to GraR. We found that the auxiliary protein GraX interacts with VraF and GraR, and requires the histidine phosphotransfer and dimerization domain of GraS to interact with this protein. Further, VraF requires the GraS region that connects the membrane-bound domain with the cytoplasmic domain of this protein for interaction with GraS. The interactions of GraX with GraS/R and VraF indicate that GraX may serve as a scaffold to bring these proteins in close proximity to GraS, plausibly to facilitate activation of GraS to ultimately transduce the signal to GraR.
Quantification of Gaussian quantum steering
Kogias, Ioannis; Ragy, Sammy; Adesso, Gerardo
2014-01-01
Einstein-Podolsky-Rosen steering incarnates a useful nonclassical correlation which sits in-between entanglement and Bell nonlocality. While a number of qualitative steering criteria exist, very little has been achieved for what concerns quantifying steerability. We introduce a computable measure of steering for arbitrary bipartite Gaussian states of continuous variable systems. For two-mode Gaussian states, the measure reduces to a form of coherent information, which is proven never to exceed entanglement, and to reduce to it on pure states. We provide an operational connection between our measure and the key rate in one-sided device-independent quantum key distribution. We further prove that steering bound entangled Gaussian states by Gaussian measurements is impossible.
Gaussian maximally multipartite entangled states
Facchi, Paolo; Lupo, Cosmo; Mancini, Stefano; Pascazio, Saverio
2009-01-01
We introduce the notion of maximally multipartite entangled states (MMES) in the context of Gaussian continuous variable quantum systems. These are bosonic multipartite states that are maximally entangled over all possible bipartitions of the system. By considering multimode Gaussian states with constrained energy, we show that perfect MMESs, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of MMESs and their frustration for n <= 7.
Overlay Spectrum Sharing using Improper Gaussian Signaling
Amin, Osama
2016-11-30
Improper Gaussian signaling (IGS) scheme has been recently shown to provide performance improvements in interference limited networks as opposed to the conventional proper Gaussian signaling (PGS) scheme. In this paper, we implement the IGS scheme in overlay cognitive radio system, where the secondary transmitter broadcasts a mixture of two different signals. The first signal is selected from the PGS scheme to match the primary message transmission. On the other hand, the second signal is chosen to be from the IGS scheme in order to reduce the interference effect on the primary receiver. We then optimally design the overlay cognitive radio to maximize the secondary link achievable rate while satisfying the primary network quality of service requirements. In particular, we consider full and partial channel knowledge scenarios and derive the feasibility conditions of operating the overlay cognitive radio systems. Moreover, we derive the superiority conditions of the IGS schemes over the PGS schemes supported with closed form expressions for the corresponding power distribution and the circularity coefficient and parameters. Simulation results are provided to support our theoretical derivations.
Statistically tuned Gaussian background subtraction technique for UAV videos
Indian Academy of Sciences (India)
R Athi Lingam; K Senthil Kumar
2014-08-01
Background subtraction is one of the efficient techniques to segment the targets from non-informative background of a video. The traditional background subtraction technique suits for videos with static background whereas the video obtained from unmanned aerial vehicle has dynamic background. Here, we propose an algorithm with tuning factor and Gaussian update for surveillance videos that suits effectively for aerial videos. The tuning factor is optimized by extracting the statistical features of the input frames.With the optimized tuning factor and Gaussian update an adaptive Gaussian-based background subtraction technique is proposed. The algorithm involves modelling, update and subtraction phases. This running Gaussian average based background subtraction technique uses updation at both model generation phase and subtraction phase. The resultant video extracts the moving objects from the dynamic background. Sample videos of various properties such as cluttered background, small objects, moving background and multiple objects are considered for evaluation. The technique is statistically compared with frame differencing technique, temporal median method and mixture of Gaussian model and performance evaluation is done to check the effectiveness of the proposed technique after optimization for both static and dynamic videos.
Shear viscosity of liquid mixtures Mass dependence
Kaushal, R
2002-01-01
Expressions for zeroth, second, and fourth sum rules of transverse stress autocorrelation function of two component fluid have been derived. These sum rules and Mori's memory function formalism have been used to study shear viscosity of Ar-Kr and isotopic mixtures. It has been found that theoretical result is in good agreement with the computer simulation result for the Ar-Kr mixture. The mass dependence of shear viscosity for different mole fraction shows that deviation from ideal linear model comes even from mass difference in two species of fluid mixture. At higher mass ratio shear viscosity of mixture is not explained by any of the emperical model.
Predictions of Phase Distribution in Liquid-Liquid Two-Component Flow
Wang, Xia; Sun, Xiaodong; Duval, Walter M.
2011-06-01
Ground-based liquid-liquid two-component flow can be used to study reduced-gravity gas-liquid two-phase flows provided that the two liquids are immiscible with similar densities. In this paper, we present a numerical study of phase distribution in liquid-liquid two-component flows using the Eulerian two-fluid model in FLUENT, together with a one-group interfacial area transport equation (IATE) that takes into account fluid particle interactions, such as coalescence and disintegration. This modeling approach is expected to dynamically capture changes in the interfacial structure. We apply the FLUENT-IATE model to a water-Therminol 59® two-component vertical flow in a 25-mm inner diameter pipe, where the two liquids are immiscible with similar densities (3% difference at 20°C). This study covers bubbly (drop) flow and bubbly-to-slug flow transition regimes with area-averaged void (drop) fractions from 3 to 30%. Comparisons of the numerical results with the experimental data indicate that for bubbly flows, the predictions of the lateral phase distributions using the FLUENT-IATE model are generally more accurate than those using the model without the IATE. In addition, we demonstrate that the coalescence of fluid particles is dominated by wake entrainment and enhanced by increasing either the continuous or dispersed phase velocity. However, the predictions show disagreement with experimental data in some flow conditions for larger void fraction conditions, which fall into the bubbly-to-slug flow transition regime. We conjecture that additional fluid particle interaction mechanisms due to the change of flow regimes are possibly involved.
Specificity residues determine binding affinity for two-component signal transduction systems.
Willett, Jonathan W; Tiwari, Nitija; Müller, Susanne; Hummels, Katherine R; Houtman, Jon C D; Fuentes, Ernesto J; Kirby, John R
2013-11-05
Two-component systems (TCS) comprise histidine kinases and their cognate response regulators and allow bacteria to sense and respond to a wide variety of signals. Histidine kinases (HKs) phosphorylate and dephosphorylate their cognate response regulators (RRs) in response to stimuli. In general, these reactions appear to be highly specific and require an appropriate association between the HK and RR proteins. The Myxococcus xanthus genome encodes one of the largest repertoires of signaling proteins in bacteria (685 open reading frames [ORFs]), including at least 127 HKs and at least 143 RRs. Of these, 27 are bona fide NtrC-family response regulators, 21 of which are encoded adjacent to their predicted cognate kinases. Using system-wide profiling methods, we determined that the HK-NtrC RR pairs display a kinetic preference during both phosphotransfer and phosphatase functions, thereby defining cognate signaling systems in M. xanthus. Isothermal titration calorimetry measurements indicated that cognate HK-RR pairs interact with dissociation constants (Kd) of approximately 1 µM, while noncognate pairs had no measurable binding. Lastly, a chimera generated between the histidine kinase, CrdS, and HK1190 revealed that residues conferring phosphotransfer and phosphatase specificity dictate binding affinity, thereby establishing discrete protein-protein interactions which prevent cross talk. The data indicate that binding affinity is a critical parameter governing system-wide signaling fidelity for bacterial signal transduction proteins. Using in vitro phosphotransfer and phosphatase profiling assays and isothermal titration calorimetry, we have taken a system-wide approach to demonstrate specificity for a family of two-component signaling proteins in Myxococcus xanthus. Our results demonstrate that previously identified specificity residues dictate binding affinity and that phosphatase specificity follows phosphotransfer specificity for cognate HK-RR pairs. The data
Directory of Open Access Journals (Sweden)
Daniel Rozas
Full Text Available BACKGROUND: Bacterial two-component signal transduction regulatory systems are the major set of signalling proteins frequently mediating responses to changes in the environment. They typically consist of a sensor, a membrane-associated histidine kinase and a cytoplasmic response regulator. The membrane-associated sensor detects the environmental signal or stress, whereas the cytoplasmic regulatory protein controls the cellular response usually by gene transcription modulation. METHODOLOGY/PRINCIPALFINDINGS: The Streptomyces coelicolor two genes operon SCO5784-SCO5785 encodes a two-component system, where SCO5784 encodes a histidine-kinase sensor and SCO5785 encodes a response regulator protein. When the expression level of the regulator gene decreases, the antibiotic synthesis and sporulation is delayed temporarily in addition to some ribosomal genes became up regulated, whereas the propagation of the regulatory gene in high copy number results in the earlier synthesis of antibiotics and sporulation, as well as the down regulation of some ribosomal genes and, moreover, in the overproduction of several extracellular proteins. Therefore, this two-component system in S. coelicolor seems to influence various processes characterised by the transition from primary to secondary metabolism, as determined by proteomic and transcriptomic analyses. CONCLUSIONS/SIGNIFICANCE: Propagation of SCO5785 in multicopy enhances the production of antibiotics as well as secretory proteins. In particular, the increase in the expression level of secretory protein encoding genes, either as an artefactual or real effect of the regulator, could be of potential usefulness when using Streptomyces strains as hosts for homologous or heterologous extracellular protein production.
Analytical solution and meaning of feasible regions in two-component three-way arrays.
Omidikia, Nematollah; Abdollahi, Hamid; Kompany-Zareh, Mohsen; Rajkó, Róbert
2016-10-01
Although many efforts have been directed to the development of approximation methods for determining the extent of feasible regions in two- and three-way data sets; analytical determination (i.e. using only finite-step direct calculation(s) instead of the less exact numerical ones) of feasible regions in three-way arrays has remained unexplored. In this contribution, an analytical solution of trilinear decomposition is introduced which can be considered as a new direct method for the resolution of three-way two-component systems. The proposed analytical calculation method is applied to the full rank three-way data array and arrays with rank overlap (a type of rank deficiency) loadings in a mode. Close inspections of the analytically calculated feasible regions of rank deficient cases help us to make clearer the information gathered from multi-way problems frequently emerged in physics, chemistry, biology, agricultural, environmental and clinical sciences, etc. These examinations can also help to answer, e.g., the following practical question: "Is two-component three-way data with proportional loading in a mode actually a three-way data array?" By the aid of the additional information resulted from the investigated feasible regions of two-component three-way data arrays with proportional profile in a mode, reasons for the inadequacy of the seemingly trilinear data treatment methods published in the literature (e.g., U-PLS/RBL-LD that was used for extraction of quantitative and qualitative information reported by Olivieri et al. (Anal. Chem. 82 (2010) 4510-4519)) could be completely understood.
Design principles in two component systems and his-asp phosphorelays
Salvadó López, Baldiri
2016-01-01
L’objectiu d’aquesta tesi és trobar principis generals que permetin relacionar l’estructura i les propietats funcionals dels circuits moleculars de transducció de senyals two-component systems (TCS) i his-asp phosphorelays (PR). La tesi s’inicia revisant els mètodes usats per a l’estudi de principis de disseny en sistemes moleculars i alguns dels resultats obtinguts fins ara, i discutint la importància de l’estudi dels principis de disseny. A continuació, explorem els proteomes seqüenc...
On the inspection policy of a two-component parallel system with failure interaction
Energy Technology Data Exchange (ETDEWEB)
Zequeira, Romulo I. [ISTIT, Equipe Modelisation et Surete des Systemes, Universite de Technologie de Troyes, 12 Rue Marie Curie, BP 2060, 10010 Troyes Cedex (France)]. E-mail: romulo.zequeira@utt.fr; Berenguer, Christophe [ISTIT, Equipe Modelisation et Surete des Systemes, Universite de Technologie de Troyes, 12 Rue Marie Curie, BP 2060, 10010 Troyes Cedex (France)]. E-mail: christophe.berenguer@utt.fr
2005-04-01
In this paper we study a two-component standby system which can successfully operate upon a demand if at least one component is not failed. We assume that failures can be detected only by periodic inspections. We consider that the failure of one component can modify the (conditional) failure probability of the component still alive with probability p and do not interact with probability 1-p. For that failure interaction scheme we obtain the system reliability function for the case of staggered inspections. We compare staggered and non-staggered inspections through numerical examples considering constant hazard rates.
Optimization and control of two-component radially self-accelerating beams
Energy Technology Data Exchange (ETDEWEB)
Vetter, Christian; Eichelkraut, Toni; Ornigotti, Marco; Szameit, Alexander [Institute of Applied Physics, Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Albert-Einstein-Str. 15, 07745 Jena (Germany)
2015-11-23
We report on the properties of radially self-accelerating intensity distributions consisting of two components in the angular frequency domain. We show how this subset of solutions, in literature also known as helicon beams, possesses peculiar characteristics that enable a better control over its properties. In this work, we present a step-by-step optimization procedure to achieve the best possible intensity contrast, a distinct rotation rate and long propagation lengths. All points are discussed on a theoretical basis and are experimentally verified.
Modulational instability for a self-attractive two-component Bose-Einstein condensate
Institute of Scientific and Technical Information of China (English)
Li Sheng-Chang; Duan Wen-Shan
2009-01-01
By means of the multiple-scale expansion method, the coupled nonlinear Schr(o)dinger equations without an explicit external potential are obtained in two-dimensional geometry for a self-attractive Bose-Einstein condensate composed of different hyperfine states. The modulational instability of two-component condensate is investigated by using a simple technique. Based on the discussion about two typical cases, the explicit expression of the growth rate for a purely growing modulational instability and the optimum stable conditions are given and analysed analytically. The results show that the modulational instability of this two-dimensional system is quite different from that in a one-dimensional system.
Mapping the Two-Component Atomic Fermi Gas to the Nuclear Shell-Model
DEFF Research Database (Denmark)
Özen, C.; Zinner, Nikolaj Thomas
2014-01-01
The physics of a two-component cold fermi gas is now frequently addressed in laboratories. Usually this is done for large samples of tens to hundreds of thousands of particles. However, it is now possible to produce few-body systems (1-100 particles) in very tight traps where the shell structure...... of the external potential becomes important. A system of two-species fermionic cold atoms with an attractive zero-range interaction is analogous to a simple model of nucleus in which neutrons and protons interact only through a residual pairing interaction. In this article, we discuss how the problem of a two...
Xu, Fei; Huang, Jiahao; Liu, Quan
2017-03-01
We have proposed a scheme to detect magnetic field gradients via an interferometer based on a double-well two-component Bose-Einstein condensate (BEC). Utilizing a sequence of quantum control operations on both external and internal degree of the BEC, one can extract the magnetic field gradients by measuring either the population in one component or the fidelity between the final external state and the initial ground state. Our scheme can be implemented by current experimental techniques of manipulating ultracold atoms.
Topological phases of two-component bosons in species-dependent artificial gauge potentials
Wu, Ying-Hai; Shi, Tao
2016-08-01
We study bosonic atoms with two internal states in artificial gauge potentials whose strengths are different for the two components. A series of topological phases for such systems is proposed using the composite fermion theory and the parton construction. It is found in exact diagonalization that some of the proposed states may be realized for simple contact interaction between bosons. The ground states and low-energy excitations of these states are modeled using trial wave functions. The effective field theories for these states are also constructed and reveal some interesting properties.
Mapping the Two-Component Atomic Fermi Gas to the Nuclear Shell-Model
DEFF Research Database (Denmark)
Özen, C.; Zinner, Nikolaj Thomas
2014-01-01
of the external potential becomes important. A system of two-species fermionic cold atoms with an attractive zero-range interaction is analogous to a simple model of nucleus in which neutrons and protons interact only through a residual pairing interaction. In this article, we discuss how the problem of a two......-component atomic fermi gas in a tight external trap can be mapped to the nuclear shell model so that readily available many-body techniques in nuclear physics, such as the Shell Model Monte Carlo (SMMC) method, can be directly applied to the study of these systems. We demonstrate an application of the SMMC method...
Numerical simulation of two-component flow fluid - fluid in the microchannel T- type
Directory of Open Access Journals (Sweden)
Shebeleva A.A.
2015-01-01
Full Text Available Results of testing methodology for calculating two-phase flows based on the method of fluid in the cells (VOF method, and the procedure for CSF accounting of surface tension forces in the microchannel are considered in the work. Mathematical modeling of two-component flow fluid -fluid in the T- microchannel conducted using this methodology. The following flow regimes studied slug flow, rivulet flow, parallel flow, dispersed (droplet flow, plug flow. Comparison of numerical results with experimental data done. Satisfactory agreement between the calculated values with the experimental data obtained.
Two-component systems and their co-option for eukaryotic signal transduction.
Schaller, G Eric; Shiu, Shin-Han; Armitage, Judith P
2011-05-10
Two-component signaling pathways involve histidine kinases, response regulators, and sometimes histidine-containing phosphotransfer proteins. Prevalent in prokaryotes, these signaling elements have also been co-opted to meet the needs of signal transduction in eukaryotes such as fungi and plants. Here we consider the evolution of such regulatory systems, with a particular emphasis on the roles they play in signaling by the plant hormones cytokinin and ethylene, in phytochrome-mediated perception of light, and as integral components of the circadian clock. Copyright © 2011 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Anca Visinescu
2011-04-01
Full Text Available Using the multiple scales method, the interaction between two bright and one dark solitons is studied. Provided that a long wave-short wave resonance condition is satisfied, the two-component Zakharov-Yajima-Oikawa (ZYO completely integrable system is obtained. By using a Madelung fluid description, the one-soliton solutions of the corresponding ZYO system are determined. Furthermore, a discussion on the interaction between one bright and two dark solitons is presented. In particular, this problem is reduced to solve a one-component ZYO system in the resonance conditions.
Two-component colour dipole emission in the central region of onium-onium scattering
Peschanski, R
1995-01-01
The initial-state radiation of soft colour dipoles produced in the central region of onium-onium scattering via single QCD Pomeron exchange (BFKL) is calculated in the framework of Mueller's dipole approach. The resulting dipole production has a two-component structure. One is constant with energy while the other grows and possesses a power-law tail at appreciably large transverse distances from the collision axis. It may be related to the growth of the gluon distribution at small Bjorken-x.
