Stochastic coupled cluster theory: Efficient sampling of the coupled cluster expansion
NASA Astrophysics Data System (ADS)
Scott, Charles J. C.; Thom, Alex J. W.
2017-09-01
We consider the sampling of the coupled cluster expansion within stochastic coupled cluster theory. Observing the limitations of previous approaches due to the inherently non-linear behavior of a coupled cluster wavefunction representation, we propose new approaches based on an intuitive, well-defined condition for sampling weights and on sampling the expansion in cluster operators of different excitation levels. We term these modifications even and truncated selections, respectively. Utilising both approaches demonstrates dramatically improved calculation stability as well as reduced computational and memory costs. These modifications are particularly effective at higher truncation levels owing to the large number of terms within the cluster expansion that can be neglected, as demonstrated by the reduction of the number of terms to be sampled when truncating at triple excitations by 77% and hextuple excitations by 98%.
Properties of coupled-cluster equations originating in excitation sub-algebras
NASA Astrophysics Data System (ADS)
Kowalski, Karol
2018-03-01
In this paper, we discuss properties of single-reference coupled cluster (CC) equations associated with the existence of sub-algebras of excitations that allow one to represent CC equations in a hybrid fashion where the cluster amplitudes associated with these sub-algebras can be obtained by solving the corresponding eigenvalue problem. For closed-shell formulations analyzed in this paper, the hybrid representation of CC equations provides a natural way for extending active-space and seniority number concepts to provide an accurate description of electron correlation effects. Moreover, a new representation can be utilized to re-define iterative algorithms used to solve CC equations, especially for tough cases defined by the presence of strong static and dynamical correlation effects. We will also explore invariance properties associated with excitation sub-algebras to define a new class of CC approximations referred to in this paper as the sub-algebra-flow-based CC methods. We illustrate the performance of these methods on the example of ground- and excited-state calculations for commonly used small benchmark systems.
NASA Astrophysics Data System (ADS)
Lyakh, Dmitry I.
2018-03-01
A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra. Inspired by the hierarchical techniques from the renormalisation group approach, H/H2-matrix algebra and fast multipole method, the computational scaling reduction in our formalism is achieved via coarsening of quantum many-body interactions at larger interaction scales, thus imposing a hierarchical structure on many-body tensors of coupled-cluster theory. In our approach, the interaction scale can be defined on any appropriate Euclidean domain (spatial domain, momentum-space domain, energy domain, etc.). We show that the hierarchically resolved many-body tensors can reduce the storage requirements to O(N), where N is the number of simulated quantum particles. Subsequently, we prove that any connected many-body diagram consisting of a finite number of arbitrary-order tensors, e.g. an arbitrary coupled-cluster diagram, can be evaluated in O(NlogN) floating-point operations. On top of that, we suggest an additional approximation to further reduce the computational complexity of higher order coupled-cluster equations, i.e. equations involving higher than double excitations, which otherwise would introduce a large prefactor into formal O(NlogN) scaling.
Baglietto, Gabriel; Gigante, Guido; Del Giudice, Paolo
2017-01-01
Two, partially interwoven, hot topics in the analysis and statistical modeling of neural data, are the development of efficient and informative representations of the time series derived from multiple neural recordings, and the extraction of information about the connectivity structure of the underlying neural network from the recorded neural activities. In the present paper we show that state-space clustering can provide an easy and effective option for reducing the dimensionality of multiple neural time series, that it can improve inference of synaptic couplings from neural activities, and that it can also allow the construction of a compact representation of the multi-dimensional dynamics, that easily lends itself to complexity measures. We apply a variant of the 'mean-shift' algorithm to perform state-space clustering, and validate it on an Hopfield network in the glassy phase, in which metastable states are largely uncorrelated from memories embedded in the synaptic matrix. In this context, we show that the neural states identified as clusters' centroids offer a parsimonious parametrization of the synaptic matrix, which allows a significant improvement in inferring the synaptic couplings from the neural activities. Moving to the more realistic case of a multi-modular spiking network, with spike-frequency adaptation inducing history-dependent effects, we propose a procedure inspired by Boltzmann learning, but extending its domain of application, to learn inter-module synaptic couplings so that the spiking network reproduces a prescribed pattern of spatial correlations; we then illustrate, in the spiking network, how clustering is effective in extracting relevant features of the network's state-space landscape. Finally, we show that the knowledge of the cluster structure allows casting the multi-dimensional neural dynamics in the form of a symbolic dynamics of transitions between clusters; as an illustration of the potential of such reduction, we define and analyze a measure of complexity of the neural time series.
Coupled-cluster based R-matrix codes (CCRM): Recent developments
NASA Astrophysics Data System (ADS)
Sur, Chiranjib; Pradhan, Anil K.
2008-05-01
We report the ongoing development of the new coupled-cluster R-matrix codes (CCRM) for treating electron-ion scattering and radiative processes within the framework of the relativistic coupled-cluster method (RCC), interfaced with the standard R-matrix methodology. The RCC method is size consistent and in principle equivalent to an all-order many-body perturbation theory. The RCC method is one of the most accurate many-body theories, and has been applied for several systems. This project should enable the study of electron-interactions with heavy atoms/ions, utilizing not only high speed computing platforms but also improved theoretical description of the relativistic and correlation effects for the target atoms/ions as treated extensively within the RCC method. Here we present a comprehensive outline of the newly developed theoretical method and a schematic representation of the new suite of CCRM codes. We begin with the flowchart and description of various stages involved in this development. We retain the notations and nomenclature of different stages as analogous to the standard R-matrix codes.
Wang, Yang; Wu, Lin
2018-07-01
Low-Rank Representation (LRR) is arguably one of the most powerful paradigms for Multi-view spectral clustering, which elegantly encodes the multi-view local graph/manifold structures into an intrinsic low-rank self-expressive data similarity embedded in high-dimensional space, to yield a better graph partition than their single-view counterparts. In this paper we revisit it with a fundamentally different perspective by discovering LRR as essentially a latent clustered orthogonal projection based representation winged with an optimized local graph structure for spectral clustering; each column of the representation is fundamentally a cluster basis orthogonal to others to indicate its members, which intuitively projects the view-specific feature representation to be the one spanned by all orthogonal basis to characterize the cluster structures. Upon this finding, we propose our technique with the following: (1) We decompose LRR into latent clustered orthogonal representation via low-rank matrix factorization, to encode the more flexible cluster structures than LRR over primal data objects; (2) We convert the problem of LRR into that of simultaneously learning orthogonal clustered representation and optimized local graph structure for each view; (3) The learned orthogonal clustered representations and local graph structures enjoy the same magnitude for multi-view, so that the ideal multi-view consensus can be readily achieved. The experiments over multi-view datasets validate its superiority, especially over recent state-of-the-art LRR models. Copyright © 2018 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Shaw, W. M., Jr.
1991-01-01
Two articles discuss the clustering of composite representations in the Cystic Fibrosis Document Collection from the National Library of Medicine's MEDLINE file. Clustering is evaluated as a function of the exhaustivity of composite representations based on Medical Subject Headings (MeSH) and citation indexes, and evaluation of retrieval…
Novel strategy to implement active-space coupled-cluster methods
NASA Astrophysics Data System (ADS)
Rolik, Zoltán; Kállay, Mihály
2018-03-01
A new approach is presented for the efficient implementation of coupled-cluster (CC) methods including higher excitations based on a molecular orbital space partitioned into active and inactive orbitals. In the new framework, the string representation of amplitudes and intermediates is used as long as it is beneficial, but the contractions are evaluated as matrix products. Using a new diagrammatic technique, the CC equations are represented in a compact form due to the string notations we introduced. As an application of these ideas, a new automated implementation of the single-reference-based multi-reference CC equations is presented for arbitrary excitation levels. The new program can be considered as an improvement over the previous implementations in many respects; e.g., diagram contributions are evaluated by efficient vectorized subroutines. Timings for test calculations for various complete active-space problems are presented. As an application of the new code, the weak interactions in the Be dimer were studied.
Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming
2018-02-28
The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.
Orms, Natalie; Krylov, Anna I
2018-04-12
The experimental photoelectron spectra of di- and triatomic copper oxide anions have been reported previously. We present an analysis of the experimental spectra of the CuO - , Cu 2 O - , and CuO 2 - anions using equation-of-motion coupled-cluster (EOM-CC) methods. The open-shell electronic structure of each molecule demands a unique combination of EOM-CC methods to achieve an accurate and balanced representation of the multiconfigurational anionic- and neutral-state manifolds. Analysis of the Dyson orbitals associated with photodetachment from CuO - reveals the strong non-Koopmans character of the CuO states. For the lowest detachment energy, a good agreement between theoretical and experimental values is obtained with CCSD(T) (coupled-cluster with single and double excitations and perturbative account of triple excitations). The (T) correction is particularly important for Cu 2 O - . Use of a relativistic pseudopotential and matching basis set improves the quality of results in most cases. EOM-DIP-CCSD analysis of the low-lying states of CuO 2 - reveals multiple singlet and triplet anionic states near the triplet ground state, adding an extra layer of complexity to the interpretation of the experimental CuO 2 - photoelectron spectrum.
Subspace Clustering via Learning an Adaptive Low-Rank Graph.
Yin, Ming; Xie, Shengli; Wu, Zongze; Zhang, Yun; Gao, Junbin
2018-08-01
By using a sparse representation or low-rank representation of data, the graph-based subspace clustering has recently attracted considerable attention in computer vision, given its capability and efficiency in clustering data. However, the graph weights built using the representation coefficients are not the exact ones as the traditional definition is in a deterministic way. The two steps of representation and clustering are conducted in an independent manner, thus an overall optimal result cannot be guaranteed. Furthermore, it is unclear how the clustering performance will be affected by using this graph. For example, the graph parameters, i.e., the weights on edges, have to be artificially pre-specified while it is very difficult to choose the optimum. To this end, in this paper, a novel subspace clustering via learning an adaptive low-rank graph affinity matrix is proposed, where the affinity matrix and the representation coefficients are learned in a unified framework. As such, the pre-computed graph regularizer is effectively obviated and better performance can be achieved. Experimental results on several famous databases demonstrate that the proposed method performs better against the state-of-the-art approaches, in clustering.
Harmonic oscillator representation in the theory of scattering and nuclear reactions
NASA Technical Reports Server (NTRS)
Smirnov, Yuri F.; Shirokov, A. M.; Lurie, Yuri, A.; Zaitsev, S. A.
1995-01-01
The following questions, concerning the application of the harmonic oscillator representation (HOR) in the theory of scattering and reactions, are discussed: the formulation of the scattering theory in HOR; exact solutions of the free motion Schroedinger equation in HOR; separable expansion of the short range potentials and the calculation of the phase shifts; 'isolated states' as generalization of the Wigner-von Neumann bound states embedded in continuum; a nuclear coupled channel problem in HOR; and the description of true three body scattering in HOR. As an illustration the soft dipole mode in the (11)Li nucleus is considered in a frame of the (9)Li+n+n cluster model taking into account of three body continuum effects.
NASA Astrophysics Data System (ADS)
Aoyama, Shigeyoshi
2013-04-01
The study of the 4He nucleus is important because it is the most basic sub-unit (cluster) in nuclei. We have investigated the structures and the reaction mechanisms in 4He by using the correlated Gaussian basis function with the global vector representation. In order to treat the boundary condition for the ab-initio calculation of the four nucleons, we employ the Microscopic R-matrix Method (MRM) and the Complex Scaling Method (CSM) . Elastic-scattering phase shifts for four-nucleon systems are studied in an ab-initio type cluster model with MRM in order to clarify the role of the tensor force and to investigate cluster distortions in low energy d+d and t+p scattering. For 1S0, the calculated phase shifts show that the t+p and h+n channels are strongly coupled to the d+d channel for the case of the realistic interaction.
NASA Astrophysics Data System (ADS)
Sen, Sangita; Shee, Avijit; Mukherjee, Debashis
2018-02-01
The orbital relaxation attendant on ionization is particularly important for the core electron ionization potential (core IP) of molecules. The Unitary Group Adapted State Universal Coupled Cluster (UGA-SUMRCC) theory, recently formulated and implemented by Sen et al. [J. Chem. Phys. 137, 074104 (2012)], is very effective in capturing orbital relaxation accompanying ionization or excitation of both the core and the valence electrons [S. Sen et al., Mol. Phys. 111, 2625 (2013); A. Shee et al., J. Chem. Theory Comput. 9, 2573 (2013)] while preserving the spin-symmetry of the target states and using the neutral closed-shell spatial orbitals of the ground state. Our Ansatz invokes a normal-ordered exponential representation of spin-free cluster-operators. The orbital relaxation induced by a specific set of cluster operators in our Ansatz is good enough to eliminate the need for different sets of orbitals for the ground and the core-ionized states. We call the single configuration state function (CSF) limit of this theory the Unitary Group Adapted Open-Shell Coupled Cluster (UGA-OSCC) theory. The aim of this paper is to comprehensively explore the efficacy of our Ansatz to describe orbital relaxation, using both theoretical analysis and numerical performance. Whenever warranted, we also make appropriate comparisons with other coupled-cluster theories. A physically motivated truncation of the chains of spin-free T-operators is also made possible by the normal-ordering, and the operational resemblance to single reference coupled-cluster theory allows easy implementation. Our test case is the prediction of the 1s core IP of molecules containing a single light- to medium-heavy nucleus and thus, in addition to demonstrating the orbital relaxation, we have addressed the scalar relativistic effects on the accuracy of the IPs by using a hierarchy of spin-free Hamiltonians in conjunction with our theory. Additionally, the contribution of the spin-free component of the two-electron Gaunt term, not usually taken into consideration, has been estimated at the Self-Consistent Field (ΔSCF) level and is found to become increasingly important and eventually quite prominent for molecules with third period atoms and below. The accuracies of the IPs computed using UGA-OSCC are found to be of the same order as the Coupled Cluster Singles Doubles (ΔCCSD) values while being free from spin contamination. Since the UGA-OSCC uses a common set of orbitals for the ground state and the ion, it obviates the need of two N5 AO to MO transformation in contrast to the ΔCCSD method.
Sen, Sangita; Shee, Avijit; Mukherjee, Debashis
2018-02-07
The orbital relaxation attendant on ionization is particularly important for the core electron ionization potential (core IP) of molecules. The Unitary Group Adapted State Universal Coupled Cluster (UGA-SUMRCC) theory, recently formulated and implemented by Sen et al. [J. Chem. Phys. 137, 074104 (2012)], is very effective in capturing orbital relaxation accompanying ionization or excitation of both the core and the valence electrons [S. Sen et al., Mol. Phys. 111, 2625 (2013); A. Shee et al., J. Chem. Theory Comput. 9, 2573 (2013)] while preserving the spin-symmetry of the target states and using the neutral closed-shell spatial orbitals of the ground state. Our Ansatz invokes a normal-ordered exponential representation of spin-free cluster-operators. The orbital relaxation induced by a specific set of cluster operators in our Ansatz is good enough to eliminate the need for different sets of orbitals for the ground and the core-ionized states. We call the single configuration state function (CSF) limit of this theory the Unitary Group Adapted Open-Shell Coupled Cluster (UGA-OSCC) theory. The aim of this paper is to comprehensively explore the efficacy of our Ansatz to describe orbital relaxation, using both theoretical analysis and numerical performance. Whenever warranted, we also make appropriate comparisons with other coupled-cluster theories. A physically motivated truncation of the chains of spin-free T-operators is also made possible by the normal-ordering, and the operational resemblance to single reference coupled-cluster theory allows easy implementation. Our test case is the prediction of the 1s core IP of molecules containing a single light- to medium-heavy nucleus and thus, in addition to demonstrating the orbital relaxation, we have addressed the scalar relativistic effects on the accuracy of the IPs by using a hierarchy of spin-free Hamiltonians in conjunction with our theory. Additionally, the contribution of the spin-free component of the two-electron Gaunt term, not usually taken into consideration, has been estimated at the Self-Consistent Field (ΔSCF) level and is found to become increasingly important and eventually quite prominent for molecules with third period atoms and below. The accuracies of the IPs computed using UGA-OSCC are found to be of the same order as the Coupled Cluster Singles Doubles (ΔCCSD) values while being free from spin contamination. Since the UGA-OSCC uses a common set of orbitals for the ground state and the ion, it obviates the need of two N 5 AO to MO transformation in contrast to the ΔCCSD method.
NASA Astrophysics Data System (ADS)
Lohmar, Johannes; Bambach, Markus; Karhausen, Kai F.
2013-01-01
Integrated computational materials engineering is an up to date method for developing new materials and optimizing complete process chains. In the simulation of a process chain, material models play a central role as they capture the response of the material to external process conditions. While much effort is put into their development and improvement, less attention is paid to their implementation, which is problematic because the representation of microstructure in the model has a decisive influence on modeling accuracy and calculation speed. The aim of this article is to analyze the influence of different microstructure representation concepts on the prediction of flow stress and microstructure evolution when using the same set of material equations. Scalar, tree-based and cluster-based concepts are compared for a multi-stage rolling process of an AA5182 alloy. It was found that implementation influences the predicted flow stress and grain size, in particular in the regime of coupled hardening and softening.
Lentes, K U; Mathieu, E; Bischoff, R; Rasmussen, U B; Pavirani, A
1993-01-01
Current methods for comparative analyses of protein sequences are 1D-alignments of amino acid sequences based on the maximization of amino acid identity (homology) and the prediction of secondary structure elements. This method has a major drawback once the amino acid identity drops below 20-25%, since maximization of a homology score does not take into account any structural information. A new technique called Hydrophobic Cluster Analysis (HCA) has been developed by Lemesle-Varloot et al. (Biochimie 72, 555-574), 1990). This consists of comparing several sequences simultaneously and combining homology detection with secondary structure analysis. HCA is primarily based on the detection and comparison of structural segments constituting the hydrophobic core of globular protein domains, with or without transmembrane domains. We have applied HCA to the analysis of different families of G-protein coupled receptors, such as catecholamine receptors as well as peptide hormone receptors. Utilizing HCA the thrombin receptor, a new and as yet unique member of the family of G-protein coupled receptors, can be clearly classified as being closely related to the family of neuropeptide receptors rather than to the catecholamine receptors for which the shape of the hydrophobic clusters and the length of their third cytoplasmic loop are very different. Furthermore, the potential of HCA to predict relationships between new putative and already characterized members of this family of receptors will be presented.
Fonseca, Ana; Nazaré, Bárbara; Canavarro, Maria Cristina
2018-07-01
This study aimed to investigate the effect of one's attachment representations on one's and the partner's caregiving representations. According to attachment theory, individual differences in parenting and caregiving behaviours may be a function of parents' caregiving representations of the self as caregiver, and of others as worthy of care, which are rooted on parents' attachment representations. Furthermore, the care-seeking and caregiving interactions that occur within the couple relationship may also shape individuals' caregiving representations. The sample comprised 286 cohabiting couples who were assessed during pregnancy (attachment representations) and one month post-birth (caregiving representations). Path analyses were used to examine effects among variables. Results showed that for mothers and fathers, their own more insecure attachment representations predicted their less positive caregiving representations of the self as caregiver and of others as worthy of help and more self-focused motivations for caregiving. Moreover, fathers' attachment representations were found to predict mothers' caregiving representations of themselves as caregivers. Secure attachment representations of both members of the couple seem to be an inner resource promoting parents' positive representations of caregiving, and should be assessed and fostered during the transition to parenthood in both members of the couple.
Context-Aware Local Binary Feature Learning for Face Recognition.
Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie
2018-05-01
In this paper, we propose a context-aware local binary feature learning (CA-LBFL) method for face recognition. Unlike existing learning-based local face descriptors such as discriminant face descriptor (DFD) and compact binary face descriptor (CBFD) which learn each feature code individually, our CA-LBFL exploits the contextual information of adjacent bits by constraining the number of shifts from different binary bits, so that more robust information can be exploited for face representation. Given a face image, we first extract pixel difference vectors (PDV) in local patches, and learn a discriminative mapping in an unsupervised manner to project each pixel difference vector into a context-aware binary vector. Then, we perform clustering on the learned binary codes to construct a codebook, and extract a histogram feature for each face image with the learned codebook as the final representation. In order to exploit local information from different scales, we propose a context-aware local binary multi-scale feature learning (CA-LBMFL) method to jointly learn multiple projection matrices for face representation. To make the proposed methods applicable for heterogeneous face recognition, we present a coupled CA-LBFL (C-CA-LBFL) method and a coupled CA-LBMFL (C-CA-LBMFL) method to reduce the modality gap of corresponding heterogeneous faces in the feature level, respectively. Extensive experimental results on four widely used face datasets clearly show that our methods outperform most state-of-the-art face descriptors.
Particle-hole symmetry in many-body theories of electron correlation
NASA Astrophysics Data System (ADS)
Kats, Daniel; Usvyat, Denis; Manby, Frederick R.
2018-06-01
Second-quantised creation and annihilation operators for fermionic particles anticommute, but the same is true for the creation and annihilation operators for holes. This introduces a symmetry into the quantum theory of fermions that is absent for bosons. In ab initio electronic structure theory, it is common to classify methods by the number of electrons for which the method returns exact results: for example Hartree-Fock theory is exact for one-electron systems, whereas coupled-cluster theory with single and double excitations is exact for two-electron systems. Here, we discuss the generalisation: methods based on approximate wavefunctions that are exact for n-particle systems are also exact for n-hole systems. Novel electron correlation methods that attempt to improve on the coupled-cluster framework sometimes retain this property, and sometimes lose it. Here, we argue for retaining particle-hole symmetry as a desirable design criterion of approximate electron correlation methods. Dispensing with it might lead to loss of n-representability of density matrices, and this in turn can lead to spurious long-range behaviour in the correlation energy.
Method for making 2-electron response reduced density matrices approximately N-representable
NASA Astrophysics Data System (ADS)
Lanssens, Caitlin; Ayers, Paul W.; Van Neck, Dimitri; De Baerdemacker, Stijn; Gunst, Klaas; Bultinck, Patrick
2018-02-01
In methods like geminal-based approaches or coupled cluster that are solved using the projected Schrödinger equation, direct computation of the 2-electron reduced density matrix (2-RDM) is impractical and one falls back to a 2-RDM based on response theory. However, the 2-RDMs from response theory are not N-representable. That is, the response 2-RDM does not correspond to an actual physical N-electron wave function. We present a new algorithm for making these non-N-representable 2-RDMs approximately N-representable, i.e., it has the right symmetry and normalization and it fulfills the P-, Q-, and G-conditions. Next to an algorithm which can be applied to any 2-RDM, we have also developed a 2-RDM optimization procedure specifically for seniority-zero 2-RDMs. We aim to find the 2-RDM with the right properties which is the closest (in the sense of the Frobenius norm) to the non-N-representable 2-RDM by minimizing the square norm of the difference between this initial response 2-RDM and the targeted 2-RDM under the constraint that the trace is normalized and the 2-RDM, Q-matrix, and G-matrix are positive semidefinite, i.e., their eigenvalues are non-negative. Our method is suitable for fixing non-N-representable 2-RDMs which are close to being N-representable. Through the N-representability optimization algorithm we add a small correction to the initial 2-RDM such that it fulfills the most important N-representability conditions.
cluML: A markup language for clustering and cluster validity assessment of microarray data.
Bolshakova, Nadia; Cunningham, Pádraig
2005-01-01
cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.
Model Selection for Monitoring CO2 Plume during Sequestration
DOE Office of Scientific and Technical Information (OSTI.GOV)
2014-12-31
The model selection method developed as part of this project mainly includes four steps: (1) assessing the connectivity/dynamic characteristics of a large prior ensemble of models, (2) model clustering using multidimensional scaling coupled with k-mean clustering, (3) model selection using the Bayes' rule in the reduced model space, (4) model expansion using iterative resampling of the posterior models. The fourth step expresses one of the advantages of the method: it provides a built-in means of quantifying the uncertainty in predictions made with the selected models. In our application to plume monitoring, by expanding the posterior space of models, the finalmore » ensemble of representations of geological model can be used to assess the uncertainty in predicting the future displacement of the CO2 plume. The software implementation of this approach is attached here.« less
Yonehara, Takehiro; Takatsuka, Kazuo
2012-12-14
We develop a theory and the method of its application for chemical dynamics in systems, in which the adiabatic potential energy hyper-surfaces (PES) are densely quasi-degenerate to each other in a wide range of molecular geometry. Such adiabatic electronic states tend to couple each other through strong nonadiabatic interactions. Technically, therefore, it is often extremely hard to accurately single out the individual PES in those systems. Moreover, due to the mutual nonadiabatic couplings that may spread wide in space and due to the energy-time uncertainty relation, the notion of the isolated and well-defined potential energy surface should lose the sense. On the other hand, such dense electronic states should offer a very interesting molecular field in which chemical reactions to proceed in characteristic manners. However, to treat these systems, the standard theoretical framework of chemical reaction dynamics, which starts from the Born-Oppenheimer approximation and ends up with quantum nuclear wavepacket dynamics, is not very useful. We here explore this problem with our developed nonadiabatic electron wavepacket theory, which we call the phase-space averaging and natural branching (PSANB) method [T. Yonehara and K. Takatsuka, J. Chem. Phys. 129, 134109 (2008)], or branching-path representation, in which the packets are propagated in time along the non-Born-Oppenheimer branching paths. In this paper, after outlining the basic theory, we examine using a one-dimensional model how well the PSANB method works with such densely quasi-degenerate nonadiabatic systems. To do so, we compare the performance of PSANB with the full quantum mechanical results and those given by the fewest switches surface hopping (FSSH) method, which is known to be one of the most reliable and flexible methods to date. It turns out that the PSANB electron wavepacket approach actually yields very good results with far fewer initial sampling paths. Then we apply the electron wavepacket dynamics in path-branching representation and the so-called semiclassical Ehrenfest theory to a hydrogen molecule embedded in twelve membered boron cluster (B(12)) in excited states, which are densely quasi-degenerate due to the vacancy in 2p orbitals of boron atom [1s(2)2s(2)2p(1)]. Bond dissociation of the hydrogen molecule quickly takes place in the cluster and the resultant hydrogen atoms are squeezed out to the surface of the cluster. We further study collision dynamics between H(2) and B(12), which also gives interesting phenomena. The present study suggests an interesting functionality of the boron clusters.
Allain, Ariane; Chauvot de Beauchêne, Isaure; Langenfeld, Florent; Guarracino, Yann; Laine, Elodie; Tchertanov, Luba
2014-01-01
Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach - MOdular NETwork Analysis (MONETA) - based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non-activated STAT5 proteins. Our theoretical prediction based on results obtained with MONETA was validated for KIT by in vitro experiments. MONETA is a versatile analytical and visualization tool entirely devoted to the understanding of the functioning/malfunctioning of allosteric regulation in proteins - a crucial basis to guide the discovery of next-generation allosteric drugs.
Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold
2014-12-01
In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.
Exploring the Structure of Spatial Representations
Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela
2016-01-01
It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681
Structure and energetics of Cr(CO)6 and Cr(CO)5
NASA Technical Reports Server (NTRS)
Barnes, Leslie A.; Liu, Bowen; Lindh, Roland
1993-01-01
The geometric structures and energetics of Cr(CO)6 and Cr(CO)5 are determined at the modified coupled-pair functional, single and double excitation coupled-cluster (CCSD), and CCSD(T) levels of theory. For Cr(CO)6, the structure and force constants for the totally symmetric representation are in good agreement with experimental data once basis set constants are taken into account. In the largest basis set at the CCSD(T) level of theory, the total binding energy of CR(CO)6 is estimated at around 140 kcal/mol, or about 86 percent of the experimental value. In contrast, the first bond energy of Cr(CO)6 is very well described at the CCSD(T) level of theory, with the best estimated value of 38 kcal/mol being within the experimental uncertainty.
Neural Systems Underlying Lexical Competition: An Eyetracking and fMRI Study
Righi, Giulia; Blumstein, Sheila E.; Mertus, John; Worden, Michael S.
2010-01-01
The present study investigated the neural bases of phonological onset competition using an eye tracking paradigm coupled with fMRI. Eighteen subjects were presented with an auditory target (e.g. beaker) and a visual display containing a pictorial representation of the target (e.g. beaker), an onset competitor (e.g. beetle), and two phonologically and semantically unrelated objects (e.g. shoe, hammer). Behavioral results replicated earlier research showing increased looks to the onset competitor compared to the unrelated items. fMRI results showed that lexical competition induced by shared phonological onsets recruits both frontal structures and posterior structures. Specifically, comparison between competitor and no-competitor trials elicited activation in two non-overlapping clusters in the left IFG, one located primarily within BA 44 and the other primarily located within BA 45, and one cluster in the left supramarginal gyrus extending into the posterior-superior temporal gyrus. These results indicate that the left IFG is sensitive to competition driven by phonological similarity and not only to competition among semantic/conceptual factors. Moreover, they indicate that the SMG is not only recruited in tasks requiring access to lexical form but is also recruited in tasks that require access to the conceptual representation of a word. PMID:19301991
Image fusion using sparse overcomplete feature dictionaries
Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt
2015-10-06
Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.