Dynamics of bubbles in a two-component Bose-Einstein condensate
Sasaki, Kazuki; Suzuki, Naoya; Saito, Hiroki
2011-03-01
The dynamics of a phase-separated two-component Bose-Einstein condensate are investigated, in which a bubble of one component moves through the other component. Numerical simulations of the Gross-Pitaevskii equation reveal a variety of dynamics associated with the creation of quantized vortices. In two dimensions, a circular bubble deforms into an ellipse and splits into fragments with vortices, which undergo the Magnus effect. The Bénard-von Kármán vortex street is also generated. In three dimensions, a spherical bubble deforms into toruses with vortex rings. When two rings are formed, they exhibit leapfrogging dynamics.
Robinson, P. A.; Newman, D. L.
1990-01-01
A simple two-component model of strong turbulence that makes clear predictions for the scalings, spectra, and statistics of Langmuir waves is developed. Scalings of quantities such as energy density, power input, dissipation power wave collapse, and number density of collapsing objects are investigated in detail and found to agree well with model predictions. The nucleation model of wave-packet formation is strongly supported by the results. Nucleation proceeds with energy flowing from background to localized states even in the absence of a driver. Modulational instabilities play little or no role in maintaining the turbulent state when significant density nonuniformities are present.
The Two-Component Virial Theorem and the Physical Properties of Stellar Systems.
Dantas; Ribeiro; Capelato; de Carvalho RR
2000-01-01
Motivated by present indirect evidence that galaxies are surrounded by dark matter halos, we investigate whether their physical properties can be described by a formulation of the virial theorem that explicitly takes into account the gravitational potential term representing the interaction of the dark halo with the baryonic or luminous component. Our analysis shows that the application of such a "two-component virial theorem" not only accounts for the scaling relations displayed by, in particular, elliptical galaxies, but also for the observed properties of all virialized stellar systems, ranging from globular clusters to galaxy clusters.
Anisotropic pair superfluidity of trapped two-component Bose gases in an optical lattice
Li, Yongqiang; He, Liang; Hofstetter, Walter
2013-09-01
We theoretically investigate the pair-superfluid phase of two-component ultracold gases with attractive inter-species interactions in an optical lattice. We establish the phase diagram for filling n = 1 at zero and finite temperatures, by applying bosonic dynamical mean-field theory, and observe stable pair-superfluid and charge-density wave quantum phases for asymmetric hopping of the two species. While the pair superfluid is found to be robust in the presence of a harmonic trap, we observe that it is destroyed already by a small population imbalance of the two species.
Two-component Fermions in Optical Lattice with Spatially Alternating Interactions
Hoang, Anh-Tuan; Nguyen, Thi-Hai-Yen; Tran, Thi-Thu-Trang; Le, Duc-Anh
2016-10-01
We investigate two-component mass-imbalanced fermions in an optical lattice with spatially modulated interactions by using two-site dynamical mean field theory. At half-filling and zero temperature, the phase diagram of the system is analytically obtained, in which the metallic region is reduced with increasing the mass imbalance. The ground-state properties of the fermionic system are discussed from the behaviors of both the spin-dependent quasi-particle weight at the Fermi level and the double occupancy for each sublattice as functions of the local interaction strengths for various values of the mass imbalance.
National Research Council Canada - National Science Library
Skerker, Jeffrey M; Prasol, Melanie S; Perchuk, Barrett S; Biondi, Emanuele G; Laub, Michael T
2005-01-01
Two-component signal transduction systems, comprised of histidine kinases and their response regulator substrates, are the predominant means by which bacteria sense and respond to extracellular signals...
Two-component jet simulations: I. Topological stability of analytical MHD outflow solutions
Matsakos, T; Vlahakis, N; Massaglia, S; Mignone, A; Trussoni, E
2007-01-01
Observations of collimated outflows in young stellar objects indicate that several features of the jets can be understood by adopting the picture of a two-component outflow, wherein a central stellar component around the jet axis is surrounded by an extended disk-wind. The precise contribution of each component may depend on the intrinsic physical properties of the YSO-disk system as well as its evolutionary stage. In this context, the present article starts a systematic investigation of two-component jet models via time-dependent simulations of two prototypical and complementary analytical solutions, each closely related to the properties of stellar-outflows and disk-winds. These models describe a meridionally and a radially self-similar exact solution of the steady-state, ideal hydromagnetic equations, respectively. By using the PLUTO code to carry out the simulations, the study focuses on the topological stability of each of the two analytical solutions, which are successfully extended to all space by remo...
Arabidopsis ethylene-response gene ETR1: Similiarity of product to two-component regulators
Energy Technology Data Exchange (ETDEWEB)
Chang, C.; Kwok, S.F.; Bleecker, A.B.; Meyerowitz, E.M. (California Institute of Technology, Pasadena, CA (United States))
1993-10-22
Ethylene behaves as a hormone in plants, regulating such aspects of growth and development as fruit ripening, flower senescence, and abscission. Ethylene insensitivity is conferred by dominant mutations in the ETR1 gene early in the ethylene signal transduction pathway of Arabidopsis thaliana. The ETR1 gene was cloned by the method of chromosome walking. Each of the four known etr1 mutant alleles contains a missense mutation near the amino terminus of the predicted protein. Although the sequence of the amino-terminal half of the deduced ETR1 protein appears to be novel, the carboxyl-terminal half is similar in sequence to both components of the prokaryotic family of signal transducers known as the two-component systems. Thus, an early step in ethylene signal transduction in plants may involve transfer of phosphate as in prokaryotic two-component systems. The dominant etr1-1 mutant gene conferred ethylene insensitivity to wild-type Arabidopsis plants when introduced by transformation.
Directory of Open Access Journals (Sweden)
Qiang Lou
2014-01-01
Full Text Available Staphylococcus epidermidis, which is a causative pathogen of nosocomial infection, expresses its virulent traits such as biofilm and autolysis regulated by two-component signal transduction system SaeRS. In this study, we performed a proteomic analysis of differences in expression between the S. epidermidis 1457 wild-type and saeRS mutant to identify candidates regulated by saeRS using two-dimensional gel electrophoresis (2-DE combined with matrix-assisted laser desorption/lonization mass spectrometry (MALDI-TOF-MS. Of 55 identified proteins that significantly differed in expression between the two strains, 15 were upregulated and 40 were downregulated. The downregulated proteins included enzymes related to glycolysis and TCA cycle, suggesting that glucose is not properly utilized in S. epidermidis when saeRS was deleted. The study will be helpful for treatment of S. epidermidis infection from the viewpoint of metabolic modulation dependent on two-component signal transduction system SaeRS.
Two-component model of the interaction of an interstellar cloud with surrounding hot plasma
Provornikova, E A; Lallement, R
2011-01-01
We present a two-component gasdynamic model of an interstellar cloud embedded in a hot plasma. It is assumed that the cloud consists of atomic hydrogen gas, interstellar plasma is quasineutral. Hydrogen atoms and plasma protons interact through a charge exchange process. Magnetic felds and radiative processes are ignored in the model. The influence of heat conduction within plasma on the interaction between a cloud and plasma is studied. We consider the extreme case and assume that hot plasma electrons instantly heat the plasma in the interaction region and that plasma flow can be described as isothermal. Using the two-component model of the interaction of cold neutral cloud and hot plasma, we estimate the lifetime of interstellar clouds. We focus on the clouds typical for the cluster of local interstellar clouds embedded in the hot Local Bubble and give an estimate of the lifetime of the Local interstellar cloud where the Sun currently travels. The charge transfer between highly charged plasma ions and neutr...
Patient Autonomy for the Management of Chronic Conditions: A Two-Component Re-conceptualization
Naik, Aanand D.; Dyer, Carmel B.; Kunik, Mark E.; McCullough, Laurence B.
2010-01-01
The clinical application of the concept of patient autonomy has centered on the ability to deliberate and make treatment decisions (decisional autonomy) to the virtual exclusion of the capacity to execute the treatment plan (executive autonomy). However, the one-component concept of autonomy is problematic in the context of multiple chronic conditions. Adherence to complex treatments commonly breaks down when patients have functional, educational, and cognitive barriers that impair their capacity to plan, sequence, and carry out tasks associated with chronic care. The purpose of this article is to call for a two-component re-conceptualization of autonomy and to argue that the clinical assessment of capacity for patients with chronic conditions should be expanded to include both autonomous decision making and autonomous execution of the agreed-upon treatment plan. We explain how the concept of autonomy should be expanded to include both decisional and executive autonomy, describe the biopsychosocial correlates of the two-component concept of autonomy, and recommend diagnostic and treatment strategies to support patients with deficits in executive autonomy. PMID:19180389
Numerical analysis of a non equilibrium two-component two-compressible flow in porous media
Saad, Bilal Mohammed
2013-09-01
We propose and analyze a finite volume scheme to simulate a non equilibrium two components (water and hydrogen) two phase flow (liquid and gas) model. In this model, the assumption of local mass non equilibrium is ensured and thus the velocity of the mass exchange between dissolved hydrogen and hydrogen in the gas phase is supposed finite. The proposed finite volume scheme is fully implicit in time together with a phase-by-phase upwind approach in space and it is discretize the equations in their general form with gravity and capillary terms We show that the proposed scheme satisfies the maximum principle for the saturation and the concentration of the dissolved hydrogen. We establish stability results on the velocity of each phase and on the discrete gradient of the concentration. We show the convergence of a subsequence to a weak solution of the continuous equations as the size of the discretization tends to zero. At our knowledge, this is the first convergence result of finite volume scheme in the case of two component two phase compressible flow in several space dimensions.
Implications of Two-component Dark Matter Induced by Forbidden Channels and Thermal Freeze-out
Aoki, Mayumi
2016-01-01
We consider a model of two-component dark matter based on a hidden $U(1)_D$ symmetry, in which relic densities of the dark matter are determined by forbidden channels and thermal freeze-out. The hidden $U(1)_D$ symmetry is spontaneously broken to a residual $\\mathbb{Z}_4$ symmetry, and the lightest $\\mathbb{Z}_4$ charged particle can be a dark matter candidate. Moreover, depending on the mass hierarchy in the dark sector, we have two-component dark matter. We show that the relic density of the lighter dark matter component can be determined by forbidden annihilation channels which require larger couplings compared to the normal freeze-out mechanism. As a result, a large self-interaction of the lighter dark matter component can be induced, which may solve small scale problems of $\\Lambda$CDM model. On the other hand, the heavier dark matter component is produced by normal freeze-out mechanism. We find that interesting implications emerge between the two dark matter components in this framework. We explore dete...
Negative control in two-component signal transduction by transmitter phosphatase activity.
Huynh, TuAnh Ngoc; Stewart, Valley
2011-10-01
Bifunctional sensor transmitter modules of two-component systems exert both positive and negative control on the receiver domain of the cognate response regulator. In negative control, the transmitter module accelerates the rate of phospho-receiver dephosphorylation. This transmitter phosphatase reaction serves the important physiological functions of resetting response regulator phosphorylation level and suppressing cross-talk. Although the biochemical reactions underlying positive control are reasonably well understood, the mechanism for transmitter phosphatase activity has been unknown. A recent hypothesis is that the transmitter phosphatase reaction is catalysed by a conserved Gln, Asn or Thr residue, via a hydrogen bond between the amide or hydroxyl group and the nucleophilic water molecule in acyl-phosphate hydrolysis. This hypothetical mechanism closely resembles the established mechanisms of auxiliary phosphatases such as CheZ and CheX, and may be widely conserved in two-component signal transduction. In addition to the proposed catalytic residues, transmitter phosphatase activity also requires the correct transmitter conformation and appropriate interactions with the receiver. Evidence suggests that the phosphatase-competent and autokinase-competent states are mutually exclusive, and the corresponding negative and positive activities are likely to be reciprocally regulated through dynamic control of transmitter conformations. © 2011 Blackwell Publishing Ltd.
Mitrophanov, Alexander Y; Hadley, Tricia J; Groisman, Eduardo A
2010-08-27
Positive feedback loops are regulatory elements that can modulate expression output, kinetics and noise in genetic circuits. Transcriptional regulators participating in such loops are often expressed from two promoters, one constitutive and one autoregulated. Here, we investigate the interplay of promoter strengths and the intensity of the stimulus activating the transcriptional regulator in defining the output of a positively autoregulated genetic circuit. Using a mathematical model of two-component regulatory systems, which are present in all domains of life, we establish that positive feedback strongly affects the steady-state output levels at both low and high levels of stimulus if the constitutive promoter of the regulator is weak. By contrast, the effect of positive feedback is negligible when the constitutive promoter is sufficiently strong, unless the stimulus intensity is very high. Furthermore, we determine that positive feedback can affect both transient and steady state output levels even in the simplest genetic regulatory systems. We tested our modeling predictions by abolishing the positive feedback loop in the two-component regulatory system PhoP/PhoQ of Salmonella enterica, which resulted in diminished induction of PhoP-activated genes. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
Two-component vector solitons in defocusing Kerr-type media with spatially modulated nonlinearity
Energy Technology Data Exchange (ETDEWEB)
Zhong, Wei-Ping, E-mail: zhongwp6@126.com [Department of Electronic and Information Engineering, Shunde Polytechnic, Guangdong Province, Shunde 528300 (China); Texas A and M University at Qatar, P.O. Box 23874 Doha (Qatar); Belić, Milivoj [Texas A and M University at Qatar, P.O. Box 23874 Doha (Qatar); Institute of Physics, University of Belgrade, P.O. Box 57, 11001 Belgrade (Serbia)
2014-12-15
We present a class of exact solutions to the coupled (2+1)-dimensional nonlinear Schrödinger equation with spatially modulated nonlinearity and a special external potential, which describe the evolution of two-component vector solitons in defocusing Kerr-type media. We find a robust soliton solution, constructed with the help of Whittaker functions. For specific choices of the topological charge, the radial mode number and the modulation depth, the solitons may exist in various forms, such as the half-moon, necklace-ring, and sawtooth vortex-ring patterns. Our results show that the profile of such solitons can be effectively controlled by the topological charge, the radial mode number, and the modulation depth. - Highlights: • Two-component vector soliton clusters in defocusing Kerr-type media are reported. • These soliton clusters are constructed with the help of Whittaker functions. • The half-moon, necklace-ring and vortex-ring patterns are found. • The profile of these solitons can be effectively controlled by three soliton parameters.
Modeling and Simulation of Two-Phase Two-Component Flow with Disappearing Nonwetting Phase
Neumann, Rebecca; Ippisch, Olaf
2012-01-01
Carbon Capture and Storage (CCS) is a recently discussed new technology, aimed at allowing an ongoing use of fossil fuels while preventing the produced CO2 to be released to the atmosphere. CSS can be modeled with two components (water and CO2) in two phases (liquid and CO2). To simulate the process, a multiphase flow equation with equilibrium phase exchange is used. One of the big problems arising in two-phase two-component flow simulations is the disappearance of the nonwetting phase, which leads to a degeneration of the equations satisfied by the saturation. A standard choice of primary variables, which is the pressure of one phase and the saturation of the other phase, cannot be applied here. We developed a new approach using the pressure of the nonwetting phase and the capillary pressure as primary variables. One important advantage of this approach is the fact that we have only one set of primary variables that can be used for the biphasic as well as the monophasic case. We implemented this new choice o...
Features of protein-protein interactions in two-component signaling deduced from genomic libraries.
White, Robert A; Szurmant, Hendrik; Hoch, James A; Hwa, Terence
2007-01-01
As more and more sequence data become available, new approaches for extracting information from these data become feasible. This chapter reports on one such method that has been applied to elucidate protein-protein interactions in bacterial two-component signaling pathways. The method identifies residues involved in the interaction through an analysis of over 2500 functionally coupled proteins and a precise determination of the substitutional constraints placed on one protein by its signaling mate. Once identified, a simple log-likelihood scoring procedure is applied to these residues to build a predictive tool for assigning signaling mates. The ability to apply this method is based on a proliferation of related domains within multiple organisms. Paralogous evolution through gene duplication and divergence of two-component systems has commonly resulted in tens of closely related interacting pairs within one organism with a roughly one-to-one correspondence between signal and response. This provides us with roughly an order of magnitude more protein pairs than there are unique, fully sequenced bacterial species. Consequently, this chapter serves as both a detailed exposition of the method that has provided more depth to our knowledge of bacterial signaling and a look ahead to what would be possible on a more widespread scale, that is, to protein-protein interactions that have only one example per genome, as the number of genomes increases by a factor of 10.
Carrano, Charles S.; Rino, Charles L.
2016-06-01
We extend the power law phase screen theory for ionospheric scintillation to account for the case where the refractive index irregularities follow a two-component inverse power law spectrum. The two-component model includes, as special cases, an unmodified power law and a modified power law with spectral break that may assume the role of an outer scale, intermediate break scale, or inner scale. As such, it provides a framework for investigating the effects of a spectral break on the scintillation statistics. Using this spectral model, we solve the fourth moment equation governing intensity variations following propagation through two-dimensional field-aligned irregularities in the ionosphere. A specific normalization is invoked that exploits self-similar properties of the structure to achieve a universal scaling, such that different combinations of perturbation strength, propagation distance, and frequency produce the same results. The numerical algorithm is validated using new theoretical predictions for the behavior of the scintillation index and intensity correlation length under strong scatter conditions. A series of numerical experiments are conducted to investigate the morphologies of the intensity spectrum, scintillation index, and intensity correlation length as functions of the spectral indices and strength of scatter; retrieve phase screen parameters from intensity scintillation observations; explore the relative contributions to the scintillation due to large- and small-scale ionospheric structures; and quantify the conditions under which a general spectral break will influence the scintillation statistics.
Exact periodic wave and soliton solutions in two-component Bose-Einstein condensates
Institute of Scientific and Technical Information of China (English)
Li Hua-Mei
2007-01-01
We present several families of exact solutions to a system of coupled nonlinear Schr(o)dinger equations. The model describes a binary mixture of two Bose-Einstein condensates in a magnetic trap potential. Using a mapping deformation method, we find exact periodic wave and soliton solutions, including bright and dark soliton pairs.