Assessing Air-Sea Interaction in the Evolving NASA GEOS Model
NASA Technical Reports Server (NTRS)
Clayson, Carol Anne; Roberts, J. Brent
2015-01-01
In order to understand how the climate responds to variations in forcing, one necessary component is to understand the full distribution of variability of exchanges of heat and moisture between the atmosphere and ocean. Surface heat and moisture fluxes are critical to the generation and decay of many coupled air-sea phenomena. These mechanisms operate across a number of scales and contain contributions from interactions between the anomalous (i.e. non-mean), often extreme-valued, flux components. Satellite-derived estimates of the surface turbulent and radiative heat fluxes provide an opportunity to assess results from modeling systems. Evaluation of only time mean and variability statistics, however only provides limited traceability to processes controlling what are often regime-dependent errors. This work will present an approach to evaluate the representation of the turbulent fluxes at the air-sea interface in the current and evolving Goddard Earth Observing System (GEOS) model. A temperature and moisture vertical profile-based clustering technique is used to identify robust weather regimes, and subsequently intercompare the turbulent fluxes and near-surface parameters within these regimes in both satellite estimates and GEOS-driven data sets. Both model reanalysis (MERRA) and seasonal-to-interannual coupled GEOS model simulations will be evaluated. Particular emphasis is placed on understanding the distribution of the fluxes including extremes, and the representation of near-surface forcing variables directly related to their estimation. Results from these analyses will help identify the existence and source of regime-dependent biases in the GEOS model ocean surface turbulent fluxes. The use of the temperature and moisture profiles for weather-state clustering will be highlighted for its potential broad application to 3-D output typical of model simulations.
Assessing air-sea interaction in the evolving NASA GEOS model
NASA Astrophysics Data System (ADS)
Clayson, C. A.; Roberts, J. B.
2014-12-01
In order to understand how the climate responds to variations in forcing, one necessary component is to understand the full distribution of variability of exchanges of heat and moisture between the atmosphere and ocean. Surface heat and moisture fluxes are critical to the generation and decay of many coupled air-sea phenomena. These mechanisms operate across a number of scales and contain contributions from interactions between the anomalous (i.e. non-mean), often extreme-valued, flux components. Satellite-derived estimates of the surface turbulent and radiative heat fluxes provide an opportunity to assess results from modeling systems. Evaluation of only time mean and variability statistics, however only provides limited traceability to processes controlling what are often regime-dependent errors. This work will present an approach to evaluate the representation of the turbulent fluxes at the air-sea interface in the current and evolving Goddard Earth Observing System (GEOS) model. A temperature and moisture vertical profile-based clustering technique is used to identify robust weather regimes, and subsequently intercompare the turbulent fluxes and near-surface parameters within these regimes in both satellite estimates and GEOS-driven data sets. Both model reanalysis (MERRA) and seasonal-to-interannual coupled GEOS model simulations will be evaluated. Particular emphasis is placed on understanding the distribution of the fluxes including extremes, and the representation of near-surface forcing variables directly related to their estimation. Results from these analyses will help identify the existence and source of regime-dependent biases in the GEOS model ocean surface turbulent fluxes. The use of the temperature and moisture profiles for weather-state clustering will be highlighted for its potential broad application to 3-D output typical of model simulations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peng, Bo; Kowalski, Karol
The representation and storage of two-electron integral tensors are vital in large- scale applications of accurate electronic structure methods. Low-rank representation and efficient storage strategy of integral tensors can significantly reduce the numerical overhead and consequently time-to-solution of these methods. In this paper, by combining pivoted incomplete Cholesky decomposition (CD) with a follow-up truncated singular vector decomposition (SVD), we develop a decomposition strategy to approximately represent the two-electron integral tensor in terms of low-rank vectors. A systematic benchmark test on a series of 1-D, 2-D, and 3-D carbon-hydrogen systems demonstrates high efficiency and scalability of the compound two-step decomposition ofmore » the two-electron integral tensor in our implementation. For the size of atomic basis set N_b ranging from ~ 100 up to ~ 2, 000, the observed numerical scaling of our implementation shows O(N_b^{2.5~3}) versus O(N_b^{3~4}) of single CD in most of other implementations. More importantly, this decomposition strategy can significantly reduce the storage requirement of the atomic-orbital (AO) two-electron integral tensor from O(N_b^4) to O(N_b^2 log_{10}(N_b)) with moderate decomposition thresholds. The accuracy tests have been performed using ground- and excited-state formulations of coupled- cluster formalism employing single and double excitations (CCSD) on several bench- mark systems including the C_{60} molecule described by nearly 1,400 basis functions. The results show that the decomposition thresholds can be generally set to 10^{-4} to 10^{-3} to give acceptable compromise between efficiency and accuracy.« less
Peng, Bo; Kowalski, Karol
2017-09-12
The representation and storage of two-electron integral tensors are vital in large-scale applications of accurate electronic structure methods. Low-rank representation and efficient storage strategy of integral tensors can significantly reduce the numerical overhead and consequently time-to-solution of these methods. In this work, by combining pivoted incomplete Cholesky decomposition (CD) with a follow-up truncated singular vector decomposition (SVD), we develop a decomposition strategy to approximately represent the two-electron integral tensor in terms of low-rank vectors. A systematic benchmark test on a series of 1-D, 2-D, and 3-D carbon-hydrogen systems demonstrates high efficiency and scalability of the compound two-step decomposition of the two-electron integral tensor in our implementation. For the size of the atomic basis set, N b , ranging from ∼100 up to ∼2,000, the observed numerical scaling of our implementation shows [Formula: see text] versus [Formula: see text] cost of performing single CD on the two-electron integral tensor in most of the other implementations. More importantly, this decomposition strategy can significantly reduce the storage requirement of the atomic orbital (AO) two-electron integral tensor from [Formula: see text] to [Formula: see text] with moderate decomposition thresholds. The accuracy tests have been performed using ground- and excited-state formulations of coupled cluster formalism employing single and double excitations (CCSD) on several benchmark systems including the C 60 molecule described by nearly 1,400 basis functions. The results show that the decomposition thresholds can be generally set to 10 -4 to 10 -3 to give acceptable compromise between efficiency and accuracy.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peng, Bo; Kowalski, Karol
In this paper we derive basic properties of the Green’s function matrix elements stemming from the exponential coupled cluster (CC) parametrization of the ground-state wave function. We demon- strate that all intermediates used to express retarded (or equivalently, ionized) part of the Green’s function in the ω-representation can be expressed through connected diagrams only. Similar proper- ties are also shared by the first order ω-derivatives of the retarded part of the CC Green’s function. This property can be extended to any order ω-derivatives of the Green’s function. Through the Dyson equation of CC Green’s function, the derivatives of corresponding CCmore » self-energy can be evaluated analytically. In analogy to the CC Green’s function, the corresponding CC self-energy is expressed in terms of connected diagrams only. Moreover, the ionized part of the CC Green’s func- tion satisfies the non-homogeneous linear system of ordinary differential equations, whose solution may be represented in the exponential form. Our analysis can be easily generalized to the advanced part of the CC Green’s function.« less
NASA Astrophysics Data System (ADS)
Shah, Shishir
This paper presents a segmentation method for detecting cells in immunohistochemically stained cytological images. A two-phase approach to segmentation is used where an unsupervised clustering approach coupled with cluster merging based on a fitness function is used as the first phase to obtain a first approximation of the cell locations. A joint segmentation-classification approach incorporating ellipse as a shape model is used as the second phase to detect the final cell contour. The segmentation model estimates a multivariate density function of low-level image features from training samples and uses it as a measure of how likely each image pixel is to be a cell. This estimate is constrained by the zero level set, which is obtained as a solution to an implicit representation of an ellipse. Results of segmentation are presented and compared to ground truth measurements.
Moody, Daniela; Wohlberg, Brendt
2018-01-02
An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.
Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao
2015-01-01
Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383
Sparse subspace clustering for data with missing entries and high-rank matrix completion.
Fan, Jicong; Chow, Tommy W S
2017-09-01
Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
Video based object representation and classification using multiple covariance matrices.
Zhang, Yurong; Liu, Quan
2017-01-01
Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.
Singlet-paired coupled cluster theory for open shells
NASA Astrophysics Data System (ADS)
Gomez, John A.; Henderson, Thomas M.; Scuseria, Gustavo E.
2016-06-01
Restricted single-reference coupled cluster theory truncated to single and double excitations accurately describes weakly correlated systems, but often breaks down in the presence of static or strong correlation. Good coupled cluster energies in the presence of degeneracies can be obtained by using a symmetry-broken reference, such as unrestricted Hartree-Fock, but at the cost of good quantum numbers. A large body of work has shown that modifying the coupled cluster ansatz allows for the treatment of strong correlation within a single-reference, symmetry-adapted framework. The recently introduced singlet-paired coupled cluster doubles (CCD0) method is one such model, which recovers correct behavior for strong correlation without requiring symmetry breaking in the reference. Here, we extend singlet-paired coupled cluster for application to open shells via restricted open-shell singlet-paired coupled cluster singles and doubles (ROCCSD0). The ROCCSD0 approach retains the benefits of standard coupled cluster theory and recovers correct behavior for strongly correlated, open-shell systems using a spin-preserving ROHF reference.
NASA Astrophysics Data System (ADS)
Xu, Yulong; Wang, Tingting; Wang, Dunyou
2012-11-01
The bimolecular nucleophilic substitution (SN2) reaction of CH3Br and OH- in aqueous solution was investigated using a multilayered-representation quantum mechanical and molecular mechanics methodology. Reactant complex, transition state, and product complex are identified and characterized in aqueous solution. The potentials of mean force are computed under both the density function theory and coupled-cluster single double (triple) (CCSD(T)) levels of theory for the reaction region. The results show that the aqueous environment has a significant impact on the reaction process. The solvation effect and the polarization effect combined raise the activation barrier height by ˜16.2 kcal/mol and the solvation effect is the dominant contribution to the potential of mean force. The CCSD(T)/MM representation presents a free energy activation barrier height of 22.8 kcal/mol and the rate constant at 298 K of 3.7 × 10-25 cm3 molecule-1 s-1 which agree very well with the experiment values at 23.0 kcal/mol and 2.6 × 10-25 cm3 molecule-1 s-1, respectively.
Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings
NASA Astrophysics Data System (ADS)
Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang
2013-12-01
This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.
ERIC Educational Resources Information Center
Shaw, W. M., Jr.
1990-01-01
These two articles discuss clustering structure in the Cystic Fibrosis Document Collection, which is derived from the National Library of Medicine's MEDLINE file. The exhaustivity of four subject representations and two citation representations is examined, and descriptor-weight thresholds and similarity thresholds are used to compute…
Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Zhang, Gang
2013-12-15
This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme ismore » confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.« less
NASA Astrophysics Data System (ADS)
Nguyen, Thuong T.; Székely, Eszter; Imbalzano, Giulio; Behler, Jörg; Csányi, Gábor; Ceriotti, Michele; Götz, Andreas W.; Paesani, Francesco
2018-06-01
The accurate representation of multidimensional potential energy surfaces is a necessary requirement for realistic computer simulations of molecular systems. The continued increase in computer power accompanied by advances in correlated electronic structure methods nowadays enables routine calculations of accurate interaction energies for small systems, which can then be used as references for the development of analytical potential energy functions (PEFs) rigorously derived from many-body (MB) expansions. Building on the accuracy of the MB-pol many-body PEF, we investigate here the performance of permutationally invariant polynomials (PIPs), neural networks, and Gaussian approximation potentials (GAPs) in representing water two-body and three-body interaction energies, denoting the resulting potentials PIP-MB-pol, Behler-Parrinello neural network-MB-pol, and GAP-MB-pol, respectively. Our analysis shows that all three analytical representations exhibit similar levels of accuracy in reproducing both two-body and three-body reference data as well as interaction energies of small water clusters obtained from calculations carried out at the coupled cluster level of theory, the current gold standard for chemical accuracy. These results demonstrate the synergy between interatomic potentials formulated in terms of a many-body expansion, such as MB-pol, that are physically sound and transferable, and machine-learning techniques that provide a flexible framework to approximate the short-range interaction energy terms.
Communication: A simplified coupled-cluster Lagrangian for polarizable embedding.
Krause, Katharina; Klopper, Wim
2016-01-28
A simplified coupled-cluster Lagrangian, which is linear in the Lagrangian multipliers, is proposed for the coupled-cluster treatment of a quantum mechanical system in a polarizable environment. In the simplified approach, the amplitude equations are decoupled from the Lagrangian multipliers and the energy obtained from the projected coupled-cluster equation corresponds to a stationary point of the Lagrangian.
Communication: A simplified coupled-cluster Lagrangian for polarizable embedding
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krause, Katharina; Klopper, Wim, E-mail: klopper@kit.edu
A simplified coupled-cluster Lagrangian, which is linear in the Lagrangian multipliers, is proposed for the coupled-cluster treatment of a quantum mechanical system in a polarizable environment. In the simplified approach, the amplitude equations are decoupled from the Lagrangian multipliers and the energy obtained from the projected coupled-cluster equation corresponds to a stationary point of the Lagrangian.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gomez, John A.; Henderson, Thomas M.; Scuseria, Gustavo E.
Restricted single-reference coupled cluster theory truncated to single and double excitations accurately describes weakly correlated systems, but often breaks down in the presence of static or strong correlation. Good coupled cluster energies in the presence of degeneracies can be obtained by using a symmetry-broken reference, such as unrestricted Hartree-Fock, but at the cost of good quantum numbers. A large body of work has shown that modifying the coupled cluster ansatz allows for the treatment of strong correlation within a single-reference, symmetry-adapted framework. The recently introduced singlet-paired coupled cluster doubles (CCD0) method is one such model, which recovers correct behavior formore » strong correlation without requiring symmetry breaking in the reference. Here, we extend singlet-paired coupled cluster for application to open shells via restricted open-shell singlet-paired coupled cluster singles and doubles (ROCCSD0). The ROCCSD0 approach retains the benefits of standard coupled cluster theory and recovers correct behavior for strongly correlated, open-shell systems using a spin-preserving ROHF reference.« less
Kögerler, Paul; Tsukerblat, Boris; Müller, Achim
2010-01-07
The structural versatility characterizing polyoxometalate chemistry, in combination with the option to deliberately use well-defined building blocks, serves as the foundation for the generation of a large family of magnetic clusters, frequently comprising highly symmetric spin arrays. If the spin centers are coupled by antiferromagnetic exchange, some of these systems exhibit spin frustration, which can result in novel magnetic properties of purely molecular origins. We discuss here the magnetic properties of selected nanosized polyoxometalate clusters featuring spin triangles as their magnetic 'building blocks' or fragments. This includes unique porous Keplerate clusters of the type {(Mo)Mo(5)}(12)M(30) (M = Fe(III), Cr(III), V(IV)) with the spin centers defining a regular icosidodecahedron and the {V(15)As(6)}-type cluster sphere containing a single equilateral spin triangle; these species are widely discussed and studied in the literature for their role in materials science as molecular representations of Kagomé lattices and in relation to quantum computing, respectively. Exhibiting fascinating and unique structural features, these magnetic molecules allow the study of the implications of frustrated spin ordering. Furthermore, this perspective covers the impact of spin frustration on the degeneracy of the ground state and related problems, namely strong magnetic anisotropy and the interplay of antisymmetric exchange and structural Jahn-Teller effects.
Identifying knowledge activism in worker health and safety representation: A cluster analysis.
Hall, Alan; Oudyk, John; King, Andrew; Naqvi, Syed; Lewchuk, Wayne
2016-01-01
Although worker representation in OHS has been widely recognized as contributing to health and safety improvements at work, few studies have examined the role that worker representatives play in this process. Using a large quantitative sample, this paper seeks to confirm findings from an earlier exploratory qualitative study that worker representatives can be differentiated by the knowledge intensive tactics and strategies that they use to achieve changes in their workplace. Just under 900 worker health and safety representatives in Ontario completed surveys which asked them to report on the amount of time they devoted to different types of representation activities (i.e., technical activities such as inspections and report writing vs. political activities such as mobilizing workers to build support), the kinds of conditions or hazards they tried to address through their representation (e.g., housekeeping vs. modifications in ventilation systems), and their reported success in making positive improvements. A cluster analysis was used to determine whether the worker representatives could be distinguished in terms of the relative time devoted to different activities and the clusters were then compared with reference to types of intervention efforts and outcomes. The cluster analysis identified three distinct groupings of representatives with significant differences in reported types of interventions and in their level of reported impact. Two of the clusters were consistent with the findings in the exploratory study, identified as knowledge activism for greater emphasis on knowledge based political activity and technical-legal representation for greater emphasis on formalized technical oriented procedures and legal regulations. Knowledge activists were more likely to take on challenging interventions and they reported more impact across the full range of interventions. This paper provides further support for the concepts of knowledge activism and technical-legal representation when differentiating the strategic orientations and impact of worker health and safety representatives, with important implications for education, political support and recruitment. © 2015 Wiley Periodicals, Inc.
Peng, Bo; Kowalski, Karol
2017-01-25
In this paper, we apply reverse Cuthill-McKee (RCM) algorithm to transform two-electron integral tensors to their block diagonal forms. By further applying Cholesky decomposition (CD) on each of the diagonal blocks, we are able to represent the high-dimensional two-electron integral tensors in terms of permutation matrices and low-rank Cholesky vectors. This representation facilitates low-rank factorizations of high-dimensional tensor contractions in post-Hartree-Fock calculations. Finally, we discuss the second-order Møller-Plesset (MP2) method and the linear coupled-cluster model with doubles (L-CCD) as examples to demonstrate the efficiency of this technique in representing the two-electron integrals in a compact form.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peng, Bo; Kowalski, Karol
In this paper, we apply reverse Cuthill-McKee (RCM) algorithm to transform two-electron integral tensors to their block diagonal forms. By further applying Cholesky decomposition (CD) on each of the diagonal blocks, we are able to represent the high-dimensional two-electron integral tensors in terms of permutation matrices and low-rank Cholesky vectors. This representation facilitates low-rank factorizations of high-dimensional tensor contractions in post-Hartree-Fock calculations. Finally, we discuss the second-order Møller-Plesset (MP2) method and the linear coupled-cluster model with doubles (L-CCD) as examples to demonstrate the efficiency of this technique in representing the two-electron integrals in a compact form.
Vendrell, Oriol; Brill, Michael; Gatti, Fabien; Lauvergnat, David; Meyer, Hans-Dieter
2009-06-21
Quantum dynamical calculations are reported for the zero point energy, several low-lying vibrational states, and the infrared spectrum of the H(5)O(2)(+) cation. The calculations are performed by the multiconfiguration time-dependent Hartree (MCTDH) method. A new vector parametrization based on a mixed Jacobi-valence description of the system is presented. With this parametrization the potential energy surface coupling is reduced with respect to a full Jacobi description, providing a better convergence of the n-mode representation of the potential. However, new coupling terms appear in the kinetic energy operator. These terms are derived and discussed. A mode-combination scheme based on six combined coordinates is used, and the representation of the 15-dimensional potential in terms of a six-combined mode cluster expansion including up to some 7-dimensional grids is discussed. A statistical analysis of the accuracy of the n-mode representation of the potential at all orders is performed. Benchmark, fully converged results are reported for the zero point energy, which lie within the statistical uncertainty of the reference diffusion Monte Carlo result for this system. Some low-lying vibrationally excited eigenstates are computed by block improved relaxation, illustrating the applicability of the approach to large systems. Benchmark calculations of the linear infrared spectrum are provided, and convergence with increasing size of the time-dependent basis and as a function of the order of the n-mode representation is studied. The calculations presented here make use of recent developments in the parallel version of the MCTDH code, which are briefly discussed. We also show that the infrared spectrum can be computed, to a very good approximation, within D(2d) symmetry, instead of the G(16) symmetry used before, in which the complete rotation of one water molecule with respect to the other is allowed, thus simplifying the dynamical problem.
Wang, Jong-Yi; Liang, Yia-Wen; Yeh, Chun-Chen; Liu, Chiu-Shong; Wang, Chen-Yu
2018-02-21
Spousal clustering of cancer warrants attention. Whether the common environment or high-age vulnerability determines cancer clustering is unclear. The risk of clustering in couples versus non-couples is undetermined. The time to cancer clustering after the first cancer diagnosis is yet to be reported. This study investigated cancer clustering over time among couples by using nationwide data. A cohort of 5643 married couples in the 2002-2013 Taiwan National Health Insurance Research Database was identified and randomly matched with 5643 non-couple pairs through dual propensity score matching. Factors associated with clustering (both spouses with tumours) were analysed by using the Cox proportional hazard model. Propensity-matched analysis revealed that the risk of clustering of all tumours among couples (13.70%) was significantly higher than that among non-couples (11.84%) (OR=1.182, 95% CI 1.058 to 1.321, P=0.0031). The median time to clustering of all tumours and of malignant tumours was 2.92 and 2.32 years, respectively. Risk characteristics associated with clustering included high age and comorbidity. Shared environmental factors among spouses might be linked to a high incidence of cancer clustering. Cancer incidence in one spouse may signal cancer vulnerability in the other spouse. Promoting family-oriented cancer care in vulnerable families and preventing shared lifestyle risk factors for cancer are suggested. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
The capacity limitations of orientation summary statistics
Attarha, Mouna; Moore, Cathleen M.
2015-01-01
The simultaneous–sequential method was used to test the processing capacity of establishing mean orientation summaries. Four clusters of oriented Gabor patches were presented in the peripheral visual field. One of the clusters had a mean orientation that was tilted either left or right while the mean orientations of the other three clusters were roughly vertical. All four clusters were presented at the same time in the simultaneous condition whereas the clusters appeared in temporal subsets of two in the sequential condition. Performance was lower when the means of all four clusters had to be processed concurrently than when only two had to be processed in the same amount of time. The advantage for establishing fewer summaries at a given time indicates that the processing of mean orientation engages limited-capacity processes (Experiment 1). This limitation cannot be attributed to crowding, low target-distractor discriminability, or a limited-capacity comparison process (Experiments 2 and 3). In contrast to the limitations of establishing multiple summary representations, establishing a single summary representation unfolds without interference (Experiment 4). When interpreted in the context of recent work on the capacity of summary statistics, these findings encourage reevaluation of the view that early visual perception consists of summary statistic representations that unfold independently across multiple areas of the visual field. PMID:25810160
Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering.
Wang, Changqing; Kipping, Judy; Bao, Chenglong; Ji, Hui; Qiu, Anqi
2016-01-01
The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children.
Ugurlu, Devran; Firat, Zeynep; Türe, Uğur; Unal, Gozde
2018-05-01
Accurate digital representation of major white matter bundles in the brain is an important goal in neuroscience image computing since the representations can be used for surgical planning, intra-patient longitudinal analysis and inter-subject population connectivity studies. Reconstructing desired fiber bundles generally involves manual selection of regions of interest by an expert, which is subject to user bias and fatigue, hence an automation is desirable. To that end, we first present a novel anatomical representation based on Neighborhood Resolved Fiber Orientation Distributions (NRFOD) along the fibers. The resolved fiber orientations are obtained by generalized q-sampling imaging (GQI) and a subsequent diffusion decomposition method. A fiber-to-fiber distance measure between the proposed fiber representations is then used in a density-based clustering framework to select the clusters corresponding to the major pathways of interest. In addition, neuroanatomical priors are utilized to constrain the set of candidate fibers before density-based clustering. The proposed fiber clustering approach is exemplified on automation of the reconstruction of the major fiber pathways in the brainstem: corticospinal tract (CST); medial lemniscus (ML); middle cerebellar peduncle (MCP); inferior cerebellar peduncle (ICP); superior cerebellar peduncle (SCP). Experimental results on Human Connectome Project (HCP)'s publicly available "WU-Minn 500 Subjects + MEG2 dataset" and expert evaluations demonstrate the potential of the proposed fiber clustering method in brainstem white matter structure analysis. Copyright © 2018 Elsevier B.V. All rights reserved.
Multiobjective synchronization of coupled systems
NASA Astrophysics Data System (ADS)
Tang, Yang; Wang, Zidong; Wong, W. K.; Kurths, Jürgen; Fang, Jian-an
2011-06-01
In this paper, multiobjective synchronization of chaotic systems is investigated by especially simultaneously minimizing optimization of control cost and convergence speed. The coupling form and coupling strength are optimized by an improved multiobjective evolutionary approach that includes a hybrid chromosome representation. The hybrid encoding scheme combines binary representation with real number representation. The constraints on the coupling form are also considered by converting the multiobjective synchronization into a multiobjective constraint problem. In addition, the performances of the adaptive learning method and non-dominated sorting genetic algorithm-II as well as the effectiveness and contributions of the proposed approach are analyzed and validated through the Rössler system in a chaotic or hyperchaotic regime and delayed chaotic neural networks.
More than one way to be happy: a typology of marital happiness.
Rauer, Amy; Volling, Brenda
2013-09-01
This study utilized observational and self-report data from 57 happily married couples to explore assumptions regarding marital happiness. Suggesting that happily married couples are not a homogeneous group, cluster analyses revealed the existence of three types of couples based on their observed behaviors in a problem-solving task: (1) mutually engaged couples (characterized by both spouses' higher negative and positive problem-solving); (2) mutually supportive couples (characterized by both spouses' higher positivity and support); and (3) wife compensation couples (characterized by high wife positivity). Although couples in all three clusters were equally happy with and committed to their marriages, these clusters were differentially associated with spouses' evaluations of their marriage. Spouses in the mutually supportive cluster reported greater intimacy and maintenance and less conflict and ambivalence, although this was more consistently the case in comparison to the wife compensation cluster, as opposed to the mutually engaged cluster. The implications of these typologies are discussed as they pertain to efforts on the part of both practitioners to promote marital happiness and repair marital relations when couples are faced with difficulties. © FPI, Inc.
Matovu, Joseph K B; Todd, Jim; Wanyenze, Rhoda K; Kairania, Robert; Serwadda, David; Wabwire-Mangen, Fred
2016-08-08
Uptake of couples' HIV counseling and testing (couples' HCT) services remains largely low in most settings. We report the effect of a demand-creation intervention trial on couples' HCT uptake among married or cohabiting individuals who had never received couples' HCT. This was a cluster-randomized intervention trial implemented in three study regions with differing HIV prevalence levels (range: 9-43 %) in Rakai district, southwestern Uganda, between February and September 2014. We randomly assigned six clusters (1:1) to receive the intervention or serve as the comparison arm using computer-generated random numbers. In the intervention clusters, individuals attended small group, couple and male-focused interactive sessions, reinforced with testimonies from 'expert couples', and received invitation coupons to test together with their partners at designated health facilities. In the comparison clusters, participants attended general adult health education sessions but received no invitation coupons. The primary outcome was couples' HCT uptake, measured 12 months post-baseline. Baseline data were collected between November 2013 and February 2014 while follow-up data were collected between March and April 2015. We conducted intention-to-treat analysis using a mixed effects Poisson regression model to assess for differences in couples' HCT uptake between the intervention and comparison clusters. Data analysis was conducted using STATA statistical software, version 14.1. Of 2135 married or cohabiting individuals interviewed at baseline, 42 % (n = 846) had ever received couples' HCT. Of those who had never received couples' HCT (n = 1,174), 697 were interviewed in the intervention clusters while 477 were interviewed in the comparison clusters. 73.6 % (n = 513) of those interviewed in the intervention and 82.6 % (n = 394) of those interviewed in the comparison cluster were interviewed at follow-up. Of those interviewed, 72.3 % (n = 371) in the intervention and 65.2 % (n = 257) in the comparison clusters received HCT. Couples' HCT uptake was higher in the intervention than in the comparison clusters (20.3 % versus 13.7 %; adjusted prevalence ratio (aPR) = 1.43, 95 % CI: 1.02, 2.01, P = 0.04). Our findings show that a small group, couple and male-focused, demand-creation intervention reinforced with testimonies from 'expert couples', improved uptake of couples' HCT in this rural setting. ClinicalTrials.gov, NCT02492061 . Date of registration: June 14, 2015.
Distinct collective states due to trade-off between attractive and repulsive couplings
NASA Astrophysics Data System (ADS)
Sathiyadevi, K.; Chandrasekar, V. K.; Senthilkumar, D. V.; Lakshmanan, M.