Some aspects of symmetric Gamma process mixtures
Naulet, Zacharie; Barat, Eric
2015-01-01
In this article, we present some specific aspects of symmetric Gamma process mixtures for use in regression models. We propose a new Gibbs sampler for simulating the posterior and we establish adaptive posterior rates of convergence related to the Gaussian mean regression problem.
DEFF Research Database (Denmark)
Jers, Carsten; Kobir, Ahasanul; Søndergaard, Elsebeth Oline;
2011-01-01
Bacillus subtilis two-component system DegS/U is well known for the complexity of its regulation. The cytosolic sensory kinase DegS does not receive a single predominant input signal like most two-component kinases, instead it integrates a wide array of metabolic inputs that modulate its activity...
Institute of Scientific and Technical Information of China (English)
ZHANG Hong-Biao
2003-01-01
The eigenstates describing two-component Bose-Einstein condensates (BEC) with weakly excitations have been found, by using the SO(3,2) algebraic mean-field approximation. We show that the two-component modified BEC (see Eq (26)) possesses uniquely super-Poissonian distribution in a fixcd magnetic ficld along z direction. The distribution will be uncertain, if B ＝ 0.
Atomic Tunneling Effect in Two-Component Bose-Einstein Condensates with a Coupling Drive
Institute of Scientific and Technical Information of China (English)
JIAO Zhi-Yong; YU Zhao-Xian; YANG Xin-Jian
2004-01-01
In this paper, we have studied the atomic population difference and the atomic tunneling current of twocomponent Bose-Einstein condensates with a coupling drive. It is found that when the two-component Bose-Einstein condensates are initially in the coherent states, the atomic population difference may exhibit the step structure, in which the numbers of the step increase with the decrease of the Rabi frequency and with the increment of the initial phase difference. The atomic population difference may exhibit collapses, and revivals, in which their periods are affected dramatically by the Rabi frequency and the initial phase difference. The atomic tunneling current may exhibit damping oscillation behaviors, and exist the step structure for the time range of 10-10 ～ 10-9 second.
Global solutions for the two-component Camassa-Holm system
Grunert, K; Raynaud, X
2011-01-01
We prove existence of a global conservative solution of the Cauchy problem for the two-component Camassa-Holm (2CH) system on the line, allowing for nonvanishing and distinct asymptotics at plus and minus infinity. The solution is proven to be smooth as long as the density is bounded away from zero. Furthermore, we show that by taking the limit of vanishing density in the 2CH system, we obtain the global conservative solution of the (scalar) Camassa-Holm equation, which provides a novel way to define and obtain these solutions. Finally, it is shown that while solutions of the 2CH system have infinite speed of propagation, singularities travel with finite speed.
The sae locus of Staphylococcus aureus encodes a two-component regulatory system.
Giraudo, A T; Calzolari, A; Cataldi, A A; Bogni, C; Nagel, R
1999-08-01
Sae is a regulatory locus that activates the production of several exoproteins in Staphylococcus aureus. A 3.4-kb fragment of a S. aureus genomic library, screened with a probe adjacent to the transposon insertion of a sae::Tn551 mutant, was cloned into a bifunctional vector. This fragment was shown to carry the sae locus by restoration of exoprotein production in sae mutants. The sae locus was mapped to the SmaI-D fragment of the staphylococcal chromosome by pulse-field electrophoresis. Sequence analysis of the cloned fragment revealed the presence of two genes, designated saeR and saeS, encoding a response regulator and a histidine protein kinase, respectively, with high homology to other bacterial two-component regulatory systems.
The curvature of semidirect product groups associated with two-component Hunter-Saxton systems
Kohlmann, Martin
2011-06-01
In this paper, we study two-component versions of the periodic Hunter-Saxton equation and its μ-variant. Considering both equations as a geodesic flow on the semidirect product of the circle diffeomorphism group Diff( S) with a space of scalar functions on S we show that both equations are locally well posed. The main result of this paper is that the sectional curvature associated with the 2HS is constant and positive and that 2µHS allows for a large subspace of positive sectional curvature. The issues of this paper are related to some of the results for 2CH and 2DP presented in Escher et al (2011 J. Geom. Phys. 61 436-52).
Feshbach P -Q partitioning technique and the two-component Dirac equation
Luo, Da-Wei; Pyshkin, P. V.; Yu, Ting; Lin, Hai-Qing; You, J. Q.; Wu, Lian-Ao
2016-09-01
We provide an alternative approach to relativistic dynamics based on the Feshbach projection technique. Instead of directly studying the Dirac equation, we derive a two-component equation for the upper spinor. This approach allows one to investigate the underlying physics in a different perspective. For particles with small mass such as the neutrino, the leading-order equation has a Hermitian effective Hamiltonian, implying there is no leakage between the upper and lower spinors. In the weak relativistic regime, the leading order corresponds to a non-Hermitian correction to the Pauli equation, which takes into account the nonzero possibility of finding the lower-spinor state and offers a more precise description.
Energy Spectrum of Two-Component Bose-Einstein Condensates in Optical Lattices
Institute of Scientific and Technical Information of China (English)
HAN Jiu-Rong; LIU Jin-Ming; JING Hui; WANG Yu-Zhu
2005-01-01
With the method of Green's function, we investigate the energy spectra of two-component ultracold bosonic atoms in optical lattices. We find that there are two energy bands for each component. The critical condition of the superfluid-Mott insulator phase transition is determined by the energy band structure. We also find that the nearest neighboring and on-site interactions fail to change the structure of energy bands, but shift the energy bands only.According to the conditions of the phase transitions, three stable superfluid and Mott insulating phases can be found by adjusting the experiment parameters. We also discuss the possibility of observing these new phases and their transitions in further experiments.
The SaeRS Two-Component System of Staphylococcus aureus
Liu, Qian; Yeo, Won-Sik; Bae, Taeok
2016-01-01
In the Gram-positive pathogenic bacterium Staphylococcus aureus, the SaeRS two-component system (TCS) plays a major role in controlling the production of over 20 virulence factors including hemolysins, leukocidins, superantigens, surface proteins, and proteases. The SaeRS TCS is composed of the sensor histidine kinase SaeS, response regulator SaeR, and two auxiliary proteins SaeP and SaeQ. Since its discovery in 1994, the sae locus has been studied extensively, and its contributions to staphylococcal virulence and pathogenesis have been well documented and understood; however, the molecular mechanism by which the SaeRS TCS receives and processes cognate signals is not. In this article, therefore, we review the literature focusing on the signaling mechanism and its interaction with other global regulators. PMID:27706107
Zhang, Shumeng; Hu, Yimin; Fan, Qingyun; Wang, Xun; He, Jin
2015-08-01
YvqEC is one of the two-component signal transduction systems that may respond to cell envelope stress and enable cells to adjust multiple cellular functions. It consists of a histidine kinase YvqE and a response regulator YvqC. In this study, we separately constructed a single gene mutant ΔyvqE and a double gene mutant ΔyvqEC in Bacillus thuringiensis BMB171 through a homing endonucleases I-SceI mediated markerless gene deletion method. We found that the deletion of either yvqE or yvqEC weakened the resistance of B. thuringiensis against vancomycin. We also identified nine operons that may be involved in the cellular metabolism regulated by YvqC. This study not only enriches our understanding of bacterial resistance mechanisms against vancomycin, but also helps investigate the functions of YvqEC.
Phase Separation and Dynamics of two-component Bose-Einstein condensates
Lee, Kean Loon; Liu, I-Kang; Wacker, Lars; Arlt, Jan J; Proukakis, Nick P
2016-01-01
The miscibility of two interacting quantum systems is an important testing ground for the understanding of complex quantum systems. Two-component Bose-Einstein condensates enable the investigation of this scenario in a particularly well controlled setting. In a homogeneous system, the transition between mixed and separated phases is fully characterised by a `miscibility parameter', based on the ratio of intra- to inter-species interaction strengths. Here we show, however, that this parameter is no longer the optimal one for trapped gases, for which the location of the phase boundary depends critically on atom numbers. We demonstrate how monitoring of damping rates and frequencies of dipole oscillations enables the experimental mapping of the phase diagram by numerical implementation of a fully self-consistent finite-temperature kinetic theory for binary condensates. The change in damping rate is explained in terms of surface oscillation in the immiscible regime, and counterflow instability in the miscible reg...
Addition Formulae of Discrete KP, q-KP and Two-Component BKP Systems
Gao, Xu; Li, Chuan-Zhong; He, Jing-Song
2016-04-01
In this paper, we construct the addition formulae for several integrable hierarchies, including the discrete KP, the q-deformed KP, the two-component BKP and the D type Drinfeld-Sokolov hierarchies. With the help of the Hirota bilinear equations and τ functions of different kinds of KP hierarchies, we prove that these addition formulae are equivalent to these hierarchies. These studies show that the addition formula in the research of the integrable systems has good universality. Supported by the Zhejiang Provincial Natural Science Foundation under Grant No. LY15A010004, the National Natural Science Foundation of China under Grant Nos. 11201251, 11571192 and the Natural Science Foundation of Ningbo under Grant No. 2015A610157. Jingsong He is supported by the National Natural Science Foundation of China under Grant No. 11271210, K.C. Wong Magna Fund in Ningbo University
Preparation of two component Fibrin Glue and its clinical evaluation in skin grafts and flaps
Directory of Open Access Journals (Sweden)
Jain P
2003-01-01
Full Text Available Tissue adhesive is one of the alternative to conventional suturing and has some added advantages. Fibrin glue has been used in obtaining haemostasis following trauma to spleen and liver. It has also been used in repair of dural tear and bronchial fistula. Fibrin glue is a biological tissue adhesive based on the final stage of coagulation wherein. Thrombin acting on fibrinogen converts it into fibrin. Thus, it has two components, one is fibrinogen and another is thrombin. We have prepared both components of fibrin glue. Fibrinogen was obtained from patient's own blood and thrombin from fresh frozen plasma of screened healthy donor. The glue was used in 20 cases requiring skin graft or flap. The results were compared with conventional suturing method. Use of the fibrin glue is simple, safe, cost effective, and rapid technique to fix the skin grafts and flaps with avoidance of peroperative bleeding and postoperative collection. It also has better overall results.
Dynamic form factor of two-component plasmas beyond the static local field approximation
Daligault, J
2003-01-01
The spectrum of ion density fluctuations in a strongly coupled plasma is described both within the static G(k, 0) and high-frequency G(k, infinity) local field approximation. By a direct comparison with molecular dynamics data, we find that for large coupling, G(k, 0) is inadequate. Based on this result, we employ the Zwanzig-Mori memory function approach to model the Thomson scattering cross section, i.e. the electron dynamic form factor S sub e sub e (k, omega) of a dense two-component plasma. We show the sensitivity of S sub e sub e (k, omega) to three approximations for G(k, omega).
PREPARATION OF PUZZOLANA ACTIVE TWO COMPONENT COMPOSITE FOR LATENT HEAT STORAGE
Directory of Open Access Journals (Sweden)
Jan Fort
2016-10-01
Full Text Available Application of Phase Change Materials (PCMs represents promising way for an increase of energy efficiency of industrial devices, reduction of energy demands for heating and cooling, waste heat recovery, solar energy storage and smart control of buildings interior climate. In this paper, the potential of diatomite as the bearer for the shape stable PCM was studied in order to develop material applicable in the mix composition of composite materials. Considering availability, endurance and compatibility of diatomite with the cement and lime based materials, preparation of diatomite/wax composite brings pozzolana active PCM with great promises at a reasonable cost. Prepared composite was analysed in detail using laser diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy and differential scanning calorimetry. Also the pozzolanic activity was measured. The prepared two components composite exhibits high latent heat storage and particle size distribution compatible with cement and hydrated lime.
WalRK two component system of Bacillus anthracis responds to temperature and antibiotic stress.
Dhiman, Alisha; Gopalani, Monisha; Bhatnagar, Rakesh
2015-04-17
WalRK Two Component System (TCS) of Bacillus anthracis forms a functional TCS. This report elaborates upon the WalRK genomic architecture, promoter structure, promoter activity and expression under various stress conditions in B. anthracis. 5' RACE located the WalRK functional promoter within 317 bp region upstream of WalR. Reporter gene assays demonstrated maximal promoter activity during early growth phases indicating utility in exponential stages of growth. qRT-PCR showed upregulation of WalRK transcripts during temperature and antibiotic stress. However, WalR overexpression did not affect the tested antibiotic MIC values in B. anthracis. Collectively, these results confirm that WalRK responds to cell envelope stress in B. anthracis.
Output Rate of Atomic Four-Wave Mixing in Two-Component Bose-Einstein Condensate
Institute of Scientific and Technical Information of China (English)
LI Jia-Hua; LI Wei-Bing; PENG Ju-Cun
2004-01-01
In this letter, following the proposal of Heurich et al. [Phys. Rev. A63 (2001) 033605], we analyze and discuss output rate of atomic four-wave mixing in the two-component Bose-Einstein condensate under the condition of the steady state. The results show that the magnitude of the signal beam increases with the increase of the intensity of the probe beam, up to a saturated value, then it decreases as the probe beam increases. The influence of the interaction range on the signal beam is also predicted. In particular, it is worth while pointing out that in contrast to the previous solutions, our obtained analytical solutions are of very simple and explicit forms, which open the door for further investigating the related physical mechanisms.
Genomic analysis of two-component signal transduction proteins in basidiomycetes.
Lavín, José L; Ramírez, Lucía; Ussery, David W; Pisabarro, Antonio G; Oguiza, José A
2010-01-01
Two-component system (TCS) proteins are components of complex signal transduction pathways in fungi, and play essential roles in the regulation of several cellular functions and responses. Species of basidiomycetes have a marked variation in their specific physiological traits, morphological complexity and lifestyles. In this study, we have used the available complete genomes of basidiomycetes to carry out a thorough identification and an extensive comparative analysis of the TCS proteins in this fungal phylum. In comparison with ascomycetes, basidiomycetes exhibit an intermediate number of TCS proteins. Several TCS proteins are highly conserved among all the basidiomycetes, and other TCS proteins appear to be specific to particular species of basidiomycetes. Moreover, some species appear to have developed a unique histidine kinase group with unusual domain architecture, the Dual-histidine kinases. The presence of differential sets of TCS proteins between basidiomycete species might reflect their adaptation to diverse environmental niches.
A two-component system regulates hemin acquisition in Porphyromonas gingivalis.
Directory of Open Access Journals (Sweden)
Jodie C Scott
Full Text Available Porphyromonas gingivalis is a Gram-negative oral anaerobe associated with infection of the periodontia. The organism has a small number of two-component signal transduction systems, and after comparing genome sequences of strains W83 and ATCC 33277 we discovered that the latter was mutant in histidine kinase (PGN_0752, while the cognate response regulator (PGN_0753 remained intact. Microarray-based transcriptional profiling and ChIP-seq assays were carried out with an ATCC 33277 transconjugant containing the functional histidine kinase from strain W83 (PG0719. The data showed that the regulon of this signal transduction system contained genes that were involved in hemin acquisition, including gingipains, at least three transport systems, as well as being self-regulated. Direct regulation by the response regulator was confirmed by electrophoretic mobility shift assays. In addition, the system appears to be activated by hemin and the regulator acts as both an activator and repressor.
Histidine phosphotransfer proteins in fungal two-component signal transduction pathways.
Fassler, Jan S; West, Ann H
2013-08-01
The histidine phosphotransfer (HPt) protein Ypd1 is an important participant in the Saccharomyces cerevisiae multistep two-component signal transduction pathway and, unlike the expanded histidine kinase gene family, is encoded by a single gene in nearly all model and pathogenic fungi. Ypd1 is essential for viability in both S. cerevisiae and in Cryptococcus neoformans. These and other aspects of Ypd1 biology, combined with the availability of structural and mutational data in S. cerevisiae, suggest that the essential interactions between Ypd1 and response regulator domains would be a good target for antifungal drug development. The goal of this minireview is to summarize the wealth of data on S. cerevisiae Ypd1 and to consider the potential benefits of conducting related studies in pathogenic fungi.
An intimate link: two-component signal transduction systems and metal transport systems in bacteria.
Singh, Kamna; Senadheera, Dilani B; Cvitkovitch, Dennis G
2014-01-01
Bacteria have evolved various strategies to contend with high concentrations of environmental heavy metal ions for rapid, adaptive responses to maintain cell viability. Evidence gathered in the past two decades suggests that bacterial two-component signal transduction systems (TCSTSs) are intimately involved in monitoring cation accumulation, and can regulate the expression of related metabolic and virulence genes to elicit adaptive responses to changes in the concentration of these ions. Using examples garnered from recent studies, we summarize the cross-regulatory relationships between metal ions and TCSTSs. We present evidence of how bacterial TCSTSs modulate metal ion homeostasis and also how metal ions, in turn, function to control the activities of these signaling systems linked with bacterial survival and virulence.
Two-component signal transduction as potential drug targets in pathogenic bacteria.
Gotoh, Yasuhiro; Eguchi, Yoko; Watanabe, Takafumi; Okamoto, Sho; Doi, Akihiro; Utsumi, Ryutaro
2010-04-01
Gene clusters contributing to processes such as cell growth and pathogenicity are often controlled by two-component signal transduction systems (TCSs). Specific inhibitors against TCS systems work differently from conventional antibiotics, and developing them into new drugs that are effective against various drug-resistant bacteria may be possible. Furthermore, inhibitors of TCSs that control virulence factors may reduce virulence without killing the pathogenic bacteria. Previous TCS inhibitors targeting the kinase domain of the histidine kinase sensor suffered from poor selectivity. Recent TCS inhibitors, however, target the sensory domains of the sensors blocking the quorum sensing system, or target the essential response regulator. These new targets are introduced, together with several specific TCSs that have the potential to serve as effective drug targets. Copyright 2010 Elsevier Ltd. All rights reserved.
Cross-talk and specificity in two-component signal transduction pathways.