2018-03-01
We investigate the effect of repulsive coupling together with an attractive coupling in a network of nonlocally coupled oscillators. To understand the complex interaction between these two couplings we introduce a control parameter in the repulsive coupling which plays a crucial role in inducing distinct complex collective patterns. In particular, we show the emergence of various cluster chimera death states through a dynamically distinct transition route, namely the oscillatory cluster state and coherent oscillation death state as a function of the repulsive coupling in the presence of the attractive coupling. In the oscillatory cluster state, the oscillators in the network are grouped into two distinct dynamical states of homogeneous and inhomogeneous oscillatory states. Further, the network of coupled oscillators follow the same transition route in the entire coupling range. Depending upon distinct coupling ranges, the system displays different number of clusters in the death state and oscillatory state. We also observe that the number of coherent domains in the oscillatory cluster state exponentially decreases with increase in coupling range and obeys a power-law decay. Additionally, we show analytical stability for observed solitary state, synchronized state, and incoherent oscillation death state.
Corepressive interaction and clustering of degrade-and-fire oscillators
Fernandez, Bastien; Tsimring, Lev S.
2016-01-01
Strongly nonlinear degrade-and-fire (DF) oscillations may emerge in genetic circuits having a delayed negative feedback loop as their core element. Here we study the synchronization of DF oscillators coupled through a common repressor field. For weak coupling, initially distinct oscillators remain desynchronized. For stronger coupling, oscillators can be forced to wait in the repressed state until the global repressor field is sufficiently degraded, and then they fire simultaneously forming a synchronized cluster. Our analytical theory provides necessary and sufficient conditions for clustering and specifies the maximum number of clusters that can be formed in the asymptotic regime. We find that in the thermodynamic limit a phase transition occurs at a certain coupling strength from the weakly clustered regime with only microscopic clusters to a strongly clustered regime where at least one giant cluster has to be present. PMID:22181453
Janssens, Thomas; Orban, Guy A.
2014-01-01
The retinotopic organization of macaque occipitotemporal cortex rostral to area V4 and caudorostral to the recently described middle temporal (MT) cluster of the monkey (Kolster et al., 2009) is not well established. The proposed number of areas within this region varies from one to four, underscoring the ambiguity concerning the functional organization in this region of extrastriate cortex. We used phase-encoded retinotopic functional MRI mapping methods to reveal the functional topography of this cortical domain. Polar-angle maps showed one complete hemifield representation bordering area V4 anteriorly, split into dorsal and ventral counterparts corresponding to the lower and upper visual field quadrants, respectively. The location of this hemifield representation corresponds to area V4A. More rostroventrally, we identified three other complete hemifield representations. Two of these correspond to the dorsal and the ventral posterior inferotemporal areas (PITd and PITv, respectively) as identified in the Felleman and Van Essen (1991) scheme. The third representation has been tentatively named dorsal occipitotemporal area (OTd). Areas V4A, PITd, PITv, and OTd share a central visual field representation, similar to the areas constituting the MT cluster. Furthermore, they vary widely in size and represent the complete contralateral visual field. Functionally, these four areas show little motion sensitivity, unlike those of the MT cluster, and two of them, OTd and PITd, displayed pronounced two-dimensional shape sensitivity. In general, these results suggest that retinotopically organized tissue extends farther into rostral occipitotemporal cortex of the monkey than generally assumed. PMID:25080580
A coupled-cluster study of photodetachment cross sections of closed-shell anions
NASA Astrophysics Data System (ADS)
Cukras, Janusz; Decleva, Piero; Coriani, Sonia
2014-11-01
We investigate the performance of Stieltjes Imaging applied to Lanczos pseudo-spectra generated at the coupled cluster singles and doubles, coupled cluster singles and approximate iterative doubles and coupled cluster singles levels of theory in modeling the photodetachment cross sections of the closed shell anions H-, Li-, Na-, F-, Cl-, and OH-. The accurate description of double excitations is found to play a much more important role than in the case of photoionization of neutral species.
A coupled-cluster study of photodetachment cross sections of closed-shell anions.
Cukras, Janusz; Decleva, Piero; Coriani, Sonia
2014-11-07
We investigate the performance of Stieltjes Imaging applied to Lanczos pseudo-spectra generated at the coupled cluster singles and doubles, coupled cluster singles and approximate iterative doubles and coupled cluster singles levels of theory in modeling the photodetachment cross sections of the closed shell anions H(-), Li(-), Na(-), F(-), Cl(-), and OH(-). The accurate description of double excitations is found to play a much more important role than in the case of photoionization of neutral species.
Chen, Vicky; Paisley, John; Lu, Xinghua
2017-03-14
Cancer is a complex disease driven by somatic genomic alterations (SGAs) that perturb signaling pathways and consequently cellular function. Identifying patterns of pathway perturbations would provide insights into common disease mechanisms shared among tumors, which is important for guiding treatment and predicting outcome. However, identifying perturbed pathways is challenging, because different tumors can have the same perturbed pathways that are perturbed by different SGAs. Here, we designed novel semantic representations that capture the functional similarity of distinct SGAs perturbing a common pathway in different tumors. Combining this representation with topic modeling would allow us to identify patterns in altered signaling pathways. We represented each gene with a vector of words describing its function, and we represented the SGAs of a tumor as a text document by pooling the words representing individual SGAs. We applied the nested hierarchical Dirichlet process (nHDP) model to a collection of tumors of 5 cancer types from TCGA. We identified topics (consisting of co-occurring words) representing the common functional themes of different SGAs. Tumors were clustered based on their topic associations, such that each cluster consists of tumors sharing common functional themes. The resulting clusters contained mixtures of cancer types, which indicates that different cancer types can share disease mechanisms. Survival analysis based on the clusters revealed significant differences in survival among the tumors of the same cancer type that were assigned to different clusters. The results indicate that applying topic modeling to semantic representations of tumors identifies patterns in the combinations of altered functional pathways in cancer.
Burkatzki, M; Filippi, Claudia; Dolg, M
2008-10-28
We extend our recently published set of energy-consistent scalar-relativistic Hartree-Fock pseudopotentials by the 3d-transition metal elements, scandium through zinc. The pseudopotentials do not exhibit a singularity at the nucleus and are therefore suitable for quantum Monte Carlo (QMC) calculations. The pseudopotentials and the accompanying basis sets (VnZ with n=T,Q) are given in standard Gaussian representation and their parameter sets are presented. Coupled cluster, configuration interaction, and QMC studies are carried out for the scandium and titanium atoms and their oxides, demonstrating the good performance of the pseudopotentials. Even though the choice of pseudopotential form is motivated by QMC, these pseudopotentials can also be employed in other quantum chemical approaches.
Age-Related Declines in the Fidelity of Newly Acquired Category Representations
ERIC Educational Resources Information Center
Davis, Tyler; Love, Bradley C.; Maddox, W. Todd
2012-01-01
We present a theory suggesting that the ability to build category representations that reflect the nuances of category structures in the environment depends upon clustering mechanisms instantiated in an MTL-PFC-based circuit. Because function in this circuit declines with age, we predict that the ability to build category representations will be…
Mental Representations of Attachment in Identical Female Twins with and without Conduct Problems
ERIC Educational Resources Information Center
Constantino, John N.; Chackes, Laura M.; Wartner, Ulrike G.; Gross, Maggie; Brophy, Susan L.; Vitale, Josie; Heath, Andrew C.
2006-01-01
Insecure mental representations of attachment, a nearly invariant feature of cluster B personality disorders, have never previously been studied in twins. We conducted the Adult Attachment Interview (AAI) on 33 pairs of monozygotic (MZ) female twins reared together as an initial exploration of causal influences on mental representations of…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel
Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.« less
Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel; ...
2017-03-08
Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.« less
Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F; Perez, Danny
2017-10-21
Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.
NASA Astrophysics Data System (ADS)
Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F.; Perez, Danny
2017-10-01
Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.
Photoionization cross section by Stieltjes imaging applied to coupled cluster Lanczos pseudo-spectra
NASA Astrophysics Data System (ADS)
Cukras, Janusz; Coriani, Sonia; Decleva, Piero; Christiansen, Ove; Norman, Patrick
2013-09-01
A recently implemented asymmetric Lanczos algorithm for computing (complex) linear response functions within the coupled cluster singles (CCS), coupled cluster singles and iterative approximate doubles (CC2), and coupled cluster singles and doubles (CCSD) is coupled to a Stieltjes imaging technique in order to describe the photoionization cross section of atoms and molecules, in the spirit of a similar procedure recently proposed by Averbukh and co-workers within the Algebraic Diagrammatic Construction approach. Pilot results are reported for the atoms He, Ne, and Ar and for the molecules H2, H2O, NH3, HF, CO, and CO2.
Cukras, Janusz; Coriani, Sonia; Decleva, Piero; Christiansen, Ove; Norman, Patrick
2013-09-07
A recently implemented asymmetric Lanczos algorithm for computing (complex) linear response functions within the coupled cluster singles (CCS), coupled cluster singles and iterative approximate doubles (CC2), and coupled cluster singles and doubles (CCSD) is coupled to a Stieltjes imaging technique in order to describe the photoionization cross section of atoms and molecules, in the spirit of a similar procedure recently proposed by Averbukh and co-workers within the Algebraic Diagrammatic Construction approach. Pilot results are reported for the atoms He, Ne, and Ar and for the molecules H2, H2O, NH3, HF, CO, and CO2.
Zhang, Dake; Stecker, Pamela; Huckabee, Sloan; Miller, Rhonda
2016-09-01
Research has suggested that different strategies used when solving fraction problems are highly correlated with students' problem-solving accuracy. This study (a) utilized latent profile modeling to classify students into three different strategic developmental levels in solving fraction comparison problems and (b) accordingly provided differentiated strategic training for students starting from two different strategic developmental levels. In Study 1 we assessed 49 middle school students' performance on fraction comparison problems and categorized students into three clusters of strategic developmental clusters: a cross-multiplication cluster with the highest accuracy, a representation strategy cluster with medium accuracy, and a whole-number strategy cluster with the lowest accuracy. Based on the strategic developmental levels identified in Study 1, in Study 2 we selected three students from the whole-number strategy cluster and another three students from the representation strategy cluster and implemented a differentiated strategic training intervention within a multiple-baseline design. Results showed that both groups of students transitioned from less advanced to more advanced strategies and improved their problem-solving accuracy during the posttest, the maintenance test, and the generalization test. © Hammill Institute on Disabilities 2014.
Assigning the low lying vibronic states of CH3O and CD3O
NASA Astrophysics Data System (ADS)
Johnson, Britta A.; Sibert, Edwin L.
2017-05-01
The assignment of lines in vibrational spectra in strongly mixing systems is considered. Several low lying vibrational states of the ground electronic X˜ 2E state of the CH3O and CD3O radicals are assigned. Jahn-Teller, spin-orbit, and Fermi couplings mix the normal mode states. The mixing complicates the assignment of the infrared spectra using a zero-order normal mode representation. Alternative zero-order representations, which include specific Jahn-Teller couplings, are explored. These representations allow for definitive assignments. In many instances it is possible to plot the wavefunctions on which the assignments are based. The plots, which are shown in the adiabatic representation, allow one to visualize the effects of various higher order couplings. The plots also enable one to visualize the conical seam and its effect on the wavefunctions. The first and the second order Jahn-Teller couplings in the rocking motion dominate the spectral features in CH3O, while first order and modulated first order couplings dominate the spectral features in CD3O. The methods described here are general and can be applied to other Jahn-Teller systems.
Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering.
Peng, Xi; Yu, Zhiding; Yi, Zhang; Tang, Huajin
2017-04-01
Under the framework of graph-based learning, the key to robust subspace clustering and subspace learning is to obtain a good similarity graph that eliminates the effects of errors and retains only connections between the data points from the same subspace (i.e., intrasubspace data points). Recent works achieve good performance by modeling errors into their objective functions to remove the errors from the inputs. However, these approaches face the limitations that the structure of errors should be known prior and a complex convex problem must be solved. In this paper, we present a novel method to eliminate the effects of the errors from the projection space (representation) rather than from the input space. We first prove that l 1 -, l 2 -, l ∞ -, and nuclear-norm-based linear projection spaces share the property of intrasubspace projection dominance, i.e., the coefficients over intrasubspace data points are larger than those over intersubspace data points. Based on this property, we introduce a method to construct a sparse similarity graph, called L2-graph. The subspace clustering and subspace learning algorithms are developed upon L2-graph. We conduct comprehensive experiment on subspace learning, image clustering, and motion segmentation and consider several quantitative benchmarks classification/clustering accuracy, normalized mutual information, and running time. Results show that L2-graph outperforms many state-of-the-art methods in our experiments, including L1-graph, low rank representation (LRR), and latent LRR, least square regression, sparse subspace clustering, and locally linear representation.
Parcellation of left parietal tool representations by functional connectivity
Garcea, Frank E.; Z. Mahon, Bradford
2014-01-01
Manipulating a tool according to its function requires the integration of visual, conceptual, and motor information, a process subserved in part by left parietal cortex. How these different types of information are integrated and how their integration is reflected in neural responses in the parietal lobule remains an open question. Here, participants viewed images of tools and animals during functional magnetic resonance imaging (fMRI). K-means clustering over time series data was used to parcellate left parietal cortex into subregions based on functional connectivity to a whole brain network of regions involved in tool processing. One cluster, in the inferior parietal cortex, expressed privileged functional connectivity to the left ventral premotor cortex. A second cluster, in the vicinity of the anterior intraparietal sulcus, expressed privileged functional connectivity with the left medial fusiform gyrus. A third cluster in the superior parietal lobe expressed privileged functional connectivity with dorsal occipital cortex. Control analyses using Monte Carlo style permutation tests demonstrated that the clustering solutions were outside the range of what would be observed based on chance ‘lumpiness’ in random data, or mere anatomical proximity. Finally, hierarchical clustering analyses were used to formally relate the resulting parcellation scheme of left parietal tool representations to previous work that has parcellated the left parietal lobule on purely anatomical grounds. These findings demonstrate significant heterogeneity in the functional organization of manipulable object representations in left parietal cortex, and outline a framework that generates novel predictions about the causes of some forms of upper limb apraxia. PMID:24892224
Partially supervised speaker clustering.