Agrawal, Ruchi; Sahoo, Bikash Kumar; Saini, Deepak Kumar
2016-05-01
Two-component signaling systems (TCSs) are composed of two proteins, sensor kinases and response regulators, which can cross-talk and integrate information between them by virtue of high-sequence conservation and modular nature, to generate concerted and diversified responses. However, TCSs have been shown to be insulated, to facilitate linear signal transmission and response generation. Here, we discuss various mechanisms that confer specificity or cross-talk among TCSs. The presented models are supported with evidence that indicate the physiological significance of the observed TCS signaling architecture. Overall, we propose that the signaling topology of any TCSs cannot be predicted using obvious sequence or structural rules, as TCS signaling is regulated by multiple factors, including spatial and temporal distribution of the participating proteins.
Two-component hybrid time-dependent density functional theory within the Tamm-Dancoff approximation
Energy Technology Data Exchange (ETDEWEB)
Kühn, Michael [Institut für Physikalische Chemie, Karlsruher Institut für Technologie, Kaiserstraße 12, 76131 Karlsruhe (Germany); Weigend, Florian, E-mail: florian.weigend@kit.edu [Institut für Physikalische Chemie, Karlsruher Institut für Technologie, Kaiserstraße 12, 76131 Karlsruhe (Germany); Institut für Nanotechnologie, Karlsruher Institut für Technologie, Postfach 3640, 76021 Karlsruhe (Germany)
2015-01-21
We report the implementation of a two-component variant of time-dependent density functional theory (TDDFT) for hybrid functionals that accounts for spin-orbit effects within the Tamm-Dancoff approximation (TDA) for closed-shell systems. The influence of the admixture of Hartree-Fock exchange on excitation energies is investigated for several atoms and diatomic molecules by comparison to numbers for pure density functionals obtained previously [M. Kühn and F. Weigend, J. Chem. Theory Comput. 9, 5341 (2013)]. It is further related to changes upon switching to the local density approximation or using the full TDDFT formalism instead of TDA. Efficiency is demonstrated for a comparably large system, Ir(ppy){sub 3} (61 atoms, 1501 basis functions, lowest 10 excited states), which is a prototype molecule for organic light-emitting diodes, due to its “spin-forbidden” triplet-singlet transition.
Chatterjee, Arka; Ghosh, Himadri
2016-01-01
Two component advective flow (TCAF) successfully explains spectral and timing properties of black hole candidates. We study the nature of photon trajectories in the vicinity of a Schwarzschild black hole and incorporate this in predicting images of TCAF with a black hole at the Centre. We also compute the emitted spectra. We employ a Monte-Carlo simulation technique to achieve our goal. For accurate prediction of the image and the spectra, null trajectories are generated without constraining the motion to any specific plane. Red shift, bolometric flux and corresponding temperature have been calculated with appropriate relativistic consideration. The centrifugal barrier dominated boundary layer or CENBOL near the inner region of the disk which acts as the Compton cloud is appropriately modelled as a thick accretion disk in Schwarzschild geometry for the purpose of imaging and computing spectra. The variations of spectra and image with physical parameters such as the accretion rate ($\\dot{m}_d$) and inclination...
Correlations of the upper branch of 1D harmonically trapped two-component fermi gases.
Gharashi, Seyed Ebrahim; Blume, D
2013-07-26
We present highly accurate energy spectra and eigenfunctions of small 1D harmonically trapped two-component Fermi gases with interspecies δ-function interactions, and analyze the correlations of the so-called upper branch (i.e., the branch that describes a repulsive Fermi gas consisting of atoms but no molecules) for positive and negative coupling constants. Changes of the two-body correlations as a function of the interspecies coupling strength reflect the competition of the interspecies interaction and the effective repulsion due to the Pauli exclusion principle, and are interpreted as a few-body analog of a transition from a nonmagnetic to a magnetic phase. Moreover, we show that the eigenstate ψadia of the infinitely strongly interacting system with |n1+n2|>2 and |n1-n2|Fermi-Fermi mapping function to the eigenfunction of the noninteracting single-component Fermi gas.
Sin, Kuek Jia; Cheong, Chin Wen; Hooi, Tan Siow
2017-04-01
This study aims to investigate the crude oil volatility using a two components autoregressive conditional heteroscedasticity (ARCH) model with the inclusion of abrupt jump feature. The model is able to capture abrupt jumps, news impact, clustering volatility, long persistence volatility and heavy-tailed distributed error which are commonly observed in the crude oil time series. For the empirical study, we have selected the WTI crude oil index from year 2000 to 2016. The results found that by including the multiple-abrupt jumps in ARCH model, there are significant improvements of estimation evaluations as compared with the standard ARCH models. The outcomes of this study can provide useful information for risk management and portfolio analysis in the crude oil markets.
Universal properties of a trapped two-component fermi gas at unitarity.
Blume, D; von Stecher, J; Greene, Chris H
2007-12-01
We treat the trapped two-component Fermi system, in which unlike fermions interact through a two-body short-range potential having no bound state but an infinite scattering length. By accurately solving the Schrödinger equation for up to N=6 fermions, we show that no many-body bound states exist other than those bound by the trapping potential, and we demonstrate unique universal properties of the system: Certain excitation frequencies are separated by 2variant Planck's over 2piomega, the wave functions agree with analytical predictions and a virial theorem is fulfilled. Further calculations up to N=30 determine the excitation gap, an experimentally accessible universal quantity, and it agrees with recent predictions based on a density functional approach.
The curvature of semidirect product groups associated with two-component Hunter-Saxton systems
Energy Technology Data Exchange (ETDEWEB)
Kohlmann, Martin, E-mail: kohlmann@ifam.uni-hannover.de [Institute for Applied Mathematics, University of Hannover, D-30167 Hannover (Germany)
2011-06-03
In this paper, we study two-component versions of the periodic Hunter-Saxton equation and its {mu}-variant. Considering both equations as a geodesic flow on the semidirect product of the circle diffeomorphism group Diff(S) with a space of scalar functions on S we show that both equations are locally well posed. The main result of this paper is that the sectional curvature associated with the 2HS is constant and positive and that 2{mu}HS allows for a large subspace of positive sectional curvature. The issues of this paper are related to some of the results for 2CH and 2DP presented in Escher et al (2011 J. Geom. Phys. 61 436-52).
Phase diagram of two-component bosons on an optical lattice
Energy Technology Data Exchange (ETDEWEB)
Altman, Ehud; Hofstetter, Walter; Demler, Eugene; Lukin, Mikhail D [Department of Physics, Harvard University, Cambridge, MA 02138 (United States)
2003-09-01
We present a theoretical analysis of the phase diagram of two-component bosons on an optical lattice. A new formalism is developed which treats the effective spin interactions in the Mott and superfluid phases on the same footing. Using this new approach we chart the phase boundaries of the broken spin symmetry states up to the Mott to superfluid transition and beyond. Near the transition point, the magnitude of spin exchange can be very large, which facilitates the experimental realization of spin-ordered states. We find that spin and quantum fluctuations have a dramatic effect on the transition, making it first order in extended regions of the phase diagram. When each species is at integer filling, an additional phase transition may occur, from a spin-ordered insulator to a Mott insulator with no broken symmetries. We determine the phase boundaries in this regime and show that this is essentially a Mott transition in the spin sector.
Gaussian Entanglement Distribution via Satellite
Hosseinidehaj, Nedasadat
2014-01-01
In this work we analyse three quantum communication schemes for the generation of Gaussian entanglement between two ground stations. Communication occurs via a satellite over two independent atmospheric fading channels dominated by turbulence-induced beam wander. In our first scheme the engineering complexity remains largely on the ground transceivers, with the satellite acting simply as a reflector. Although the channel state information of the two atmospheric channels remains unknown in this scheme, the Gaussian entanglement generation between the ground stations can still be determined. On the ground, distillation and Gaussification procedures can be applied, leading to a refined Gaussian entanglement generation rate between the ground stations. We compare the rates produced by this first scheme with two competing schemes in which quantum complexity is added to the satellite, thereby illustrating the trade-off between space-based engineering complexity and the rate of ground-station entanglement generation...
Equi-Gaussian Curvature Folding
Indian Academy of Sciences (India)
E M El-Kholy; El-Said R Lashin; Salama N Daoud
2007-08-01
In this paper we introduce a new type of folding called equi-Gaussian curvature folding of connected Riemannian 2-manifolds. We prove that the composition and the cartesian product of such foldings is again an equi-Gaussian curvature folding. In case of equi-Gaussian curvature foldings, $f:M→ P_n$, of an orientable surface onto a polygon $P_n$ we prove that (i) $f\\in\\mathcal{F}_{EG}(S^2)\\Leftrightarrow n=3$ (ii) $f\\in\\mathcal{F}_{EG}(T^2)\\Rightarrow n=4$ (iii) $f\\in\\mathcal{F}_{EG}(\\# 2T^2)\\Rightarrow n=5, 6$ and we generalize (iii) for $\\# nT^2$.
Matsumoto, Jin; Masada, Youhei; Asano, Eiji; Shibata, Kazunari
2011-06-01
The nonlinear dynamics of the outflow driven by magnetic explosion on the surface of compact object is investigated through special relativistic magnetohydrodynamic simulations. We adopt, as an initial equilibrium state, a spherical stellar object embedded in the hydrostatic plasma which has a density ρ(r) ~ r-α and is threaded by a dipole magnetic field. The injection of magnetic energy at the surface of compact star breaks the dynamical equilibrium and triggers two-component outflow. At the early evolutionary stage, the magnetic pressure increases rapidly in time around the stellar surface, initiating a magnetically driven outflow. Then it excites a strong forward shock, shock driven outflow. The expansion velocity of the magnetically driven outflow is characterized by the Alfvén velocity on the stellar surface, and follows a simple scaling relation υmag ~ υA1/2. When the initial density profile declines steeply with radius, the strong shock is accelerated self-similarly to relativistic velocity ahead of the magnetically driven component. We find that the evolution of the strong forward shock can be described by a self-similar relation Γsh ~ rsh, where Γsh is the Lorentz factor of the plasma measured at the shock surface rsh. It should be stressed that the pure hydrodynamic process is responsible for the acceleration of the shock driven outflow. Our two-component outflow model, which is the natural outcome of the magnetic explosion, would deepen the understanding of the magnetic active phenomena on various magnetized stellar objects.
Phosphate sink containing two-component signaling systems as tunable threshold devices.
Directory of Open Access Journals (Sweden)
Munia Amin
2014-10-01
Full Text Available Synthetic biology aims to design de novo biological systems and reengineer existing ones. These efforts have mostly focused on transcriptional circuits, with reengineering of signaling circuits hampered by limited understanding of their systems dynamics and experimental challenges. Bacterial two-component signaling systems offer a rich diversity of sensory systems that are built around a core phosphotransfer reaction between histidine kinases and their output response regulator proteins, and thus are a good target for reengineering through synthetic biology. Here, we explore the signal-response relationship arising from a specific motif found in two-component signaling. In this motif, a single histidine kinase (HK phosphotransfers reversibly to two separate output response regulator (RR proteins. We show that, under the experimentally observed parameters from bacteria and yeast, this motif not only allows rapid signal termination, whereby one of the RRs acts as a phosphate sink towards the other RR (i.e. the output RR, but also implements a sigmoidal signal-response relationship. We identify two mathematical conditions on system parameters that are necessary for sigmoidal signal-response relationships and define key parameters that control threshold levels and sensitivity of the signal-response curve. We confirm these findings experimentally, by in vitro reconstitution of the one HK-two RR motif found in the Sinorhizobium meliloti chemotaxis pathway and measuring the resulting signal-response curve. We find that the level of sigmoidality in this system can be experimentally controlled by the presence of the sink RR, and also through an auxiliary protein that is shown to bind to the HK (yielding Hill coefficients of above 7. These findings show that the one HK-two RR motif allows bacteria and yeast to implement tunable switch-like signal processing and provides an ideal basis for developing threshold devices for synthetic biology applications.
A Monte Carlo simulation model for stationary non-Gaussian processes
DEFF Research Database (Denmark)
Grigoriu, M.; Ditlevsen, Ove Dalager; Arwade, S. R.
2003-01-01
includes translation processes and is useful for both Monte Carlo simulation and analytical studies. As for translation processes, the mixture of translation processes can have a wide range of marginal distributions and correlation functions. Moreover, these processes can match a broader range of second...... athe proposed Monte Carlo algorithm and compare features of translation processes and mixture of translation processes. Keywords: Monte Carlo simulation, non-Gaussian processes, sampling theorem, stochastic processes, translation processes......A class of stationary non-Gaussian processes, referred to as the class of mixtures of translation processes, is defined by their finite dimensional distributions consisting of mixtures of finite dimensional distributions of translation processes. The class of mixtures of translation processes...
Analytic model of the effect of poly-Gaussian roughness on rarefied gas flow near the surface
Aksenova, Olga A.; Khalidov, Iskander A.
2016-11-01
The dependence of the macro-parameters of the flow on surface roughness of the walls and on geometrical shape of the surface is investigated asymptotically and numerically in a rarefied gas molecular flow at high Knudsen numbers. Surface roughness is approximated in statistical simulation by the model of poly-Gaussian (with probability density as the mixture of Gaussian densities [1]) random process. Substantial difference is detected for considered models of the roughness (Gaussian, poly-Gaussian and simple models applied by other researchers), as well in asymptotical expressions [3], as in numerical results. For instance, the influence of surface roughness on momentum and energy exchange coefficients increases noticeably for poly-Gaussian model compared to Gaussian one (although the main properties of poly-Gaussian random processes and fields are similar to corresponding properties of Gaussian processes and fields). Main advantage of the model is based on relative simple relations between the parameters of the model and the basic statistical characteristics of random field. Considered statistical approach permits to apply not only diffuse-specular model of the local scattering function V0 of reflected gas atoms, but also Cercignani-Lampis scattering kernel or phenomenological models of scattering function. Thus, the comparison between poly-Gaussian and Gaussian models shows more significant effect of roughness in aerodynamic values for poly-Gaussian model.
DEFF Research Database (Denmark)
Islam, Aminul; Hansen, Hans Nørgaard; Marhöfer, David Maximilian
2011-01-01
Two component (2k) injection moulding is growing rapidly even in the field of precision micro moulding. Besides combining different material properties in the same product, two component moulding can eliminate many assembly steps in manufacturing process chain. One of the biggest technical...... challenges associated with 2k moulding is the unavailability of suitable two component material combinations which can meet the diverse requirement from product and process point of view. This paper presents a new pair of commercial polymer materials (BASF Ultramid A3EG10 and Kraiburg TPE Thermolast K TC5PCZ......-of-the-art two component micro moulding machine named Formica Plast from Desma Tec. The tests performed on the demonstrator showed potential for the material pair to be used in high precision two component moulding applications. The adhesion between the two materials, replication quality of the 2k part, sealing...
Numerical modeling of sintering of two-component metal powders with laser beams
Niziev, V. G.; Koldoba, A. V.; Mirzade, F. Kh.; Panchenko, V. Ya.; Poveschenko, Yu. A.; Popov, M. V.
2011-02-01
Direct laser sintering of a mixture of two metal powders with significantly different melting points is investigated by numerical simulation. The model is based on self-consistent non-linear continuity equations for volume fractions of components and on energy transfer equations for the powder mixture. It includes the movement of the solid particles due to shrinkage because of the density change of the powder mixture and the liquid flow driven by the capillary and gravity forces. The liquid flow is determined by Darcy's law. The effect of surface settlement of the powder is obtained. The width increasing rate of the melting zone depend both on the parameters of the laser radiation (on the power of the beam) and on the physical parameters of the particle's material, and it increases with the increasing of the penetrability or the increasing of the phase-transition heat. The increasing of the laser power under other factors being equal results in the acceleration of the melting front propagation.
ChemXSeer Digital Library Gaussian Search
Lahiri, Shibamouli; Nangia, Shikha; Mitra, Prasenjit; Giles, C Lee; Mueller, Karl T
2011-01-01
We report on the Gaussian file search system designed as part of the ChemXSeer digital library. Gaussian files are produced by the Gaussian software [4], a software package used for calculating molecular electronic structure and properties. The output files are semi-structured, allowing relatively easy access to the Gaussian attributes and metadata. Our system is currently capable of searching Gaussian documents using a boolean combination of atoms (chemical elements) and attributes. We have also implemented a faceted browsing feature on three important Gaussian attribute types - Basis Set, Job Type and Method Used. The faceted browsing feature enables a user to view and process a smaller, filtered subset of documents.
Betti Numbers of Gaussian Fields
Park, Changbom; Pranav, Pratyush; Chingangbam, Pravabati; van de Weygaert, Rien; Jones, Bernard; Vegter, Gert; Kim, Inkang; Hidding, Johan; Hellwing, Wojciech A.
2013-01-01
We present the relation between the genus in cosmology and the Betti numbers for excursion sets of three- and two-dimensional smooth Gaussian random fields, and numerically investigate the Betti numbers as a function of threshold level. Betti numbers are topological invariants of figures that can be
The Multivariate Gaussian Probability Distribution
DEFF Research Database (Denmark)
Ahrendt, Peter
2005-01-01
This technical report intends to gather information about the multivariate gaussian distribution, that was previously not (at least to my knowledge) to be found in one place and written as a reference manual. Additionally, some useful tips and tricks are collected that may be useful in practical...
Directory of Open Access Journals (Sweden)
Ming-Che Liu
Full Text Available Stenotrophomonas maltophilia, a gram-negative bacterium, has increasingly emerged as an important nosocomial pathogen. It is well-known for resistance to a variety of antimicrobial agents including cationic antimicrobial polypeptides (CAPs. Resistance to polymyxin B, a kind of CAPs, is known to be controlled by the two-component system PhoPQ. To unravel the role of PhoPQ in polymyxin B resistance of S. maltophilia, a phoP mutant was constructed. We found MICs of polymyxin B, chloramphenicol, ampicillin, gentamicin, kanamycin, streptomycin and spectinomycin decreased 2-64 fold in the phoP mutant. Complementation of the phoP mutant by the wild-type phoP gene restored all of the MICs to the wild type levels. Expression of PhoP was shown to be autoregulated and responsive to Mg2+ levels. The polymyxin B and gentamicin killing tests indicated that pretreatment of low Mg2+ can protect the wild-type S. maltophilia from killing but not phoP mutant. Interestingly, we found phoP mutant had a decrease in expression of SmeZ, an efflux transporter protein for aminoglycosides in S. maltophilia. Moreover, phoP mutant showed increased permeability in the cell membrane relative to the wild-type. In summary, we demonstrated the two-component regulator PhoP of S. maltophilia is involved in antimicrobial susceptibilities and low Mg2+ serves as a signal for triggering the pathway. Both the alteration in membrane permeability and downregulation of SmeZ efflux transporter in the phoP mutant contributed to the increased drug susceptibilities of S. maltophilia, in particular for aminoglycosides. This is the first report to describe the role of the Mg2+-sensing PhoP signaling pathway of S. maltophilia in regulation of the SmeZ efflux transporter and in antimicrobial susceptibilities. This study suggests PhoPQ TCS may serve as a target for development of antimicrobial agents against multidrug-resistant S. maltophilia.
Teschler, Jennifer K; Cheng, Andrew T; Yildiz, Fitnat H
2017-09-15
Two-component signal transduction systems (TCSs), typically composed of a sensor histidine kinase (HK) and a response regulator (RR), are the primary mechanism by which pathogenic bacteria sense and respond to extracellular signals. The pathogenic bacterium Vibrio cholerae is no exception and harbors 52 RR genes. Using in-frame deletion mutants of each RR gene, we performed a systematic analysis of their role in V. cholerae biofilm formation. We determined that 7 RRs impacted the expression of an essential biofilm gene and found that the recently characterized RR, VxrB, regulates the expression of key structural and regulatory biofilm genes in V. choleraevxrB is part of a 5-gene operon, which contains the cognate HK vxrA and three genes of unknown function. Strains carrying ΔvxrA and ΔvxrB mutations are deficient in biofilm formation, while the ΔvxrC mutation enhances biofilm formation. The overexpression of VxrB led to a decrease in motility. We also observed a small but reproducible effect of the absence of VxrB on the levels of cyclic di-GMP (c-di-GMP). Our work reveals a new function for the Vxr TCS as a regulator of biofilm formation and suggests that this regulation may act through key biofilm regulators and the modulation of cellular c-di-GMP levels.IMPORTANCE Biofilms play an important role in the Vibrio cholerae life cycle, providing protection from environmental stresses and contributing to the transmission of V. cholerae to the human host. V. cholerae can utilize two-component systems (TCS), composed of a histidine kinase (HK) and a response regulator (RR), to regulate biofilm formation in response to external cues. We performed a systematic analysis of V. cholerae RRs and identified a new regulator of biofilm formation, VxrB. We demonstrated that the VxrAB TCS is essential for robust biofilm formation and that this system may regulate biofilm formation via its regulation of key biofilm regulators and cyclic di-GMP levels. This research furthers our
Two-component coupled KdV equations and its connection with the generalized Harry Dym equations
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Popowicz, Ziemowit, E-mail: ziemek@ift.uni.wroc.pl [Institute of Theoretical Physics, University of Wrocław, Wrocław pl. M. Borna 9, 50-205 Wrocław (Poland)
2014-01-15
It is shown that three different Lax operators in the Dym hierarchy produce three generalized coupled Harry Dym equations. These equations transform, via the reciprocal link, to the coupled two-component Korteweg de Vries (KdV) system. The first equation gives us known integrable two-component KdV system, while the second reduces to the known symmetrical two-component KdV equation. The last one reduces to the Drienfeld-Sokolov equation. This approach gives us new Lax representation for these equations.
Two-component coupled KdV equations and its connection with the generalized Harry Dym equations
Popowicz, Ziemowit
2014-01-01
It is shown that three different Lax operators in the Dym hierarchy produce three generalized coupled Harry Dym equations. These equations transform, via the reciprocal link, to the coupled two-component Korteweg de Vries (KdV) system. The first equation gives us known integrable two-component KdV system, while the second reduces to the known symmetrical two-component KdV equation. The last one reduces to the Drienfeld-Sokolov equation. This approach gives us new Lax representation for these equations.
Directory of Open Access Journals (Sweden)
Mhamad Abou-Hamdan
2015-08-01
Full Text Available Abstract The bacterial genus Bartonella is classified in the alpha-2 Proteobacteria on the basis of 16S rDNA sequence comparison. The Bartonella two-component system feuPQ is found in nearly all bacterial species. We investigated the usefulness of the response regulator feuP gene sequence in the classification of 18 well characterized Bartonella species. Phylogenetic relationships were inferred using parsimony neighbour-joining and maximum-likelihood methods. Reliable classifications of most of the studied species were obtained. Bartonella were divided into two supported clades containing two supported clusters each. These results were similar to our previous data obtained with groEL ftsZ and ribC genes sequences. The wide range of feuP DNA sequence similarity 78.6 to 96.5 among Bartonella species makes it a promising candidate for multi-locus sequence typing MLST of clinical isolates. This is the first report proving the usefulness of feuP sequences in bartonellae classification at the species level.
Comparative Analysis of Two-component Signal Transduction System in Two Streptomycete Genomes
Institute of Scientific and Technical Information of China (English)
Wu WEI; Yixue LI; Weihua WANG; Zhiwei CAO; Hong YU; Xiaojing WANG; Jing ZHAO; Hao TAN; Hao XU; Weihong JIANG
2007-01-01
Species of the genus Streptomyces are major bacteria responsible for producing most natural antibiotics. Streptomyces coelicolor A3(2) and Streptomyces avermitilis were sequenced in 2002 and 2003,respectively. Two-component signal transduction systems (TCSs), consisting of a histidine sensor kinase (SK) and a cognate response regulator (RR), form the most common mechanism of transmembrane signal transduction in prokaryotes. TCSs in S. coelicolor A3(2) have been analyzed in detail. Here, we identify and classify the SK and RR of S. avermitilis and compare the TCSs with those of S. coelicolor A3(2) by computational approaches. Phylogenetic analysis of the cognate SK-RR pairs of the two species indicated that the cognate SK-RR pairs fall into four classes according to the distribution of their orthologs in other organisms. In addition to the cognate SK-RR pairs, some potential partners of non-cognate SK-RR were found, including those of unpaired SK and orphan RR and the cross-talk between different components in either strain. Our study provides new clues for further exploration of the molecular regulation mechanism of streptomycetes with industrial importance.
A feasibility study of using two-component polyurethane adhesive in constructing wooden structures
Institute of Scientific and Technical Information of China (English)
Mohammad Derikvand; Ghanbar Ebrahimi; Mehdi Tajvidi
2014-01-01
This investigation was conducted to determine the feasibility of using a two-component polyurethane (PUR) adhesive, with special waterproof properties, in constructing wooden structures. We designed and conducted tests to compare the shear strength and adhesion per-formance of PUR with polyvinyl acetate (PVAc) adhesive on block-shear specimens constructed of oriental beech (Fagus orientalis L.), fir (Abies alba Mill.), poplar (Populus deltoides Bartr.), white oak (Quercus alba L.), sycamore (Platanus orientalis L.) and white walnut (Juglans cinerea L.). The values of the percentage of wood failure were also determined in specimens constructed with each adhesive. The highest shear strength values of both adhesives were obtained in specimens constructed of beech, while the lowest shear strength values were obtained in fir and poplar specimens. Average shear strength of the PUR adhesive was 16.5%higher than that of the PVAc adhesive. Specimens constructed of fir, poplar and sycamore were characterised by the highest percentages of wood failure, whereas the lowest average percentages of wood failure were obtained in beech and oak specimens. With the exception of oak specimens, there was no statistically significant difference between per-centage of wood failure among the PUR and PVAc adhesives. Generally, the PUR adhesive showed an acceptable adhesion performance on wood materials used in our study.
The Evolution of Two-Component Systems in Bacteria RevealsDifferent Strategies for Niche Adaptation
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Alm, Eric; Huang, Katherine; Arkin, Adam
2006-09-13
Two-component systems including histidine protein kinasesrepresent the primary signal transduction paradigm in prokaryoticorganisms. To understand how these systems adapt to allow organisms todetect niche-specific signals, we analyzed the phylogenetic distributionof nearly 5000 histidine protein kinases from 207 sequenced prokaryoticgenomes. We found that many genomes carry a large repertoire of recentlyevolved signaling genes, which may reflect selective pressure to adapt tonew environmental conditions. Both lineage-specific gene family expansionand horizontal gene transfer play major roles in the introduction of newhistidine kinases into genomes; however, there are differences in howthese two evolutionary forces act. Genes imported via horizontal transferare more likely to retain their original functionality as inferred from asimilar complement of signaling domains, while gene family expansionaccompanied by domain shuffling appears to be a major source of novelgenetic diversity. Family expansion is the dominantsource of newhistidine kinase genes in the genomes most enriched in signalingproteins, and detailed analysis reveals that divergence in domainstructure and changes in expression patterns are hallmarks of recentexpansions. Finally, while these two modes of gene acquisition arewidespread across bacterial taxa, there are clear species-specificpreferences for which mode is used.
Zhou, Lei; Yang, Liu; Zeng, Xianfei; Danzheng, Jiacuo; Zheng, Qing; Liu, Jiayun; Liu, Feng; Xin, Yijuan; Cheng, Xiaodong; Su, Mingquan; Ma, Yueyun; Hao, Xiaoke
2015-07-01
Two-component systems (TCSs) have been reported to exhibit a sensing and responding role under drug stress that induces drug resistance in several bacterial species. However, the relationship between TCSs and multidrug resistance in Mycobacterium tuberculosis has not been comprehensively analysed to date. In this study, 90 M. tuberculosis clinical isolates were analysed using 15-loci mycobacterial interspersed repetitive unit (MIRU)-variable number tandem repeat (VNTR) typing and repetitive extragenic palindromic (rep)-PCR-based DNA fingerprinting. The results showed that all of the isolates were of the Beijing lineage, and strains with a drug-susceptible phenotype had not diverged into similar genotype clusters. Expression analysis of 13 response regulators of TCSs using real-time PCR and tandem mass spectrometry (MS/MS) proteomic analysis demonstrated that four response regulator genes (devR, mtrA, regX3 and Rv3143) were significantly upregulated in multidrug-resistant (MDR) strains compared with the laboratory strain H37Rv as well as drug-susceptible and isoniazid-monoresistant strains (PMycobacterium bovis BCG did not alter its sensitivity to the four antitubercular drugs. This suggests that upregulation of devR, which is common in MDR-TB strains, might be induced by drug stress and hypoxic adaptation following the acquisition of multidrug resistance.
Singular solutions of a modified two-component Camassa-Holm equation.
Holm, Darryl D; O Náraigh, Lennon; Tronci, Cesare
2009-01-01
The Camassa-Holm (CH) equation is a well-known integrable equation describing the velocity dynamics of shallow water waves. This equation exhibits spontaneous emergence of singular solutions (peakons) from smooth initial conditions. The CH equation has been recently extended to a two-component integrable system (CH2), which includes both velocity and density variables in the dynamics. Although possessing peakon solutions in the velocity, the CH2 equation does not admit singular solutions in the density profile. We modify the CH2 system to allow a dependence on the average density as well as the pointwise density. The modified CH2 system (MCH2) does admit peakon solutions in the velocity and average density. We analytically identify the steepening mechanism that allows the singular solutions to emerge from smooth spatially confined initial data. Numerical results for the MCH2 system are given and compared with the pure CH2 case. These numerics show that the modification in the MCH2 system to introduce the average density has little short-time effect on the emergent dynamical properties. However, an analytical and numerical study of pairwise peakon interactions for the MCH2 system shows a different asymptotic feature. Namely, besides the expected soliton scattering behavior seen in overtaking and head-on peakon collisions, the MCH2 system also allows the phase shift of the peakon collision to diverge in certain parameter regimes.
ACOUSTIC WAVES EMISSION IN THE TWO-COMPONENT HEREDITARY-ELASTIC MEDIUM
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V. S. Polenov
2014-01-01
Full Text Available Summary. On the dynamics of two-component media a number of papers, which address the elastic waves in a homogeneous, unbounded fluid-saturated porous medium. In other studies address issues of dissipative processes in harmonic deformation hereditary elastic medium. In the article the dissipative processes of the viscoelastic porous medium, which hereditary properties are described by the core relaxation fractional exponential function U.N. Rabotnova integro-differential Boltzmann-Volterr ratio, harmonic deformation by the straining saturated incompressible liquid are investigated. Speed of wave propagation, absorption coefficient, mechanical loss tangent, logarithmic decrement, depending on fractional parameter γ, determining formulas received. The frequency logarithm and temperature graph dependences with the goal fractional parameter are constructed. Shows the dependences velocity and attenuation coefficient of the tangent of the phase angle of the logarithm of the temperature, and the dependence of the attenuation coefficient of the logarithm of the frequency. Dependencies the speed and the tangent of the phase angle of the frequency identical function of the logarithm of temperature.
Cui, Yanhua; Liu, Wei; Qu, Xiaojun; Chen, Zhangting; Zhang, Xu; Liu, Tong; Zhang, Lanwei
2012-05-20
The Gram-positive bacterium Lactobacillus delbrueckii subsp. bulgaricus is of vital importance to the food industry, especially to the dairy industry. Two component systems (TCSs) are one of the most important mechanisms for environmental sensing and signal transduction in the majority of Gram-positive and Gram-negative bacteria. A typical TCS consists of a histidine protein kinase (HPK) and a cytoplasmic response regulator (RR). To investigate the functions of TCSs during acid adaptation in L. bulgaricus, we used quantitative PCR to reveal how TCSs expression changes during acid adaptation. Two TCSs (JN675228/JN675229 and JN675230/JN675231) and two HPKs (JN675236 and JN675240) were induced during acid adaptation. These TCSs were speculated to be related with the acid adaptation ability of L. bulgaricus. The mutants of JN675228/JN675229 were constructed in order to investigate the functions of JN675228/JN675229. The mutants showed reduced acid adaptation compared to that of wild type, and the complemented strains were similar to the wild-type strain. These observations suggested that JN675228 and JN675229 were involved in acid adaptation in L. bulgaricus. The interaction between JN675228 and JN675229 was identified by means of yeast two-hybrid system. The results indicated there is interaction between JN675228 and JN675229.
Freshwater DOM quantity and quality from a two-component model of UV absorbance
Carter, Heather T.; Tipping, Edward; Koprivnjak, Jean-Francois; Miller, Matthew P.; Cookson, Brenda; Hamilton-Taylor, John
2012-01-01
We present a model that considers UV-absorbing dissolved organic matter (DOM) to consist of two components (A and B), each with a distinct and constant spectrum. Component A absorbs UV light strongly, and is therefore presumed to possess aromatic chromophores and hydrophobic character, whereas B absorbs weakly and can be assumed hydrophilic. We parameterised the model with dissolved organic carbon concentrations [DOC] and corresponding UV spectra for c. 1700 filtered surface water samples from North America and the United Kingdom, by optimising extinction coefficients for A and B, together with a small constant concentration of non-absorbing DOM (0.80 mg DOC L-1). Good unbiased predictions of [DOC] from absorbance data at 270 and 350 nm were obtained (r2 = 0.98), the sum of squared residuals in [DOC] being reduced by 66% compared to a regression model fitted to absorbance at 270 nm alone. The parameterised model can use measured optical absorbance values at any pair of suitable wavelengths to calculate both [DOC] and the relative amounts of A and B in a water sample, i.e. measures of quantity and quality. Blind prediction of [DOC] was satisfactory for 9 of 11 independent data sets (181 of 213 individual samples).
Monte Carlo simulations of two-component drop growth by stochastic coalescence
Alfonso, L.; Raga, G. B.; Baumgardner, D.
2009-02-01
The evolution of two-dimensional drop distributions is simulated in this study using a Monte Carlo method. The stochastic algorithm of Gillespie (1976) for chemical reactions in the formulation proposed by Laurenzi et al. (2002) was used to simulate the kinetic behavior of the drop population. Within this framework, species are defined as droplets of specific size and aerosol composition. The performance of the algorithm was checked by a comparison with the analytical solutions found by Lushnikov (1975) and Golovin (1963) and with finite difference solutions of the two-component kinetic collection equation obtained for the Golovin (sum) and hydrodynamic kernels. Very good agreement was observed between the Monte Carlo simulations and the analytical and numerical solutions. A simulation for realistic initial conditions is presented for the hydrodynamic kernel. As expected, the aerosol mass is shifted from small to large particles due to collection process. This algorithm could be extended to incorporate various properties of clouds such several crystals habits, different types of soluble CCN, particle charging and drop breakup.
Monte Carlo simulations of two-component drop growth by stochastic coalescence
Directory of Open Access Journals (Sweden)
L. Alfonso
2009-02-01
Full Text Available The evolution of two-dimensional drop distributions is simulated in this study using a Monte Carlo method. The stochastic algorithm of Gillespie (1976 for chemical reactions in the formulation proposed by Laurenzi et al. (2002 was used to simulate the kinetic behavior of the drop population. Within this framework, species are defined as droplets of specific size and aerosol composition. The performance of the algorithm was checked by a comparison with the analytical solutions found by Lushnikov (1975 and Golovin (1963 and with finite difference solutions of the two-component kinetic collection equation obtained for the Golovin (sum and hydrodynamic kernels. Very good agreement was observed between the Monte Carlo simulations and the analytical and numerical solutions. A simulation for realistic initial conditions is presented for the hydrodynamic kernel. As expected, the aerosol mass is shifted from small to large particles due to collection process. This algorithm could be extended to incorporate various properties of clouds such several crystals habits, different types of soluble CCN, particle charging and drop breakup.
Thermoset nanocomposites from two-component waterborne polyurethanes and cellulose whiskers.