Tang, Hao; Chu, Stephen Mingyu; Hasegawa-Johnson, Mark; Huang, Thomas S
2012-05-01
Content-based multimedia indexing, retrieval, and processing as well as multimedia databases demand the structuring of the media content (image, audio, video, text, etc.), one significant goal being to associate the identity of the content to the individual segments of the signals. In this paper, we specifically address the problem of speaker clustering, the task of assigning every speech utterance in an audio stream to its speaker. We offer a complete treatment to the idea of partially supervised speaker clustering, which refers to the use of our prior knowledge of speakers in general to assist the unsupervised speaker clustering process. By means of an independent training data set, we encode the prior knowledge at the various stages of the speaker clustering pipeline via 1) learning a speaker-discriminative acoustic feature transformation, 2) learning a universal speaker prior model, and 3) learning a discriminative speaker subspace, or equivalently, a speaker-discriminative distance metric. We study the directional scattering property of the Gaussian mixture model (GMM) mean supervector representation of utterances in the high-dimensional space, and advocate exploiting this property by using the cosine distance metric instead of the euclidean distance metric for speaker clustering in the GMM mean supervector space. We propose to perform discriminant analysis based on the cosine distance metric, which leads to a novel distance metric learning algorithm—linear spherical discriminant analysis (LSDA). We show that the proposed LSDA formulation can be systematically solved within the elegant graph embedding general dimensionality reduction framework. Our speaker clustering experiments on the GALE database clearly indicate that 1) our speaker clustering methods based on the GMM mean supervector representation and vector-based distance metrics outperform traditional speaker clustering methods based on the “bag of acoustic features” representation and statistical model-based distance metrics, 2) our advocated use of the cosine distance metric yields consistent increases in the speaker clustering performance as compared to the commonly used euclidean distance metric, 3) our partially supervised speaker clustering concept and strategies significantly improve the speaker clustering performance over the baselines, and 4) our proposed LSDA algorithm further leads to state-of-the-art speaker clustering performance.
High-performance parallel analysis of coupled problems for aircraft propulsion
NASA Technical Reports Server (NTRS)
Felippa, C. A.; Farhat, C.; Lanteri, S.; Gumaste, U.; Ronaghi, M.
1994-01-01
Applications are described of high-performance parallel, computation for the analysis of complete jet engines, considering its multi-discipline coupled problem. The coupled problem involves interaction of structures with gas dynamics, heat conduction and heat transfer in aircraft engines. The methodology issues addressed include: consistent discrete formulation of coupled problems with emphasis on coupling phenomena; effect of partitioning strategies, augmentation and temporal solution procedures; sensitivity of response to problem parameters; and methods for interfacing multiscale discretizations in different single fields. The computer implementation issues addressed include: parallel treatment of coupled systems; domain decomposition and mesh partitioning strategies; data representation in object-oriented form and mapping to hardware driven representation, and tradeoff studies between partitioning schemes and fully coupled treatment.
The best of both Reps—Diabatized Gaussians on adiabatic surfaces
NASA Astrophysics Data System (ADS)
Meek, Garrett A.; Levine, Benjamin G.
2016-11-01
When simulating nonadiabatic molecular dynamics, choosing an electronic representation requires consideration of well-known trade-offs. The uniqueness and spatially local couplings of the adiabatic representation come at the expense of an electronic wave function that changes discontinuously with nuclear motion and associated singularities in the nonadiabatic coupling matrix elements. The quasi-diabatic representation offers a smoothly varying wave function and finite couplings, but identification of a globally well-behaved quasi-diabatic representation is a system-specific challenge. In this work, we introduce the diabatized Gaussians on adiabatic surfaces (DGAS) approximation, a variant of the ab initio multiple spawning (AIMS) method that preserves the advantages of both electronic representations while avoiding their respective pitfalls. The DGAS wave function is expanded in a basis of vibronic functions that are continuous in both electronic and nuclear coordinates, but potentially discontinuous in time. Because the time-dependent Schrödinger equation contains only first-order derivatives with respect to time, singularities in the second-derivative nonadiabatic coupling terms (i.e., diagonal Born-Oppenheimer correction; DBOC) at conical intersections are rigorously absent, though singular time-derivative couplings remain. Interpolation of the electronic wave function allows the accurate prediction of population transfer probabilities even in the presence of the remaining singularities. We compare DGAS calculations of the dynamics of photoexcited ethene to AIMS calculations performed in the adiabatic representation, including the DBOC. The 28 fs excited state lifetime observed in DGAS simulations is considerably shorter than the 50 fs lifetime observed in the adiabatic simulations. The slower decay in the adiabatic representation is attributable to the large, repulsive DBOC in the neighborhood of conical intersections. These repulsive DBOC terms are artifacts of the discontinuities in the individual adiabatic vibronic basis functions and therefore cannot reflect the behavior of the exact molecular wave function, which must be continuous.
Pfeiffer, Florian; Rauhut, Guntram
2011-10-13
Accurate anharmonic frequencies are provided for molecules of current research, i.e., diazirines, diazomethane, the corresponding fluorinated and deuterated compounds, their dioxygen analogs, and others. Vibrational-state energies were obtained from state-specific vibrational multiconfiguration self-consistent field theory (VMCSCF) based on multilevel potential energy surfaces (PES) generated from explicitly correlated coupled cluster, CCSD(T)-F12a, and double-hybrid density functional calculations, B2PLYP. To accelerate the vibrational structure calculations, a configuration selection scheme as well as a polynomial representation of the PES have been exploited. Because experimental data are scarce for these systems, many calculated frequencies of this study are predictions and may guide experiments to come.
Celestial Cities and the Roads That Connect Them
2008-01-25
Observations from NASA Spitzer Space Telescope show that filamentary galaxies form stars at twice the rate of their densely clustered counterparts. This is a representation of galaxies in and surrounding a galaxy cluster called Abell 1763.
NASA Astrophysics Data System (ADS)
Liu, Jing-Min; Zhai, Yu; Li, Hui
2017-07-01
An effective six-dimensional ab initio potential energy surface (PES) for H2-OCS which explicitly includes the intramolecular stretch normal modes of carbonyl sulfide (OCS) is presented. The electronic structure computations are carried out using the explicitly correlated coupled cluster [CCSD(T)-F12] method with the augmented correlation-consistent aug-cc-pVTZ basis set, and the accuracy is critically tested by performing a series of benchmark calculations. Analytic four-dimensional PESs are obtained by least-squares fitting vibrationally averaged interaction energies to the Morse/long-range potential model. These fits to 13 485 points have a root-mean-square deviation (RMSD) of 0.16 cm-1. The combined radial discrete variable representation/angular finite basis representation method and the Lanczos algorithm were employed to evaluate the rovibrational energy levels for five isotopic species of the OCS-hydrogen complexes. The predicted transition frequencies and intensities based on the resulting vibrationally averaged PESs are in good agreement with the available experimental values, whose RMSDs are smaller than 0.004 cm-1 for five different species of OCS-hydrogen complexes. The calculated infrared band origin shifts for all five species of OCS-hydrogen complexes are only 0.03 cm-1 smaller than the corresponding experimental values. These validate the high quality of our PESs which can be used for modeling OCS doped in hydrogen clusters to further study quantum solution and microscopic superfluidity. In addition, the analytic coordinate transformation functions between isotopologues are also derived due to the center of mass shifting of different isotope substitutes.
Yang, Yang; Saleemi, Imran; Shah, Mubarak
2013-07-01
This paper proposes a novel representation of articulated human actions and gestures and facial expressions. The main goals of the proposed approach are: 1) to enable recognition using very few examples, i.e., one or k-shot learning, and 2) meaningful organization of unlabeled datasets by unsupervised clustering. Our proposed representation is obtained by automatically discovering high-level subactions or motion primitives, by hierarchical clustering of observed optical flow in four-dimensional, spatial, and motion flow space. The completely unsupervised proposed method, in contrast to state-of-the-art representations like bag of video words, provides a meaningful representation conducive to visual interpretation and textual labeling. Each primitive action depicts an atomic subaction, like directional motion of limb or torso, and is represented by a mixture of four-dimensional Gaussian distributions. For one--shot and k-shot learning, the sequence of primitive labels discovered in a test video are labeled using KL divergence, and can then be represented as a string and matched against similar strings of training videos. The same sequence can also be collapsed into a histogram of primitives or be used to learn a Hidden Markov model to represent classes. We have performed extensive experiments on recognition by one and k-shot learning as well as unsupervised action clustering on six human actions and gesture datasets, a composite dataset, and a database of facial expressions. These experiments confirm the validity and discriminative nature of the proposed representation.
Delay-induced cluster patterns in coupled Cayley tree networks
NASA Astrophysics Data System (ADS)
Singh, A.; Jalan, S.
2013-07-01
We study effects of delay in diffusively coupled logistic maps on the Cayley tree networks. We find that smaller coupling values exhibit sensitiveness to value of delay, and lead to different cluster patterns of self-organized and driven types. Whereas larger coupling strengths exhibit robustness against change in delay values, and lead to stable driven clusters comprising nodes from last generation of the Cayley tree. Furthermore, introduction of delay exhibits suppression as well as enhancement of synchronization depending upon coupling strength values. To the end we discuss the importance of results to understand conflicts and cooperations observed in family business.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nanda, Kaushik D.; Krylov, Anna I.
The equation-of-motion coupled-cluster (EOM-CC) methods provide a robust description of electronically excited states and their properties. Here, we present a formalism for two-photon absorption (2PA) cross sections for the equation-of-motion for excitation energies CC with single and double substitutions (EOM-CC for electronically excited states with single and double substitutions) wave functions. Rather than the response theory formulation, we employ the expectation-value approach which is commonly used within EOM-CC, configuration interaction, and algebraic diagrammatic construction frameworks. In addition to canonical implementation, we also exploit resolution-of-the-identity (RI) and Cholesky decomposition (CD) for the electron-repulsion integrals to reduce memory requirements and to increasemore » parallel efficiency. The new methods are benchmarked against the CCSD and CC3 response theories for several small molecules. We found that the expectation-value 2PA cross sections are within 5% from the quadratic response CCSD values. The RI and CD approximations lead to small errors relative to the canonical implementation (less than 4%) while affording computational savings. RI/CD successfully address the well-known issue of large basis set requirements for 2PA cross sections calculations. The capabilities of the new code are illustrated by calculations of the 2PA cross sections for model chromophores of the photoactive yellow and green fluorescent proteins.« less
Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction
ERIC Educational Resources Information Center
Trivedi, Shubhendu; Pardos, Zachary A.; Sarkozy, Gabor N.; Heffernan, Neil T.
2012-01-01
Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, Curtis L.; Prescott, Steven; Coleman, Justin
This report describes the current progress and status related to the Industry Application #2 focusing on External Hazards. For this industry application within the Light Water Reactor Sustainability (LWRS) Program Risk-Informed Safety Margin Characterization (RISMC) R&D Pathway, we will create the Risk-Informed Margin Management (RIMM) approach to represent meaningful (i.e., realistic facility representation) event scenarios and consequences by using an advanced 3D facility representation that will evaluate external hazards such as flooding and earthquakes in order to identify, model and analyze the appropriate physics that needs to be included to determine plant vulnerabilities related to external events; manage the communicationmore » and interactions between different physics modeling and analysis technologies; and develop the computational infrastructure through tools related to plant representation, scenario depiction, and physics prediction. One of the unique aspects of the RISMC approach is how it couples probabilistic approaches (the scenario) with mechanistic phenomena representation (the physics) through simulation. This simulation-based modeling allows decision makers to focus on a variety of safety, performance, or economic metrics. In this report, we describe the evaluation of various physics toolkits related to flooding representation. Ultimately, we will be coupling the flooding representation with other events such as earthquakes in order to provide coupled physics analysis for scenarios where interactions exist.« less
Antiferromagnetic exchange coupling measurements on single Co clusters
NASA Astrophysics Data System (ADS)
Wernsdorfer, W.; Leroy, D.; Portemont, C.; Brenac, A.; Morel, R.; Notin, L.; Mailly, D.
2009-03-01
We report on single-cluster measurements of the angular dependence of the low-temperature ferromagnetic core magnetization switching field in exchange-coupled Co/CoO core-shell clusters (4 nm) using a micro-bridge DC superconducting quantum interference device (μ-SQUID). It is observed that the coupling with the antiferromagnetic shell induces modification in the switching field for clusters with intrinsic uniaxial anisotropy depending on the direction of the magnetic field applied during the cooling. Using a modified Stoner-Wohlfarth model, it is shown that the core interacts with two weakly coupled and asymmetrical antiferromagnetic sublattices. Ref.: C. Portemont, R. Morel, W. Wernsdorfer, D. Mailly, A. Brenac, and L. Notin, Phys. Rev. B 78, 144415 (2008)
Sadeghi, Zahra
2016-09-01
In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.
Nepusz, Tamás; Sasidharan, Rajkumar; Paccanaro, Alberto
2010-03-09
An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. SCPS (Spectral Clustering of Protein Sequences) is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences) and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences). Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with external tools such as BLAST and Cytoscape, and it can produce publication-quality graphical representations of the clusters obtained, thus constituting a comprehensive and effective tool for practical research in computational biology. Source code and precompiled executables for Windows, Linux and Mac OS X are freely available at http://www.paccanarolab.org/software/scps.
Werbart, Andrzej; Brusell, Lars; Iggedal, Rebecka; Lavfors, Kristin; Widholm, Alexander
2016-10-01
Changes in dynamic psychological structures are often a treatment goal in psychotherapy. The present study aimed at creating a typology of self-representations among young women and men in psychoanalytic psychotherapy, to study longitudinal changes in self-representations, and to compare self-representations in the clinical sample with those of a nonclinical group. Twenty-five women and sixteen men were interviewed according to Blatt's Object Relations Inventory pretreatment, at termination, and at a 1.5-year follow-up. In the comparison group, eleven women and nine men were interviewed at baseline, 1.5 years, and three years later. Typologies of the 123 self-descriptions in the clinical group and 60 in the nonclinical group were constructed by means of ideal-type analysis for men and women separately. Clusters of self-representations could be depicted on a two-dimensional matrix with the axes Relatedness-Self-definition and Integration-Nonintegration. In most cases, the self-descriptions changed over time in terms of belonging to different ideal-type clusters. In the clinical group, there was a movement toward increased integration in self-representations, but above all toward a better balance between relatedness and self-definition. The changes continued after termination, paralleled by reduced symptoms, improved functioning, and higher developmental levels of representations. No corresponding tendency could be observed in the nonclinical group.
Dynamics of a network of phase oscillators with plastic couplings
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nekorkin, V. I.; Kasatkin, D. V.; Moscow Institute of Physics and Technology
The processes of synchronization and phase cluster formation are investigated in a complex network of dynamically coupled phase oscillators. Coupling weights evolve dynamically depending on the phase relations between the oscillators. It is shown that the network exhibits several types of behavior: the globally synchronized state, two-cluster and multi-cluster states, different synchronous states with a fixed phase relationship between the oscillators and chaotic desynchronized state.