Wu, Guo-min; Chen, Jian; Huo, Shu-ping; Liu, Gui-feng; Kong, Zhen-wu
2014-05-25
We prepared thermoset nancomposites from biomass-based two-component waterborne polyurethane (2K-WPU) and cellulose namowhiskers (CNWs). Due to the formation of hydrogen bonds, the viscosity of 2K-WPU dispersion was found to be increased with the addition of CNWs. SEM images showed "sea-island structure" corresponding to the microphase separation between CNWs nano-filler and the 2K-WPU matrix. The α-relaxation temperature (Tα) and glass transition temperature (Tg) increased with the increase of CNWs content, which was due to the formation of a rigid CNWs nano-phase acting as crosslinking points in the 2K-WPU matrix. Mechanical properties from tensile test showed Young's modulus and tensile strength of 2K-WPU/CNWs nanocomposites were reinforced by the addition of CNWs. Thermo-stability of 2K-WPU/CNWs nanocomposites decreased slightly with the increase of CNWs content, which could be attributed to the increased thermal conductivity of the material after adding CNWs. Copyright © 2014 Elsevier Ltd. All rights reserved.
Photonic band-gap properties for two-component slow light
Ruseckas, J; Juzeliunas, G; Unanyan, R G; Otterbach, J; Fleischhauer, M
2011-01-01
We consider two-component "spinor" slow light in an ensemble of atoms coherently driven by two pairs of counterpropagating control laser fields in a double tripod-type linkage scheme. We derive an equation of motion for the spinor slow light (SSL) representing an effective Dirac equation for a massive particle with the mass determined by the two-photon detuning. By changing the detuning the atomic medium acts as a photonic crystal with a controllable band gap. If the frequency of the incident probe light lies within the band gap, the light tunnels through the sample. For frequencies outside the band gap, the transmission probability oscillates with increasing length of the sample. In both cases the reflection takes place into the complementary mode of the probe field. We investigate the influence of the finite excited state lifetime on the transmission and reflection coefficients of the probe light. We discuss possible experimental implementations of the SSL using alkali atoms such as Rubidium or Sodium.
Sander, Myriam C; Werkle-Bergner, Markus; Gerjets, Peter; Shing, Yee Lee; Lindenberger, Ulman
2012-02-15
We recently introduced a two-component model of the mechanisms underlying age differences in memory functioning across the lifespan. According to this model, memory performance is based on associative and strategic components. The associative component is relatively mature by middle childhood, whereas the strategic component shows a maturational lag and continues to develop until young adulthood. Focusing on work from our own lab, we review studies from the domains of episodic and working memory informed by this model, and discuss their potential implications for educational settings. The episodic memory studies uncover the latent potential of the associative component in childhood by documenting children's ability to greatly improve their memory performance following mnemonic instruction and training. The studies on working memory also point to an immature strategic component in children whose operation is enhanced under supportive conditions. Educational settings may aim at fostering the interplay between associative and strategic components. We explore possible routes towards this goal by linking our findings to recent trends in research on instructional design. Copyright © 2011 Elsevier Ltd. All rights reserved.
Rotational properties of two-component Bose gases in the lowest Landau level
Meyer, Marius; Sreejith, Ganesh Jaya; Viefers, Susanne
2015-03-01
We study the rotational (yrast) spectra of dilute two-component atomic Bose gases in the low angular momentum regime, assuming equal interspecies and intraspecies interaction. Our analysis employs the composite fermion (CF) approach including a pseudospin degree of freedom. While the CF approach is not a priori expected to work well in this angular momentum regime, we show that composite fermion diagonalization gives remarkably accurate approximations to low energy states in the spectra. For angular momenta 0 = N), we find that the CF states span the full Hilbert space and provide a convenient set of basis states which, by construction, are eigenstates of the symmetries of the Hamiltonian. Within this CF basis, we identify a subset of the basis states with the lowest Λ-level kinetic energy. Diagonalization within this significally smaller subspace constitutes a major computational simplification and provides very close approximations to ground states and a number of low-lying states within each pseudospin and angular momentum channel. This work was financially supported by the Research Council of Norway and by NORDITA.
Bioorthogonal two-component drug delivery in HER2(+) breast cancer mouse models
Hapuarachchige, Sudath; Kato, Yoshinori; Artemov, Dmitri
2016-04-01
The HER2 receptor is overexpressed in approximately 20% of breast cancers and is associated with tumorigenesis, metastasis, and a poor prognosis. Trastuzumab is a first-line targeted drug used against HER2(+) breast cancers; however, at least 50% of HER2(+) tumors develop resistance to trastuzumab. To treat these patients, trastuzumab-based antibody-drug conjugates (ACDs) have been developed and are currently used in the clinic. Despite their high efficacy, the long circulation half-life and non-specific binding of cytotoxic ADCs can result in systemic toxicity. In addition, standard ADCs do not provide an image-guided mode of administration. Here, we have developed a two-component, two-step, pre-targeting drug delivery system integrated with image guidance to circumvent these issues. In this strategy, HER2 receptors are pre-labeled with a functionalized trastuzumab antibody followed by the delivery of drug-loaded nanocarriers. Both components are cross-linked by multiple bioorthogonal click reactions in situ on the surface of the target cell and internalized as nanoclusters. We have explored the efficacy of this delivery strategy in HER2(+) human breast cancer models. Our therapeutic study confirms the high therapeutic efficacy of the new delivery system, with no significant toxicity.
Vortices with scalar condensates in two-component Ginzburg-Landau systems
Forgacs, Peter
2016-01-01
In a class of two-component Ginzburg-Landau models (TCGL) with a U(1)$\\times$U(1) symmetric potential, vortices with a condensate at their core may have significantly lower energies than the Abrikosov-Nielsen-Olesen (ANO) ones. On the example of liquid metallic hydrogen (LMH) above the critical temperature for protons we show that the ANO vortices become unstable against core-condensation, while condensate-core (CC) vortices are stable. For LMH the ratio of the masses of the two types of condensates, $M=m_2/m_1$ is large, and then as a consequence the energy per flux quantum of the vortices, $E_n/n$ becomes a non-monotonous function of the number of flux quanta, $n$. This leads to yet another manifestation of neither type 1 nor type 2, (type 1.5) superconductivity: superconducting and normal domains coexist while various "giant" vortices form. We note that LMH provides a particularly clean example of type 1.5 state as the interband coupling between electronic and protonic Cooper-pairs is forbidden.
Modified Baryonic Dynamics: two-component cosmological simulations with light sterile neutrinos
Energy Technology Data Exchange (ETDEWEB)
Angus, G.W.; Gentile, G. [Department of Physics and Astrophysics, Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050 Belgium (Belgium); Diaferio, A. [Dipartimento di Fisica, Università di Torino, Via P. Giuria 1, Torino, I-10125 Italy (Italy); Famaey, B. [Observatoire astronomique de Strasbourg, CNRS UMR 7550, Université de Strasbourg, 11 rue de l' Université, Strasbourg, F-67000 France (France); Heyden, K.J. van der, E-mail: garry.angus@vub.ac.be, E-mail: diaferio@ph.unito.it, E-mail: benoit.famaey@astro.unistra.fr, E-mail: gianfranco.gentile@ugent.be, E-mail: heyden@ast.uct.ac.za [Astrophysics, Cosmology and Gravity Centre, Dept. of Astronomy, University of Cape Town, Private Bag X3, Rondebosch, 7701 South Africa (South Africa)
2014-10-01
In this article we continue to test cosmological models centred on Modified Newtonian Dynamics (MOND) with light sterile neutrinos, which could in principle be a way to solve the fine-tuning problems of the standard model on galaxy scales while preserving successful predictions on larger scales. Due to previous failures of the simple MOND cosmological model, here we test a speculative model where the modified gravitational field is produced only by the baryons and the sterile neutrinos produce a purely Newtonian field (hence Modified Baryonic Dynamics). We use two-component cosmological simulations to separate the baryonic N-body particles from the sterile neutrino ones. The premise is to attenuate the over-production of massive galaxy cluster halos which were prevalent in the original MOND plus light sterile neutrinos scenario. Theoretical issues with such a formulation notwithstanding, the Modified Baryonic Dynamics model fails to produce the correct amplitude for the galaxy cluster mass function for any reasonable value of the primordial power spectrum normalisation.
Modelling elliptical galaxies phase-space constraints on two-component (gamma1,gamma2) models
Ciotti, L
1999-01-01
In the context of the study of the properties of the mutual mass distribution of the bright and dark matter in elliptical galaxies, present a family of two-component, spherical, self-consistent galaxy models, where one density distribution follows a gamma_1 profile, and the other a gamma_2 profile [(gamma_1,gamma_2) models], with different total masses and ``core'' radii. A variable amount of Osipkov-Merritt (radial) orbital anisotropy is allowed in both components. For these models, I derive analytically the necessary and sufficient conditions that the model parameters must satisfy in order to correspond to a physical system. Moreover, the possibility of adding a black hole at the center of radially anisotropic gamma models is discussed, determining analytically a lower limit of the anisotropy radius as a function of gamma. The analytical phase-space distribution function for (1,0) models is presented, together with the solution of the Jeans equations and the quantities entering the scalar virial theorem. It...
P2CS: a two-component system resource for prokaryotic signal transduction research
Directory of Open Access Journals (Sweden)
Méjean Vincent
2009-07-01
Full Text Available Abstract Background With the escalation of high throughput prokaryotic genome sequencing, there is an ever-increasing need for databases that characterise, catalogue and present data relating to particular gene sets and genomes/metagenomes. Two-component system (TCS signal transduction pathways are the dominant mechanisms by which micro-organisms sense and respond to external as well as internal environmental changes. These systems respond to a wide range of stimuli by triggering diverse physiological adjustments, including alterations in gene expression, enzymatic reactions, or protein-protein interactions. Description We present P2CS (Prokaryotic 2-Component Systems, an integrated and comprehensive database of TCS signal transduction proteins, which contains a compilation of the TCS genes within 755 completely sequenced prokaryotic genomes and 39 metagenomes. P2CS provides detailed annotation of each TCS gene including family classification, sequence features, functional domains, as well as genomic context visualization. To bypass the generic problem of gene underestimation during genome annotation, we also constituted and searched an ORFeome, which improves the recovery of TCS proteins compared to searches on the equivalent proteomes. Conclusion P2CS has been developed for computational analysis of the modular TCSs of prokaryotic genomes and metagenomes. It provides a complete overview of information on TCSs, including predicted candidate proteins and probable proteins, which need further curation/validation. The database can be browsed and queried with a user-friendly web interface at http://www.p2cs.org/.
Monedero, Vicente; Revilla-Guarinos, Ainhoa; Zúñiga, Manuel
2017-01-01
Two-component systems (TCSs) are widespread signal transduction pathways mainly found in bacteria where they play a major role in adaptation to changing environmental conditions. TCSs generally consist of sensor histidine kinases that autophosphorylate in response to a specific stimulus and subsequently transfer the phosphate group to their cognate response regulators thus modulating their activity, usually as transcriptional regulators. In this review we present the current knowledge on the physiological role of TCSs in species of the families Lactobacillaceae and Leuconostocaceae of the group of lactic acid bacteria (LAB). LAB are microorganisms of great relevance for health and food production as the group spans from starter organisms to pathogens. Whereas the role of TCSs in pathogenic LAB (most of them belonging to the family Streptococcaceae) has focused the attention, the roles of TCSs in commensal LAB, such as most species of Lactobacillaceae and Leuconostocaceae, have been somewhat neglected. However, evidence available indicates that TCSs are key players in the regulation of the physiology of these bacteria. The first studies in food-associated LAB showed the involvement of some TCSs in quorum sensing and production of bacteriocins, but subsequent studies have shown that TCSs participate in other physiological processes, such as stress response, regulation of nitrogen metabolism, regulation of malate metabolism, and resistance to antimicrobial peptides, among others. Copyright © 2017 Elsevier Inc. All rights reserved.
The Role of Two-Component Signal Transduction Systems in Staphylococcus aureus Virulence Regulation.
Haag, Andreas F; Bagnoli, Fabio
2016-01-05
Staphylococcus aureus is a versatile, opportunistic human pathogen that can asymptomatically colonize a human host but can also cause a variety of cutaneous and systemic infections. The ability of S. aureus to adapt to such diverse environments is reflected in the presence of complex regulatory networks fine-tuning metabolic and virulence gene expression. One of the most widely distributed mechanisms is the two-component signal transduction system (TCS) which allows a pathogen to alter its gene expression profile in response to environmental stimuli. The simpler TCSs consist of only a transmembrane histidine kinase (HK) and a cytosolic response regulator. S. aureus encodes a total of 16 conserved pairs of TCSs that are involved in diverse signalling cascades ranging from global virulence gene regulation (e.g. quorum sensing by the Agr system), the bacterial response to antimicrobial agents, cell wall metabolism, respiration and nutrient sensing. These regulatory circuits are often interconnected and affect each other's expression, thus fine-tuning staphylococcal gene regulation. This manuscript gives an overview of the current knowledge of staphylococcal environmental sensing by TCS and its influence on virulence gene expression and virulence itself. Understanding bacterial gene regulation by TCS can give major insights into staphylococcal pathogenicity and has important implications for knowledge-based drug design and vaccine formulation.
Directory of Open Access Journals (Sweden)
Alisha Dhiman
2014-01-01
Full Text Available Two-component signal transduction systems (TCS, consisting of a sensor histidine protein kinase and its cognate response regulator, are an important mode of environmental sensing in bacteria. Additionally, they have been found to regulate virulence determinants in several pathogens. Bacillus anthracis, the causative agent of anthrax and a bioterrorism agent, harbours 41 pairs of TCS. However, their role in its pathogenicity has remained largely unexplored. Here, we show that WalRK of B. anthracis forms a functional TCS which exhibits some species-specific functions. Biochemical studies showed that domain variants of WalK, the histidine kinase, exhibit classical properties of autophosphorylation and phosphotransfer to its cognate response regulator WalR. Interestingly, these domain variants also show phosphatase activity towards phosphorylated WalR, thereby making WalK a bifunctional histidine kinase/phosphatase. An in silico regulon determination approach, using a consensus binding sequence from Bacillus subtilis, provided a list of 30 genes that could form a putative WalR regulon in B. anthracis. Further, electrophoretic mobility shift assay was used to show direct binding of purified WalR to the upstream regions of three putative regulon candidates, an S-layer protein EA1, a cell division ABC transporter FtsE and a sporulation histidine kinase KinB3. Our work lends insight into the species-specific functions and mode of action of B. anthracis WalRK.
Directory of Open Access Journals (Sweden)
Eric Alm
2006-11-01
Full Text Available Two-component systems including histidine protein kinases represent the primary signal transduction paradigm in prokaryotic organisms. To understand how these systems adapt to allow organisms to detect niche-specific signals, we analyzed the phylogenetic distribution of nearly 5,000 histidine protein kinases from 207 sequenced prokaryotic genomes. We found that many genomes carry a large repertoire of recently evolved signaling genes, which may reflect selective pressure to adapt to new environmental conditions. Both lineage-specific gene family expansion and horizontal gene transfer play major roles in the introduction of new histidine kinases into genomes; however, there are differences in how these two evolutionary forces act. Genes imported via horizontal transfer are more likely to retain their original functionality as inferred from a similar complement of signaling domains, while gene family expansion accompanied by domain shuffling appears to be a major source of novel genetic diversity. Family expansion is the dominant source of new histidine kinase genes in the genomes most enriched in signaling proteins, and detailed analysis reveals that divergence in domain structure and changes in expression patterns are hallmarks of recent expansions. Finally, while these two modes of gene acquisition are widespread across bacterial taxa, there are clear species-specific preferences for which mode is used.
Dhiman, Alisha; Bhatnagar, Sonika; Kulshreshtha, Parul; Bhatnagar, Rakesh
2014-01-01
Two-component signal transduction systems (TCS), consisting of a sensor histidine protein kinase and its cognate response regulator, are an important mode of environmental sensing in bacteria. Additionally, they have been found to regulate virulence determinants in several pathogens. Bacillus anthracis, the causative agent of anthrax and a bioterrorism agent, harbours 41 pairs of TCS. However, their role in its pathogenicity has remained largely unexplored. Here, we show that WalRK of B. anthracis forms a functional TCS which exhibits some species-specific functions. Biochemical studies showed that domain variants of WalK, the histidine kinase, exhibit classical properties of autophosphorylation and phosphotransfer to its cognate response regulator WalR. Interestingly, these domain variants also show phosphatase activity towards phosphorylated WalR, thereby making WalK a bifunctional histidine kinase/phosphatase. An in silico regulon determination approach, using a consensus binding sequence from Bacillus subtilis, provided a list of 30 genes that could form a putative WalR regulon in B. anthracis. Further, electrophoretic mobility shift assay was used to show direct binding of purified WalR to the upstream regions of three putative regulon candidates, an S-layer protein EA1, a cell division ABC transporter FtsE and a sporulation histidine kinase KinB3. Our work lends insight into the species-specific functions and mode of action of B. anthracis WalRK.
[Two-component signal transduction as attractive drug targets in pathogenic bacteria].
Utsumi, Ryutaro; Igarashi, Masayuki
2012-01-01
Gene clusters contributing to processes such as cell growth and pathogenicity are often controlled by two-component signal transduction systems (TCSs). TCS consists of a histidine kinase (HK) and a response regulator (RR). TCSs are attractive as drug targets for antimicrobials because many HK and RR genes are coded on the bacterial genome though few are found in lower eukaryotes. The HK/RR signal transduction system is distinct from serine/threonine and tyrosine phosphorylation in higher eukaryotes. Specific inhibitors against TCS systems work differently from conventional antibiotics, and developing them into new drugs that are effective against various drug-resistant bacteria may be possible. Furthermore, inhibitors of TCSs that control virulence factors may reduce virulence without killing the pathogenic bacteria. Previous TCS inhibitors targeting the kinase domain of the histidine kinase sensor suffered from poor selectivity. Recent TCS inhibitors, however, target the sensory domains of the sensors blocking the quorum sensing system, or target the essential response regulator. These new targets are introduced, together with several specific TCSs that have the potential to serve as effective drug targets.
P2CS: a two-component system resource for prokaryotic signal transduction research.