Mapping the cortical representation of speech sounds in a syllable repetition task.
Markiewicz, Christopher J; Bohland, Jason W
2016-11-01
Speech repetition relies on a series of distributed cortical representations and functional pathways. A speaker must map auditory representations of incoming sounds onto learned speech items, maintain an accurate representation of those items in short-term memory, interface that representation with the motor output system, and fluently articulate the target sequence. A "dorsal stream" consisting of posterior temporal, inferior parietal and premotor regions is thought to mediate auditory-motor representations and transformations, but the nature and activation of these representations for different portions of speech repetition tasks remains unclear. Here we mapped the correlates of phonetic and/or phonological information related to the specific phonemes and syllables that were heard, remembered, and produced using a series of cortical searchlight multi-voxel pattern analyses trained on estimates of BOLD responses from individual trials. Based on responses linked to input events (auditory syllable presentation), predictive vowel-level information was found in the left inferior frontal sulcus, while syllable prediction revealed significant clusters in the left ventral premotor cortex and central sulcus and the left mid superior temporal sulcus. Responses linked to output events (the GO signal cueing overt production) revealed strong clusters of vowel-related information bilaterally in the mid to posterior superior temporal sulcus. For the prediction of onset and coda consonants, input-linked responses yielded distributed clusters in the superior temporal cortices, which were further informative for classifiers trained on output-linked responses. Output-linked responses in the Rolandic cortex made strong predictions for the syllables and consonants produced, but their predictive power was reduced for vowels. The results of this study provide a systematic survey of how cortical response patterns covary with the identity of speech sounds, which will help to constrain and guide theoretical models of speech perception, speech production, and phonological working memory. Copyright © 2016 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Byrd, Jason N., E-mail: byrd.jason@ensco.com; ENSCO, Inc., 4849 North Wickham Road, Melbourne, Florida 32940; Lutz, Jesse J., E-mail: jesse.lutz.ctr@afit.edu
The accurate determination of the preferred Si{sub 12}C{sub 12} isomer is important to guide experimental efforts directed towards synthesizing SiC nano-wires and related polymer structures which are anticipated to be highly efficient exciton materials for the opto-electronic devices. In order to definitively identify preferred isomeric structures for silicon carbon nano-clusters, highly accurate geometries, energies, and harmonic zero point energies have been computed using coupled-cluster theory with systematic extrapolation to the complete basis limit for set of silicon carbon clusters ranging in size from SiC{sub 3} to Si{sub 12}C{sub 12}. It is found that post-MBPT(2) correlation energy plays a significant rolemore » in obtaining converged relative isomer energies, suggesting that predictions using low rung density functional methods will not have adequate accuracy. Utilizing the best composite coupled-cluster energy that is still computationally feasible, entailing a 3-4 SCF and coupled-cluster theory with singles and doubles extrapolation with triple-ζ (T) correlation, the closo Si{sub 12}C{sub 12} isomer is identified to be the preferred isomer in the support of previous calculations [X. F. Duan and L. W. Burggraf, J. Chem. Phys. 142, 034303 (2015)]. Additionally we have investigated more pragmatic approaches to obtaining accurate silicon carbide isomer energies, including the use of frozen natural orbital coupled-cluster theory and several rungs of standard and double-hybrid density functional theory. Frozen natural orbitals as a way to compute post-MBPT(2) correlation energy are found to be an excellent balance between efficiency and accuracy.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moody, Daniela Irina
An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detectmore » geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.« less
Synaptic clustering within dendrites: an emerging theory of memory formation
Kastellakis, George; Cai, Denise J.; Mednick, Sara C.; Silva, Alcino J.; Poirazi, Panayiota
2015-01-01
It is generally accepted that complex memories are stored in distributed representations throughout the brain, however the mechanisms underlying these representations are not understood. Here, we review recent findings regarding the subcellular mechanisms implicated in memory formation, which provide evidence for a dendrite-centered theory of memory. Plasticity-related phenomena which affect synaptic properties, such as synaptic tagging and capture, synaptic clustering, branch strength potentiation and spinogenesis provide the foundation for a model of memory storage that relies heavily on processes operating at the dendrite level. The emerging picture suggests that clusters of functionally related synapses may serve as key computational and memory storage units in the brain. We discuss both experimental evidence and theoretical models that support this hypothesis and explore its advantages for neuronal function. PMID:25576663
Reweighted mass center based object-oriented sparse subspace clustering for hyperspectral images
NASA Astrophysics Data System (ADS)
Zhai, Han; Zhang, Hongyan; Zhang, Liangpei; Li, Pingxiang
2016-10-01
Considering the inevitable obstacles faced by the pixel-based clustering methods, such as salt-and-pepper noise, high computational complexity, and the lack of spatial information, a reweighted mass center based object-oriented sparse subspace clustering (RMC-OOSSC) algorithm for hyperspectral images (HSIs) is proposed. First, the mean-shift segmentation method is utilized to oversegment the HSI to obtain meaningful objects. Second, a distance reweighted mass center learning model is presented to extract the representative and discriminative features for each object. Third, assuming that all the objects are sampled from a union of subspaces, it is natural to apply the SSC algorithm to the HSI. Faced with the high correlation among the hyperspectral objects, a weighting scheme is adopted to ensure that the highly correlated objects are preferred in the procedure of sparse representation, to reduce the representation errors. Two widely used hyperspectral datasets were utilized to test the performance of the proposed RMC-OOSSC algorithm, obtaining high clustering accuracies (overall accuracy) of 71.98% and 89.57%, respectively. The experimental results show that the proposed method clearly improves the clustering performance with respect to the other state-of-the-art clustering methods, and it significantly reduces the computational time.
Using background knowledge for picture organization and retrieval
NASA Astrophysics Data System (ADS)
Quintana, Yuri
1997-01-01
A picture knowledge base management system is described that is used to represent, organize and retrieve pictures from a frame knowledge base. Experiments with human test subjects were conducted to obtain further descriptions of pictures from news magazines. These descriptions were used to represent the semantic content of pictures in frame representations. A conceptual clustering algorithm is described which organizes pictures not only on the observable features, but also on implicit properties derived from the frame representations. The algorithm uses inheritance reasoning to take into account background knowledge in the clustering. The algorithm creates clusters of pictures using a group similarity function that is based on the gestalt theory of picture perception. For each cluster created, a frame is generated which describes the semantic content of pictures in the cluster. Clustering and retrieval experiments were conducted with and without background knowledge. The paper shows how the use of background knowledge and semantic similarity heuristics improves the speed, precision, and recall of queries processed. The paper concludes with a discussion of how natural language processing of can be used to assist in the development of knowledge bases and the processing of user queries.
Smiga, Szymon; Fabiano, Eduardo
2017-11-15
We have developed a simplified coupled cluster (SCC) methodology, using the basic idea of scaled MP2 methods. The scheme has been applied to the coupled cluster double equations and implemented in three different non-iterative variants. This new method (especially the SCCD[3] variant, which utilizes a spin-resolved formalism) has been found to be very efficient and to yield an accurate approximation of the reference CCD results for both total and interaction energies of different atoms and molecules. Furthermore, we demonstrate that the equations determining the scaling coefficients for the SCCD[3] approach can generate non-empirical SCS-MP2 scaling coefficients which are in good agreement with previous theoretical investigations.
Boolean network representation of contagion dynamics during a financial crisis
NASA Astrophysics Data System (ADS)
Caetano, Marco Antonio Leonel; Yoneyama, Takashi
2015-01-01
This work presents a network model for representation of the evolution of certain patterns of economic behavior. More specifically, after representing the agents as points in a space in which each dimension associated to a relevant economic variable, their relative "motions" that can be either stationary or discordant, are coded into a boolean network. Patterns with stationary averages indicate the maintenance of status quo, whereas discordant patterns represent aggregation of new agent into the cluster or departure from the former policies. The changing patterns can be embedded into a network representation, particularly using the concept of autocatalytic boolean networks. As a case study, the economic tendencies of the BRIC countries + Argentina were studied. Although Argentina is not included in the cluster formed by BRIC countries, it tends to follow the BRIC members because of strong commercial ties.
Medical Named Entity Recognition for Indonesian Language Using Word Representations
NASA Astrophysics Data System (ADS)
Rahman, Arief
2018-03-01
Nowadays, Named Entity Recognition (NER) system is used in medical texts to obtain important medical information, like diseases, symptoms, and drugs. While most NER systems are applied to formal medical texts, informal ones like those from social media (also called semi-formal texts) are starting to get recognition as a gold mine for medical information. We propose a theoretical Named Entity Recognition (NER) model for semi-formal medical texts in our medical knowledge management system by comparing two kinds of word representations: cluster-based word representation and distributed representation.
Karademas, Evangelos C; Giannousi, Zoe
2013-01-01
The aim of this study was to examine the relation between illness representations of personal and treatment control and psychological symptoms (i.e. symptoms of anxiety and depression) in 72 married couples dealing with a recently diagnosed cancer. Patients were first-diagnosed with early stage (45.83%) or metastatic cancer (54.17%). Dyadic responses were examined with the actor-partner interdependence model. Also, in order to examine whether patients and spouses' representations of control moderate the relation of their partners' corresponding representations to psychological symptoms, we used the relevant bootstrapping framework developed by Hayes and Matthes [(2009). Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. Behavior Research Methods, 41, 924-936]. Patients' symptoms of anxiety and depression were associated with both partners' representations of control. Chi-square difference tests indicated that actor and partner effects were equal. Spouses' symptoms of anxiety and depression were related only to their own representations. Moreover, spouses' representations of personal control moderated the relation of patients' corresponding representations to depressive symptoms, whereas patients' representations of treatment control moderated the relation of their spouses' corresponding representations to both anxiety and depression. Findings suggest that both partners' representations of control are important for adaptation to illness. Moreover, they indicate that dyadic regulation may be equally important to self-regulation as far as adaptation to illness is concerned.
The Graphic Representation of Structure in Similarity/Dissimilarity Matrices: Alternative Methods.
ERIC Educational Resources Information Center
Rudnitsky, Alan N.
Three approaches to the graphic representation of similarity and dissimilarity matrices are compared and contrasted. Specifically, Kruskal's multidimensional scaling, Johnson's hierarchical clustering, and Waern's graphing techniques are employed to depict, in two dimensions, data representing the structure of a set of botanical concepts. Each of…
Effects of cluster-shell competition and BCS-like pairing in 12C
NASA Astrophysics Data System (ADS)
Matsuno, H.; Itagaki, N.
2017-12-01
The antisymmetrized quasi-cluster model (AQCM) was proposed to describe α-cluster and jj-coupling shell models on the same footing. In this model, the cluster-shell transition is characterized by two parameters, R representing the distance between α clusters and Λ describing the breaking of α clusters, and the contribution of the spin-orbit interaction, very important in the jj-coupling shell model, can be taken into account starting with the α-cluster model wave function. Not only the closure configurations of the major shells but also the subclosure configurations of the jj-coupling shell model can be described starting with the α-cluster model wave functions; however, the particle-hole excitations of single particles have not been fully established yet. In this study we show that the framework of AQCM can be extended even to the states with the character of single-particle excitations. For ^{12}C, two-particle-two-hole (2p2h) excitations from the subclosure configuration of 0p_{3/2} corresponding to a BCS-like pairing are described, and these shell model states are coupled with the three α-cluster model wave functions. The correlation energy from the optimal configuration can be estimated not only in the cluster part but also in the shell model part. We try to pave the way to establish a generalized description of the nuclear structure.
On the Coupling Time of the Heat-Bath Process for the Fortuin-Kasteleyn Random-Cluster Model
NASA Astrophysics Data System (ADS)
Collevecchio, Andrea; Elçi, Eren Metin; Garoni, Timothy M.; Weigel, Martin
2018-01-01
We consider the coupling from the past implementation of the random-cluster heat-bath process, and study its random running time, or coupling time. We focus on hypercubic lattices embedded on tori, in dimensions one to three, with cluster fugacity at least one. We make a number of conjectures regarding the asymptotic behaviour of the coupling time, motivated by rigorous results in one dimension and Monte Carlo simulations in dimensions two and three. Amongst our findings, we observe that, for generic parameter values, the distribution of the appropriately standardized coupling time converges to a Gumbel distribution, and that the standard deviation of the coupling time is asymptotic to an explicit universal constant multiple of the relaxation time. Perhaps surprisingly, we observe these results to hold both off criticality, where the coupling time closely mimics the coupon collector's problem, and also at the critical point, provided the cluster fugacity is below the value at which the transition becomes discontinuous. Finally, we consider analogous questions for the single-spin Ising heat-bath process.
NASA Astrophysics Data System (ADS)
Black, Joshua A.; Knowles, Peter J.
2018-06-01
The performance of quasi-variational coupled-cluster (QV) theory applied to the calculation of activation and reaction energies has been investigated. A statistical analysis of results obtained for six different sets of reactions has been carried out, and the results have been compared to those from standard single-reference methods. In general, the QV methods lead to increased activation energies and larger absolute reaction energies compared to those obtained with traditional coupled-cluster theory.
Coupled-cluster computations of atomic nuclei
NASA Astrophysics Data System (ADS)
Hagen, G.; Papenbrock, T.; Hjorth-Jensen, M.; Dean, D. J.
2014-09-01
In the past decade, coupled-cluster theory has seen a renaissance in nuclear physics, with computations of neutron-rich and medium-mass nuclei. The method is efficient for nuclei with product-state references, and it describes many aspects of weakly bound and unbound nuclei. This report reviews the technical and conceptual developments of this method in nuclear physics, and the results of coupled-cluster calculations for nucleonic matter, and for exotic isotopes of helium, oxygen, calcium, and some of their neighbors.
Cabana, Alvaro; Mizraji, Eduardo; Pomi, Andrés; Valle-Lisboa, Juan Carlos
2008-04-01
Graph-theoretical methods have recently been used to analyze certain properties of natural and social networks. In this work, we have investigated the early stages in the growth of a Uruguayan academic network, the Biology Area of the Programme for the Development of Basic Science (PEDECIBA). This transparent social network is a territory for the exploration of the reliability of clustering methods that can potentially be used when we are confronted with opaque natural systems that provide us with a limited spectrum of observables (happens in research on the relations between brain, thought and language). From our social net, we constructed two different graph representations based on the relationships among researchers revealed by their co-participation in Master's thesis committees. We studied these networks at different times and found that they achieve connectedness early in their evolution and exhibit the small-world property (i.e. high clustering with short path lengths). The data seem compatible with power law distributions of connectivity, clustering coefficients and betweenness centrality. Evidence of preferential attachment of new nodes and of new links between old nodes was also found in both representations. These results suggest that there are topological properties observed throughout the growth of the network that do not depend on the representations we have chosen but reflect intrinsic properties of the academic collective under study. Researchers in PEDECIBA are classified according to their specialties. We analysed the community structure detected by a standard algorithm in both representations. We found that much of the pre-specified structure is recovered and part of the mismatches can be attributed to convergent interests between scientists from different sub-disciplines. This result shows the potentiality of some clustering methods for the analysis of partially known natural systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wahlen-Strothman, J. M.; Henderson, T. H.; Hermes, M. R.