Barakat, Mohamed; Ortet, Philippe; Jourlin-Castelli, Cécile; Ansaldi, Mireille; Méjean, Vincent; Whitworth, David E
2009-07-15
With the escalation of high throughput prokaryotic genome sequencing, there is an ever-increasing need for databases that characterise, catalogue and present data relating to particular gene sets and genomes/metagenomes. Two-component system (TCS) signal transduction pathways are the dominant mechanisms by which micro-organisms sense and respond to external as well as internal environmental changes. These systems respond to a wide range of stimuli by triggering diverse physiological adjustments, including alterations in gene expression, enzymatic reactions, or protein-protein interactions. We present P2CS (Prokaryotic 2-Component Systems), an integrated and comprehensive database of TCS signal transduction proteins, which contains a compilation of the TCS genes within 755 completely sequenced prokaryotic genomes and 39 metagenomes. P2CS provides detailed annotation of each TCS gene including family classification, sequence features, functional domains, as well as genomic context visualization. To bypass the generic problem of gene underestimation during genome annotation, we also constituted and searched an ORFeome, which improves the recovery of TCS proteins compared to searches on the equivalent proteomes. P2CS has been developed for computational analysis of the modular TCSs of prokaryotic genomes and metagenomes. It provides a complete overview of information on TCSs, including predicted candidate proteins and probable proteins, which need further curation/validation. The database can be browsed and queried with a user-friendly web interface at http://www.p2cs.org/.
Yu, Shuijing; Peng, Yanping; Chen, Wanyi; Deng, Yangwu; Guo, Yanhua
2014-09-01
Lactobacillus casei has traditionally been recognized as a probiotic, thus needing to survive the industrial production processes and transit through the gastrointestinal tract before providing benefit to human health. The two-component signal transduction system (TCS) plays important roles in sensing and reacting to environmental changes, which consists of a histidine kinase (HK) and a response regulator (RR). In this study we identified HKs and RRs of six sequenced L. casei strains. Ortholog analysis revealed 15 TCS clusters (HK-RR pairs), one orphan HKs and three orphan RRs, of which 12 TCS clusters were common to all six strains, three were absent in one strain. Further classification of the predicted HKs and RRs revealed interesting aspects of their putative functions. Some TCS clusters are involved with the response under the stress of the bile salts, acid, or oxidative, which contribute to survive the difficult journey through the human gastrointestinal tract. Computational predictions of 15 TCSs were verified by PCR experiments. This genomic level study of TCSs should provide valuable insights into the conservation and divergence of TCS proteins in the L. casei strains.
Hiscox, Thomas J; Ohtani, Kaori; Shimizu, Tohru; Cheung, Jackie K; Rood, Julian I
2014-12-01
Clostridium perfringens is a Gram-positive rod that is widely distributed in nature and is the etiological agent of several human and animal diseases. The complete genome sequence of C. perfringens strain 13 has been determined and multiple two-component signal transduction systems identified. One of these systems, designated here as the MalNO system, was analyzed in this study. Microarray analysis was used to carry out functional analysis of a malO mutant. The results, which were confirmed by quantitative reverse-transcriptase PCR, indicated that genes putatively involved in the uptake and metabolism of maltose were up-regulated in the malO mutant. These effects were reversed by complementation with the wild-type malO gene. Growth of these isogenic strains in medium with and without maltose showed that the malO mutant recovered more quickly from maltose deprivation when compared to the wild-type and complemented strains, leading to the conclusion that the MalNO system regulates maltose utilization in C. perfringens. It is postulated that this regulatory network may allow this soil bacterium and opportunistic pathogen to respond to environmental conditions where there are higher concentrations of maltose or maltodextrins, such as in the presence of decaying plant material in rich soil. Copyright © 2014 Elsevier Ltd. All rights reserved.
Bretl, Daniel J; Demetriadou, Chrystalla; Zahrt, Thomas C
2011-12-01
Pathogenic microorganisms encounter a variety of environmental stresses following infection of their respective hosts. Mycobacterium tuberculosis, the etiological agent of tuberculosis, is an unusual bacterial pathogen in that it is able to establish lifelong infections in individuals within granulomatous lesions that are formed following a productive immune response. Adaptation to this highly dynamic environment is thought to be mediated primarily through transcriptional reprogramming initiated in response to recognition of stimuli, including low-oxygen tension, nutrient depletion, reactive oxygen and nitrogen species, altered pH, toxic lipid moieties, cell wall/cell membrane-perturbing agents, and other environmental cues. To survive continued exposure to these potentially adverse factors, M. tuberculosis encodes a variety of regulatory factors, including 11 complete two-component signal transduction systems (TCSSs) and several orphaned response regulators (RRs) and sensor kinases (SKs). This report reviews our current knowledge of the TCSSs present in M. tuberculosis. In particular, we discuss the biochemical and functional characteristics of individual RRs and SKs, the environmental stimuli regulating their activation, the regulons controlled by the various TCSSs, and the known or postulated role(s) of individual TCSSs in the context of M. tuberculosis physiology and/or pathogenesis.
Osmotic Second Virial Coefficients of Aqueous Solutions from Two-Component Equations of State.
Cerdeiriña, Claudio A; Widom, B
2016-12-29
Osmotic second virial coefficients in dilute aqueous solutions of small nonpolar solutes are calculated from three different two-component equations of state. The solutes are five noble gases, four diatomics, and six hydrocarbons in the range C1-C4. The equations of state are modified versions of the van der Waals, Redlich-Kwong, and Peng-Robinson equations, with an added hydrogen-bonding term for the solvent water. The parameters in the resulting equations of state are assigned so as to reproduce the experimental values and temperature dependence of the density, vapor pressure, and compressibility of the solvent, the gas-phase second virial coefficient of the pure solute, the solubility and partial molecular volume of the solute, and earlier estimates of the solutes' molecular radii. For all 15 solutes, the calculations are done for 298.15 K, whereas for CH4, C2H6, and C3H8 in particular, they are also done as functions of temperature over the full range 278.15-348.15 K. The calculated osmotic virial coefficients are compared with earlier calculations of these coefficients for these solutes and also with the results derived from earlier computer simulations of model aqueous solutions of methane. They are also compared with the experimental gas-phase second virial coefficients of the pure gaseous solutes to determine the effect the mediation of the solvent has on the resulting solute-solute interactions in the solution.
The Formation of Bulges, Discs and Two Component Galaxies in the CANDELS Survey at z < 3
Margalef-Bentabol, Berta; Mortlock, Alice; Hartley, Will; Duncan, Kenneth; Ferguson, Harry C; Koekemoer, Anton M; Dekel, Avishai; Primack, Joel R
2016-01-01
We examine a sample of 1495 galaxies in the CANDELS fields to determine the evolution of two component galaxies, including bulges and discs, within massive galaxies at the epoch 1 < z < 3 when the Hubble sequence forms. We fit all of our galaxies' light profiles with a single S\\'ersic fit, as well as with a combination of exponential and S\\'ersic profiles. The latter is done in order to describe a galaxy with an inner and an outer component, or bulge and disc component. We develop and use three classification methods (visual, F-test and the RFF) to separate our sample into 1-component galaxies (disc/spheroids-like galaxies) and 2-component galaxies (galaxies formed by an 'inner part' or bulge and an 'outer part' or disc). We then compare the results from using these three different ways to classify our galaxies. We find that the fraction of galaxies selected as 2-component galaxies increases on average 50 per cent from the lowest mass bin to the most massive galaxies, and decreases with redshift by a fa...
Vapour-mediated sensing and motility in two-component droplets
Cira, N. J.; Benusiglio, A.; Prakash, M.
2015-03-01
Controlling the wetting behaviour of liquids on surfaces is important for a variety of industrial applications such as water-repellent coatings and lubrication. Liquid behaviour on a surface can range from complete spreading, as in the `tears of wine' effect, to minimal wetting as observed on a superhydrophobic lotus leaf. Controlling droplet movement is important in microfluidic liquid handling, on self-cleaning surfaces and in heat transfer. Droplet motion can be achieved by gradients of surface energy. However, existing techniques require either a large gradient or a carefully prepared surface to overcome the effects of contact line pinning, which usually limit droplet motion. Here we show that two-component droplets of well-chosen miscible liquids such as propylene glycol and water deposited on clean glass are not subject to pinning and cause the motion of neighbouring droplets over a distance. Unlike the canonical predictions for these liquids on a high-energy surface, these droplets do not spread completely but exhibit an apparent contact angle. We demonstrate experimentally and analytically that these droplets are stabilized by evaporation-induced surface tension gradients and that they move in response to the vapour emitted by neighbouring droplets. Our fundamental understanding of this robust system enabled us to construct a wide variety of autonomous fluidic machines out of everyday materials.
Impact of backmixing of the aqueous phase on two-component rare earth separation process
Institute of Scientific and Technical Information of China (English)
WU Sheng; CHENG Fuxiang; LIAO Chunsheng; YAN Chunhua
2013-01-01
Solvent extraction based on mixer-settler is the major industrial method of rare earth (RE) separation.In the mixer-settler extraction process,due to the insufficient settling time in normal circumstances,backmixing of the aqueous phase could have significant impact on the process of RE extraction separation.Therefore on the basis of the extraction equilibrium and mass balance of the mixer-settler extraction process,here we developed a mathematic expression of the aqueous phase backmixing in a two-component separation process,and obtained a quantitative analysis of the backmixing effect on the purification process by the approximations according to certain hypotheses.Two extraction systems of La/Ce and Pr/Nd separation were chosen as the examples to analyze the backmixing effect,and the results showed that the aqueous backmixing had greater influence in the scrubbing segment than in the extraction segment,especially in the system with a high separation factor such as La/Ce separation.Therefore it was suggested that the aqueous backmixing effect should be well attended in the design and application of RE extraction separation.
A hybrid two-component system protein from Azospirillum brasilense Sp7 was involved in chemotaxis.
Cui, Yanhua; Tu, Ran; Wu, Lixian; Hong, Yuanyuan; Chen, Sanfeng
2011-09-20
We here report the sequence and functional analysis of org35 of Azospirillum brasilense Sp7, which was originally identified to be able to interact with NifA in yeast-two-hybrid system. The org35 encodes a hybrid two-component system protein, including N-terminal PAS domains, a histidine kinase (HPK) domain and a response regulator (RR) domain in C-terminal. To determine the function of the Org35, a deletion-insertion mutant in PAS domain [named Sp7353] and a complemental strain Sp7353C were constructed. The mutant had reduced chemotaxis ability compared to that of wild-type, and the complemental strain was similar to the wild-type strain. These data suggested that the A. brasilense org35 played a key role in chemotaxis. Variants containing different domains of the org35 were expressed, and the functions of these domains were studied in vitro. Phosphorylation assays in vitro demonstrated that the HPK domain of Org35 possessed the autokinase activity and that the phosphorylated HPK was able to transfer phosphate groups to the RR domain. The result indicated Org35 was a phosphorylation-communicating protein.
One-pot Synthesis of Dimethyl Carbonate in the Presence of a Two-component Catalyst
Institute of Scientific and Technical Information of China (English)
CHEN Xiu-zhi; HU Chang-wen; GAO Zhi-ming
2005-01-01
The one-pot synthesis of dimethyl carbonate (DMC) with co-production of propy-lene carbonate(PC) and propylene glycol(PG) from propylene oxide( PO), carbon dioxide and methanol as the starting materials was investigated.The catalyst adopted here was a mixture of tetrabutyl ammonium bromide and sodium methoxide. It was found that under the reaction conditions of t = 150 ℃, p =3-4 MPa and 2 h, the PO conversion could reach 100%, the DMC,PC and the PG selectivities were 49.7%, 42.7% and 49. 8%, respectively, and the selectivity of by-products was below 10%.
Hierarchy in Sampling Gaussian-correlated Bosons
Huh, Joonsuk
2016-01-01
Boson Sampling represents a class of physical processes potentially intractable for classical devices to simulate. The Gaussian extension of Boson Sampling remains a computationally hard problem, where the input state is a product of uncorrelated Gaussian modes. Besides, motivated by molecular spectroscopy, Vibronic Boson Sampling involves operations that can generate Gaussian correlation among different Boson modes. Therefore, Gaussian Boson Sampling is a special case of Vibronic Boson Sampling. However, this does not necessarily mean that Vibronic Boson Sampling is more complex than Gaussian Boson Sampling. Here we develop a hierarchical structure to show how the initial correlation in Vibronic Boson Sampling can be absorbed in Gaussian Boson Sampling with ancillary modes and in a scattershot fashion. Since every Gaussian state is associated with a thermal state, our result implies that every sampling problem in molecular vibronic transitions, at any temperature, can be simulated by Gaussian Boson Sampling ...
Stable and Efficient Gaussian Process Calculations
National Aeronautics and Space Administration — The use of Gaussian processes can be an effective approach to prediction in a supervised learning environment. For large data sets, the standard Gaussian process...
Laguerre Gaussian beam multiplexing through turbulence
CSIR Research Space (South Africa)
Trichili, A
2014-08-17
Full Text Available We analyze the effect of atmospheric turbulence on the propagation of multiplexed Laguerre Gaussian modes. We present a method to multiplex Laguerre Gaussian modes using digital holograms and decompose the resulting field after encountering a...
Propagation and interaction of cos-Gaussian beams in photorefractive crystals
Jiang, Qichang; Su, Yanli; Nie, Hexian; Ma, Ziwei; Li, Yonghong
2017-07-01
Investigate numerically the propagation and interaction of cos-Gaussian beams in a biased photorefractive crystal by the finite difference method. The results show that the single cos-Gaussian beam can evolve into Y-type breathing solitons when the self-focusing nonlinearity is small, and the soliton properties can be controlled by adjusting the nonlinear parameter or cos modulation parameter. The distance between two components of Y-type breathing solitons will decrease with increasing the nonlinear parameter or decreasing the cos modulation parameter. The breathing soliton with two weak sidebands can form when the self-focusing nonlinearity is big. Moreover, two internal components of two cos-Gaussian beams have obvious interaction but two outside components have tiny interaction.
Analytic matrix elements with shifted correlated Gaussians
DEFF Research Database (Denmark)
Fedorov, D. V.
2017-01-01
Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are calculated analytically. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics.......Matrix elements between shifted correlated Gaussians of various potentials with several form-factors are calculated analytically. Analytic matrix elements are of importance for the correlated Gaussian method in quantum few-body physics....
Effects of external magnetic trap on two dark solitons of a two-component Bose-Einstein condensate
Institute of Scientific and Technical Information of China (English)
Hong Li; D. N. Wang
2008-01-01
Two dark solitons are considered in a two-component Bose-Einstein condensate with an external magnetic trap, and effects of the trap potential on their dynamics are investigated by the numerical simulation. The results show that the dark solitons attract, collide and repel periodically in two components as time changes, the time period depends strictly on the initial condition and the potential, and there are obvious self-trapping effects on the two dark solitons.
Directory of Open Access Journals (Sweden)
Mark K. Ashby
2006-01-01
Full Text Available The publicly available annotated archaeal genome sequences (23 complete and three partial annotations, October 2005 were searched for the presence of potential two-component open reading frames (ORFs using gene category lists and BLASTP. A total of 489 potential two-component genes were identified from the gene category lists and BLASTP. Two-component genes were found in 14 of the 21 Euryarchaeal sequences (October 2005 and in neither the Crenarchaeota nor the Nanoarchaeota. A total of 20 predicted protein domains were identified in the putative two-component ORFs that, in addition to the histidine kinase and receiver domains, also includes sensor and signalling domains. The detailed structure of these putative proteins is shown, as is the distribution of each class of two-component genes in each species. Potential members of orthologous groups have been identified, as have any potential operons containing two or more two-component genes. The number of two-component genes in those Euryarchaeal species which have them seems to be linked more to lifestyle and habitat than to genome complexity, with most examples being found in Methanospirillum hungatei, Haloarcula marismortui, Methanococcoides burtonii and the mesophilic Methanosarcinales group. The large numbers of two-component genes in these species may reflect a greater requirement for internal regulation. Phylogenetic analysis of orthologous groups of five different protein classes, three probably involved in regulating taxis, suggests that most of these ORFs have been inherited vertically from an ancestral Euryarchaeal species and point to a limited number of key horizontal gene transfer events.
Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data
DEFF Research Database (Denmark)
Røge, Rasmus; Madsen, Kristoffer Hougaard; Schmidt, Mikkel Nørgaard
2017-01-01
spherical manifold are rarely analyzed, in part due to the computational challenges imposed by directional statistics. In this letter, we discuss a Bayesian von Mises-Fisher (vMF) mixture model for data on the unit hypersphere and present an efficient inference procedure based on collapsed Markov chain...... Monte Carlo sampling. Comparing the vMF and gaussian mixture models on synthetic data, we demonstrate that the vMF model has a slight advantage inferring the true underlying clustering when compared to gaussian-based models on data generated from both a mixture of vMFs and a mixture of gaussians......Cluster analysis of functional magnetic resonance imaging (fMRI) data is often performed using gaussian mixture models, but when the time series are standardized such that the data reside on a hypersphere, this modeling assumption is questionable. The consequences of ignoring the underlying...
Suda, S. R.; Petters, M. D.
2013-12-01
Atmospheric aerosols serve as cloud condensation nuclei (CCN), altering cloud properties and ultimately affecting climate through their effect on the radiative balance. Aerosol CCN activity depends in part on aerosol composition and surfactant compounds are of particular interest because surfactants are enriched at the water/air interface, resulting in a radial concentration gradient within the aqueous droplet. Accurate treatment of the surfactant concentration gradient complicates the otherwise straightforward predictions of CCN activity for aerosols of known composition. To accurately evaluate predictions made by theory, laboratory studies investigating the relationship between critical supersaturation and dry diameter of particles that include surfactants require significant reduction in measurement uncertainty for both water-uptake and CCN measurements. Furthermore, uncertainties remain regarding kinetic limitations to surfactant partitioning that could result in deviation from predictions based on equilibrium thermodynamics. This study attempts to address some of these issues through high-resolution analysis of CCN activity of two-component mixed surfactant/non-surfactant aerosols at different internal mixing ratios performed with and without a water-uptake time delay to ascertain whether or not the observed effects are kinetically limited. We present new data for the aerosols consisting of 1) the ionic surfactant sodium dodecyl sulfate (SDS) with ammonium sulfate, 2) SDS with sodium chloride and 3) the strong non-ionic fluorosurfactant Zonyl with an organic proxy glucose. As a point of reference we also evaluated the mixture of ammonium sulfate with glucose. Aerosol activation diameters were determined using CCN analysis in conjunction with scanning mobility size classification and high sheath-to-aerosol flow ratios. This resulted in CCN-derived kappa values that could be determined within +/-5% relative error. To test whether dynamic surfactant partitioning
Optical trapping with Super-Gaussian beams
CSIR Research Space (South Africa)
McLaren, M
2013-04-01
Full Text Available We outline the possibility of optical trapping and tweezing with Super-Gaussian beam profiles. We show that the trapping strength can be tuned continuously by adjusting the order of a Super-Gaussian beam, approaching that of a perfect Gaussian...
Minimum output entropy of Gaussian channels
Lloyd, S; Maccone, L; Pirandola, S; Garcia-Patron, R
2009-01-01
We show that the minimum output entropy for all single-mode Gaussian channels is additive and is attained for Gaussian inputs. This allows the derivation of the channel capacity for a number of Gaussian channels, including that of the channel with linear loss, thermal noise, and linear amplification.
Feng, Bao-Feng; Maruno, Ken-ichi; Ohta, Yasuhiro
2017-02-01
In the present paper, we propose a two-component generalization of the reduced Ostrovsky (Vakhnenko) equation, whose differential form can be viewed as the short-wave limit of a two-component Degasperis-Procesi (DP) equation. They are integrable due to the existence of Lax pairs. Moreover, we have shown that the two-component reduced Ostrovsky equation can be reduced from an extended BKP hierarchy with negative flow through a pseudo 3-reduction and a hodograph (reciprocal) transform. As a by-product, its bilinear form and N-soliton solution in terms of pfaffians are presented. One- and two-soliton solutions are provided and analyzed. In the second part of the paper, we start with a modified BKP hierarchy, which is a Bäcklund transformation of the above extended BKP hierarchy, an integrable semi-discrete analogue of the two-component reduced Ostrovsky equation is constructed by defining an appropriate discrete hodograph transform and dependent variable transformations. In particular, the backward difference form of above semi-discrete two-component reduced Ostrovsky equation gives rise to the integrable semi-discretization of the short wave limit of a two-component DP equation. Their N-soliton solutions in terms of pffafians are also provided.
Quantitative Kinetic Analyses of Shutting Off a Two-Component System
Directory of Open Access Journals (Sweden)
Rong Gao
2017-05-01
Full Text Available Cells rely on accurate control of signaling systems to adapt to environmental perturbations. System deactivation upon stimulus removal is as important as activation of signaling pathways. The two-component system (TCS is one of the major bacterial signaling schemes. In many TCSs, phosphatase activity of the histidine kinase (HK is believed to play an essential role in shutting off the pathway and resetting the system to the prestimulus state. Two basic challenges are to understand the dynamic behavior of system deactivation and to quantitatively evaluate the role of phosphatase activity under natural cellular conditions. Here we report a kinetic analysis of the response to shutting off the archetype Escherichia coli PhoR-PhoB TCS pathway using both transcription reporter assays and in vivo phosphorylation analyses. Upon removal of the stimulus, the pathway is shut off by rapid dephosphorylation of the PhoB response regulator (RR while PhoB-regulated gene products gradually reset to prestimulus levels through growth dilution. We developed an approach combining experimentation and modeling to assess in vivo kinetic parameters of the phosphatase activity with kinetic data from multiple phosphatase-diminished mutants. This enabled an estimation of the PhoR phosphatase activity in vivo, which is much stronger than the phosphatase activity of PhoR cytoplasmic domains analyzed in vitro. We quantitatively modeled how strong the phosphatase activity needs to be to suppress nonspecific phosphorylation in TCSs and discovered that strong phosphatase activity of PhoR is required for cross-phosphorylation suppression.
Transcriptome analysis of the Brucella abortus BvrR/BvrS two-component regulatory system.
Directory of Open Access Journals (Sweden)
Cristina Viadas
Full Text Available BACKGROUND: The two-component BvrR/BvrS system is essential for Brucella abortus virulence. It was shown previously that its dysfunction alters the expression of some major outer membrane proteins and the pattern of lipid A acylation. To determine the genes regulated by BvrR/BvrS, we performed a whole-genome microarray analysis using B. abortus RNA obtained from wild type and bvrR mutant cells grown in the same conditions. METHODOLOGY/PRINCIPAL FINDINGS: A total of 127 differentially expressed genes were found: 83 were over expressed and 44 were less expressed in the bvrR mutant. Two operons, the phosphotransferase system and the maltose transport system, were down-regulated. Several genes involved in cell envelope or outer membrane biogenesis were differentially expressed: genes for outer membrane proteins (omp25a, omp25d, lipoproteins, LPS and fatty acid biosynthesis, stress response proteins, chaperones, flagellar genes, and twelve genes encoding ABC transport systems. Ten genes related with carbon metabolism (pckA and fumB among others were up-regulated in the bvrR mutant, and denitrification genes (nirK, norC and nosZ were also regulated. Notably, seven transcriptional regulators were affected, including VjbR, ExoR and OmpR that were less expressed in the bvrR mutant. Finally, the expression of eleven genes which have been previously related with Brucella virulence was also altered. CONCLUSIONS/SIGNIFICANCE: All these data corroborate the impact of BvrR/BvrS on cell envelope modulation, confirm that this system controls the carbon and nitrogen metabolism, and suggest a cross-talk among some regulators to adjust the Brucella physiology to the shift expected to occur during the transit from the extracellular to the intracellular niche.
Energy Technology Data Exchange (ETDEWEB)
Nohaile, M J [Univ. of California, Berkeley, CA (United States). Dept. of Chemistry
1996-05-01
Multidimensional heteronuclear NMR spectroscopy was used to investigate the N-terminal domain of the transcriptional enhancer NTRC (NiTrogen Regulatory protein C). This domain belongs to the family of receiver domains of two-component regulatory systems involved in signal transduction. Phosphorylation of NTRC at D54 leads to an activated form of the molecule which stimulates transcription of genes involved in nitrogen regulation. Three and four dimensional NMR techniques were used to determine an intermediate resolution structure of the unphosphorylated, inactive form of the N-terminal domain of NTRC. The structure is comprised of five {alpha}-helices and a five-stranded {beta}-sheet in a ({beta}/{alpha}){sub 5} topology. Analysis of the backbone dynamics of NTRC indicate that helix 4 and strand 5 are significantly more flexible than the rest of the secondary structure of the protein and that the loops making up the active site are flexible. The short lifetime of phospho-NTRC hampers the study of this form. However, conditions for determining the resonance assignments and, possibly, the three dimensional structure of phosphorylated NTRC have been obtained. Tentative assignments of the phosphorylated form indicate that the majority of the changes that NTRC experiences upon phosphorylation occur in helix 3, strand 4, helix 4, strand 5, and the loop between strand 5 and helix 5 (the 3445 face of NTRC) as well as near the site of phosphorylation. In order to examine a stable, activated form of the protein, constitutively active mutants of NTRC were investigated.
Gene Regulation by the LiaSR Two-Component System in Streptococcus mutans.
Directory of Open Access Journals (Sweden)
Manoharan Shankar
Full Text Available The LiaSR two-component signal transduction system regulates cellular responses to several environmental stresses, including those that induce cell envelope damages. Downstream regulons of the LiaSR system have been implicated in tolerance to acid, antibiotics and detergents. In the dental pathogen Streptococcus mutans, the LiaSR system is necessary for tolerance against acid, antibiotics, and cell wall damaging stresses during growth in the oral cavity. To understand the molecular mechanisms by which LiaSR regulates gene expression, we created a mutant LiaR in which the conserved aspartic acid residue (the phosphorylation site, was changed to alanine residue (D58A. As expected, the LiaR-D58A variant was unable to acquire the phosphate group and bind to target promoters. We also noted that the predicted LiaR-binding motif upstream of the lia operon does not appear to be well conserved. Consistent with this observation, we found that LiaR was unable to bind to the promoter region of lia; however, we showed that LiaR was able to bind to the promoters of SMU.753, SMU.2084 and SMU.1727. Based on sequence analysis and DNA binding studies we proposed a new 25-bp conserved motif essential for LiaR binding. Introducing alterations at fully conserved positions in the 25-bp motif affected LiaR binding, and the binding was dependent on the combination of positions that were altered. By scanning the S. mutans genome for the occurrence of the newly defined LiaR binding motif, we identified the promoter of hrcA (encoding a key regulator of the heat shock response that contains a LiaR binding motif, and we showed that hrcA is negatively regulated by the LiaSR system. Taken together our results suggest a putative role of the LiaSR system in heat shock responses of S. mutans.
Eguchi, Yoko; Ishii, Eiji; Hata, Kensuke; Utsumi, Ryutaro
2011-03-01
Two-component signal transduction systems (TCSs), utilized extensively by bacteria and archaea, are involved in the rapid adaptation of the organisms to fluctuating environments. A typical TCS transduces the signal by a phosphorelay between the sensor histidine kinase and its cognate response regulator. Recently, small-sized proteins that link TCSs have been reported and are called "connectors." Their physiological roles, however, have remained elusive. SafA (sensor associating factor A) (formerly B1500), a small (65-amino-acid [65-aa]) membrane protein, is among such connectors and links Escherichia coli TCSs EvgS/EvgA and PhoQ/PhoP. Since the activation of the EvgS/EvgA system induces acid resistance, we examined whether the SafA-activated PhoQ/PhoP system is also involved in the acid resistance induced by EvgS/EvgA. Using a constitutively active evgS1 mutant for the activation of EvgS/EvgA, we found that SafA, PhoQ, and PhoP all contributed to the acid resistance phenotype. Moreover, EvgS/EvgA activation resulted in the accumulation of cellular RpoS in the exponential-phase cells in a SafA-, PhoQ-, and PhoP-dependent manner. This RpoS accumulation was caused by another connector, IraM, expression of which was induced by the activation of the PhoQ/PhoP system, thus preventing RpoS degradation by trapping response regulator RssB. Acid resistance assays demonstrated that IraM also participated in the EvgS/EvgA-induced acid resistance. Therefore, we propose a model of a signal transduction cascade proceeding from EvgS/EvgA to PhoQ/PhoP and then to RssB (connected by SafA and IraM) and discuss its contribution to the acid resistance phenotype.
Signal integration by the two-component signal transduction response regulator CpxR.
Wolfe, Alan J; Parikh, Niyati; Lima, Bruno P; Zemaitaitis, Bozena
2008-04-01
The CpxAR two-component signal transduction system in Escherichia coli and other pathogens senses diverse envelope stresses and promotes the transcription of a variety of genes that remedy these stresses. An important member of the CpxAR regulon is cpxP. The CpxA-dependent transcription of cpxP has been linked to stresses such as misfolded proteins and alkaline pH. It also has been proposed that acetyl phosphate, the intermediate of the phosphotransacetylase (Pta)-acetate kinase (AckA) pathway, can activate the transcription of cpxP in a CpxA-independent manner by donating its phosphoryl group to CpxR. We tested this hypothesis by measuring the transcription of cpxP using mutants with mutations in the CpxAR pathway, mutants with mutations in the Pta-AckA pathway, and mutants with a combination of both types of mutations. From this epistasis analysis, we learned that CpxR integrates diverse stimuli. The stimuli that originate in the envelope depend on CpxA, while those associated with growth and central metabolism depend on the Pta-AckA pathway. While CpxR could receive a phosphoryl group from acetyl phosphate, this global signal was not the primary trigger for CpxR activation associated with the Pta-AckA pathway. On the strength of these results, we contend that the interactions between central metabolism and signal transduction can be quite complex and that successful investigations of such interactions must include a complete epistatic analysis.
Banerjee, Rahul; Yan, Honggao; Cukier, Robert I
2014-05-08
Signal transduction can be accomplished via a two-component system (TCS) consisting of a histidine kinase (HK) and a response regulator (RR). In this work, we simulate the response regulator RR468 from Thermotoga maritima, in which phosphorylation and dephosphorylation of a conserved aspartate residue acts as a switch via a large conformational change concentrated in three proximal loops. A detailed view of the conformational transition is obscured by the lack of stability of the intermediate states, which are difficult to detect using common structural biology techniques. Molecular dynamics (MD) trajectories of the inactive and active conformations were run, and show that the inactive (or active) trajectories do not exhibit sampling of the active (or inactive) conformations on this time scale. Targeted MD (TMD) was used to generate trajectories that span the inactive and active conformations and provide a view of how a localized event like phosphorylation can lead to conformational changes elsewhere in the protein, especially in the three proximal loops. The TMD trajectories are clustered to identify stages along the transition path. Residue interaction networks are identified that point to key residues having to rearrange in the process of transition. These are identified using both hydrogen bond analysis and residue interaction strength measurements. Potentials of mean force are generated for key residue rearrangements to ascertain their free energy barriers. We introduce methods that attempt to extrapolate from one conformation to the other and find that the most fluctuating proximal loop can transit part way from one to the other, suggesting that this conformational information is embedded in the sequence.
Imidazole as a Small Molecule Analogue in Two-Component Signal Transduction.
Page, Stephani C; Silversmith, Ruth E; Collins, Edward J; Bourret, Robert B
2015-12-15
In two-component signal transduction systems (TCSs), responses to stimuli are mediated through phosphotransfer between protein components. Canonical TCSs use His → Asp phosphotransfer in which phosphoryl groups are transferred from a conserved His on a sensory histidine kinase (HK) to a conserved Asp on a response regulator (RR). RRs contain the catalytic core of His → Asp phosphotransfer, evidenced by the ability of RRs to autophosphorylate with small molecule analogues of phospho-His proteins. Phosphorelays are a more complex variation of TCSs that additionally utilize Asp → His phosphotransfer through the use of an additional component, the histidine-containing phosphotransfer domain (Hpt), which reacts with RRs both as phosphodonors and phosphoacceptors. Here we show that imidazole has features of a rudimentary Hpt. Imidazole acted as a nucleophile and attacked phosphorylated RRs (RR-P) to produce monophosphoimidazole (MPI) and unphosphorylated RR. Phosphotransfer from RR-P to imidazole required the intact RR active site, indicating that the RR provided the core catalytic machinery for Asp → His phosphotransfer. Imidazole functioned in an artificial phosphorelay to transfer phosphoryl groups between unrelated RRs. The X-ray crystal structure of an activated RR·imidazole complex showed imidazole oriented in the RR active site similarly to the His of an Hpt. Imidazole interacted with RR nonconserved active site residues, which influenced the relative reactivity of RR-P with imidazole versus water. Rate constants for reaction of imidazole or MPI with chimeric RRs suggested that the RR active site contributes to the kinetic preferences exhibited by the YPD1 Hpt.
Temporal Variability from the Two-Component Advective Flow Solution and Its Observational Evidence
Dutta, Broja G.; Chakrabarti, Sandip K.
2016-09-01
In the propagating oscillatory shock model, the oscillation of the post-shock region, i.e., the Compton cloud, causes the observed low-frequency quasi-periodic oscillations (QPOs). The evolution of QPO frequency is explained by the systematic variation of the Compton cloud size, i.e., the steady radial movement of the shock front, which is triggered by the cooling of the post-shock region. Thus, analysis of the energy-dependent temporal properties in different variability timescales can diagnose the dynamics and geometry of accretion flows around black holes. We study these properties for the high-inclination black hole source XTE J1550-564 during its 1998 outburst and the low-inclination black hole source GX 339-4 during its 2006-07 outburst using RXTE/PCA data, and we find that they can satisfactorily explain the time lags associated with the QPOs from these systems. We find a smooth decrease of the time lag as a function of time in the rising phase of both sources. In the declining phase, the time lag increases with time. We find a systematic evolution of QPO frequency and hard lags in these outbursts. In XTE J1550-564, the lag changes from hard to soft (i.e., from a positive to a negative value) at a crossing frequency (ν c) of ˜3.4 Hz. We present possible mechanisms to explain the lag behavior of high and low-inclination sources within the framework of a single two-component advective flow model.
Large-scale Models Reveal the Two-component Mechanics of Striated Muscle
Directory of Open Access Journals (Sweden)
Robert Jarosch
2008-12-01
Full Text Available This paper provides a comprehensive explanation of striated muscle mechanics and contraction on the basis of filament rotations. Helical proteins, particularly the coiled-coils of tropomyosin, myosin and ÃŽÂ±-actinin, shorten their H-bonds cooperatively and produce torque and filament rotations when the Coulombic net-charge repulsion of their highly charged side-chains is diminished by interaction with ions. The classical Ã¢Â€Âœtwo-component modelÃ¢Â€Â of active muscle differentiated a Ã¢Â€Âœcontractile componentÃ¢Â€Â which stretches the Ã¢Â€Âœseries elastic componentÃ¢Â€Â during force production. The contractile components are the helically shaped thin filaments of muscle that shorten the sarcomeres by clockwise drilling into the myosin cross-bridges with torque decrease (= force-deficit. Muscle stretch means drawing out the thin filament helices off the cross-bridges under passive counterclockwise rotation with torque increase (= stretch activation. Since each thin filament is anchored by four elastic ÃŽÂ±-actinin Z-filaments (provided with forceregulating sites for Ca2+ binding, the thin filament rotations change the torsional twist of the four Z-filaments as the Ã¢Â€Âœseries elastic componentsÃ¢Â€Â. Large scale models simulate the changes of structure and force in the Z-band by the different Z-filament twisting stages A, B, C, D, E, F and G. Stage D corresponds to the isometric state. The basic phenomena of muscle physiology, i. e. latency relaxation, Fenn-effect, the force-velocity relation, the length-tension relation, unexplained energy, shortening heat, the Huxley-Simmons phases, etc. are explained and interpreted with the help of the model experiments.