Coupled cluster and symmetry projected Hartree-Fock are two central paradigms in electronic structure theory. However, they are very different. Single reference coupled cluster is highly successful for treating weakly correlated systems, but fails under strong correlation unless one sacrifices good quantum numbers and works with broken-symmetry wave functions, which is unphysical for finite systems. Symmetry projection is effective for the treatment of strong correlation at the mean-field level through multireference non-orthogonal configuration interaction wavefunctions, but unlike coupled cluster, it is neither size extensive nor ideal for treating dynamic correlation. We here examine different scenarios for merging these two dissimilar theories.more » We carry out this exercise over the integrable Lipkin model Hamiltonian, which despite its simplicity, encompasses non-trivial physics for degenerate systems and can be solved via diagonalization for a very large number of particles. We show how symmetry projection and coupled cluster doubles individually fail in different correlation limits, whereas models that merge these two theories are highly successful over the entire phase diagram. Despite the simplicity of the Lipkin Hamiltonian, the lessons learned in this work will be useful for building an ab initio symmetry projected coupled cluster theory that we expect to be accurate in the weakly and strongly correlated limits, as well as the recoupling regime.« less
NASA Astrophysics Data System (ADS)
Hermes, Matthew R.; Dukelsky, Jorge; Scuseria, Gustavo E.
2017-06-01
The failures of single-reference coupled-cluster theory for strongly correlated many-body systems is flagged at the mean-field level by the spontaneous breaking of one or more physical symmetries of the Hamiltonian. Restoring the symmetry of the mean-field determinant by projection reveals that coupled-cluster theory fails because it factorizes high-order excitation amplitudes incorrectly. However, symmetry-projected mean-field wave functions do not account sufficiently for dynamic (or weak) correlation. Here we pursue a merger of symmetry projection and coupled-cluster theory, following previous work along these lines that utilized the simple Lipkin model system as a test bed [J. Chem. Phys. 146, 054110 (2017), 10.1063/1.4974989]. We generalize the concept of a symmetry-projected mean-field wave function to the concept of a symmetry projected state, in which the factorization of high-order excitation amplitudes in terms of low-order ones is guided by symmetry projection and is not exponential, and combine them with coupled-cluster theory in order to model the ground state of the Agassi Hamiltonian. This model has two separate channels of correlation and two separate physical symmetries which are broken under strong correlation. We show how the combination of symmetry collective states and coupled-cluster theory is effective in obtaining correlation energies and order parameters of the Agassi model throughout its phase diagram.
A theoretical and experimental benchmark study of core-excited states in nitrogen
NASA Astrophysics Data System (ADS)
Myhre, Rolf H.; Wolf, Thomas J. A.; Cheng, Lan; Nandi, Saikat; Coriani, Sonia; Gühr, Markus; Koch, Henrik
2018-02-01
The high resolution near edge X-ray absorption fine structure spectrum of nitrogen displays the vibrational structure of the core-excited states. This makes nitrogen well suited for assessing the accuracy of different electronic structure methods for core excitations. We report high resolution experimental measurements performed at the SOLEIL synchrotron facility. These are compared with theoretical spectra calculated using coupled cluster theory and algebraic diagrammatic construction theory. The coupled cluster singles and doubles with perturbative triples model known as CC3 is shown to accurately reproduce the experimental excitation energies as well as the spacing of the vibrational transitions. The computational results are also shown to be systematically improved within the coupled cluster hierarchy, with the coupled cluster singles, doubles, triples, and quadruples method faithfully reproducing the experimental vibrational structure.
Hanrath, Michael; Engels-Putzka, Anna
2010-08-14
In this paper, we present an efficient implementation of general tensor contractions, which is part of a new coupled-cluster program. The tensor contractions, used to evaluate the residuals in each coupled-cluster iteration are particularly important for the performance of the program. We developed a generic procedure, which carries out contractions of two tensors irrespective of their explicit structure. It can handle coupled-cluster-type expressions of arbitrary excitation level. To make the contraction efficient without loosing flexibility, we use a three-step procedure. First, the data contained in the tensors are rearranged into matrices, then a matrix-matrix multiplication is performed, and finally the result is backtransformed to a tensor. The current implementation is significantly more efficient than previous ones capable of treating arbitrary high excitations.
Le Breton, Nolwenn; Wright, John J; Jones, Andrew J Y; Salvadori, Enrico; Bridges, Hannah R; Hirst, Judy; Roessler, Maxie M
2017-11-15
Energy-transducing respiratory complex I (NADH:ubiquinone oxidoreductase) is one of the largest and most complicated enzymes in mammalian cells. Here, we used hyperfine electron paramagnetic resonance (EPR) spectroscopic methods, combined with site-directed mutagenesis, to determine the mechanism of a single proton-coupled electron transfer reaction at one of eight iron-sulfur clusters in complex I, [4Fe-4S] cluster N2. N2 is the terminal cluster of the enzyme's intramolecular electron-transfer chain and the electron donor to ubiquinone. Because of its position and pH-dependent reduction potential, N2 has long been considered a candidate for the elusive "energy-coupling" site in complex I at which energy generated by the redox reaction is used to initiate proton translocation. Here, we used hyperfine sublevel correlation (HYSCORE) spectroscopy, including relaxation-filtered hyperfine and single-matched resonance transfer (SMART) HYSCORE, to detect two weakly coupled exchangeable protons near N2. We assign the larger coupling with A( 1 H) = [-3.0, -3.0, 8.7] MHz to the exchangeable proton of a conserved histidine and conclude that the histidine is hydrogen-bonded to N2, tuning its reduction potential. The histidine protonation state responds to the cluster oxidation state, but the two are not coupled sufficiently strongly to catalyze a stoichiometric and efficient energy transduction reaction. We thus exclude cluster N2, despite its proton-coupled electron transfer chemistry, as the energy-coupling site in complex I. Our work demonstrates the capability of pulse EPR methods for providing detailed information on the properties of individual protons in even the most challenging of energy-converting enzymes.
Cluster-modified function projective synchronisation of complex networks with asymmetric coupling
NASA Astrophysics Data System (ADS)
Wang, Shuguo
2018-02-01
This paper investigates the cluster-modified function projective synchronisation (CMFPS) of a generalised linearly coupled network with asymmetric coupling and nonidentical dynamical nodes. A novel synchronisation scheme is proposed to achieve CMFPS in community networks. We use adaptive control method to derive CMFPS criteria based on Lyapunov stability theory. Each cluster of networks is synchronised with target system by state transformation with scaling function matrix. Numerical simulation results are presented finally to illustrate the effectiveness of this method.
Myers, C E; Gluck, M A
1996-08-01
A previous model of hippocampal region function in classical conditioning is generalized to H. Eichenbaum, A. Fagan, P. Mathews, and N.J. Cohen's (1989) and H. Eichenbaum, A. Fagan, and N.J. Cohen's (1989) simultaneous odor discrimination studies in rats. The model assumes that the hippocampal region forms new stimulus representations that compress redundant information while differentiating predictie information; the piriform (olfactory) cortex meanwhile clusters similar and co-occurring odors. Hippocampal damage interrupts the ability to differentiate odor representations, while leaving piriform-mediated odor clustering unchecked. The result is a net tendency to overcompress in the lesioned model. Behavior in the model is very similar to that of the rats, including lesion deficits, facilitation of successively learned tasks, and transfer performance. The computational mechanisms underlying model performance are consistent with the qualitative interpretations suggested by Eichen baum et al. to explain their empirical data.
Segmentation of High Angular Resolution Diffusion MRI using Sparse Riemannian Manifold Clustering
Wright, Margaret J.; Thompson, Paul M.; Vidal, René
2015-01-01
We address the problem of segmenting high angular resolution diffusion imaging (HARDI) data into multiple regions (or fiber tracts) with distinct diffusion properties. We use the orientation distribution function (ODF) to represent HARDI data and cast the problem as a clustering problem in the space of ODFs. Our approach integrates tools from sparse representation theory and Riemannian geometry into a graph theoretic segmentation framework. By exploiting the Riemannian properties of the space of ODFs, we learn a sparse representation for each ODF and infer the segmentation by applying spectral clustering to a similarity matrix built from these representations. In cases where regions with similar (resp. distinct) diffusion properties belong to different (resp. same) fiber tracts, we obtain the segmentation by incorporating spatial and user-specified pairwise relationships into the formulation. Experiments on synthetic data evaluate the sensitivity of our method to image noise and the presence of complex fiber configurations, and show its superior performance compared to alternative segmentation methods. Experiments on phantom and real data demonstrate the accuracy of the proposed method in segmenting simulated fibers, as well as white matter fiber tracts of clinical importance in the human brain. PMID:24108748
Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation
Khaligh-Razavi, Seyed-Mahdi; Kriegeskorte, Nikolaus
2014-01-01
Inferior temporal (IT) cortex in human and nonhuman primates serves visual object recognition. Computational object-vision models, although continually improving, do not yet reach human performance. It is unclear to what extent the internal representations of computational models can explain the IT representation. Here we investigate a wide range of computational model representations (37 in total), testing their categorization performance and their ability to account for the IT representational geometry. The models include well-known neuroscientific object-recognition models (e.g. HMAX, VisNet) along with several models from computer vision (e.g. SIFT, GIST, self-similarity features, and a deep convolutional neural network). We compared the representational dissimilarity matrices (RDMs) of the model representations with the RDMs obtained from human IT (measured with fMRI) and monkey IT (measured with cell recording) for the same set of stimuli (not used in training the models). Better performing models were more similar to IT in that they showed greater clustering of representational patterns by category. In addition, better performing models also more strongly resembled IT in terms of their within-category representational dissimilarities. Representational geometries were significantly correlated between IT and many of the models. However, the categorical clustering observed in IT was largely unexplained by the unsupervised models. The deep convolutional network, which was trained by supervision with over a million category-labeled images, reached the highest categorization performance and also best explained IT, although it did not fully explain the IT data. Combining the features of this model with appropriate weights and adding linear combinations that maximize the margin between animate and inanimate objects and between faces and other objects yielded a representation that fully explained our IT data. Overall, our results suggest that explaining IT requires computational features trained through supervised learning to emphasize the behaviorally important categorical divisions prominently reflected in IT. PMID:25375136
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Xiaolei, E-mail: virtualzx@gmail.com; Malbon, Christopher L., E-mail: clmalbon@gmail.com; Yarkony, David R., E-mail: yarkony@jhu.edu
2016-03-28
In a recent work we constructed a quasi-diabatic representation, H{sup d}, of the 1, 2, 3{sup 1}A adiabatic states of phenol from high level multireference single and double excitation configuration interaction electronic structure data, energies, energy gradients, and derivative couplings. That H{sup d} accurately describes surface minima, saddle points, and also regions of strong nonadiabatic interactions, reproducing the locus of conical intersection seams and the coordinate dependence of the derivative couplings. The present work determines the accuracy of H{sup d} for describing phenol photodissociation. Additionally, we demonstrate that a modest energetic shift of two diabats yields a quantifiably more accuratemore » H{sup d} compared with experimental energetics. The analysis shows that in favorable circumstances it is possible to use single point energies obtained from the most reliable electronic structure methods available, including methods for which the energy gradients and derivative couplings are not available, to improve the quality of a global representation of several coupled potential energy surfaces. Our data suggest an alternative interpretation of kinetic energy release measurements near λ{sub phot} ∼ 248 nm.« less
NASA Astrophysics Data System (ADS)
Pašteka, L. F.; Mawhorter, R. J.; Schwerdtfeger, P.
2016-04-01
We report calculations on the q(Yb) electric field gradient (EFG) for the X2Σ+ and A2Π1/2 electronic states of the ytterbium monofluoride (YbF) molecule at the molecular mean-field Dirac-Coulomb-Gaunt as well as scalar-relativistic coupled-cluster levels of theory using large uncontracted basis sets. Vibrational contributions are included in the final results. Our estimated nuclear quadrupole coupling constants of -3386(78) MHz and -2083(153) MHz for the X2Σ+ and A2Π1/2 states of 173YbF are in stark contrast to the only available experimental results (-2050(170) MHz and -1090(160) MHz) respectively, where the only similarity is the difference between the two values. Perturbative triple contributions in the coupled cluster treatment are significant and point towards the necessity to go to higher order in the coupled-cluster treatment in future calculations. We also present density functional calculations which show rather large variations for the Yb EFG with different functionals used; the best result was obtained using the CAM-B3LYP* functional.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Datta, Dipayan, E-mail: datta.dipayan@gmail.com; Gauss, Jürgen, E-mail: gauss@uni-mainz.de
We report analytical calculations of isotropic hyperfine-coupling constants in radicals using a spin-adapted open-shell coupled-cluster theory, namely, the unitary group based combinatoric open-shell coupled-cluster (COSCC) approach within the singles and doubles approximation. A scheme for the evaluation of the one-particle spin-density matrix required in these calculations is outlined within the spin-free formulation of the COSCC approach. In this scheme, the one-particle spin-density matrix for an open-shell state with spin S and M{sub S} = + S is expressed in terms of the one- and two-particle spin-free (charge) density matrices obtained from the Lagrangian formulation that is used for calculating themore » analytic first derivatives of the energy. Benchmark calculations are presented for NO, NCO, CH{sub 2}CN, and two conjugated π-radicals, viz., allyl and 1-pyrrolyl in order to demonstrate the performance of the proposed scheme.« less
A theoretical and experimental benchmark study of core-excited states in nitrogen
Myhre, Rolf H.; Wolf, Thomas J. A.; Cheng, Lan; ...
2018-02-14
The high resolution near edge X-ray absorption fine structure spectrum of nitrogen displays the vibrational structure of the core-excited states. This makes nitrogen well suited for assessing the accuracy of different electronic structure methods for core excitations. We report high resolution experimental measurements performed at the SOLEIL synchrotron facility. These are compared with theoretical spectra calculated using coupled cluster theory and algebraic diagrammatic construction theory. The coupled cluster singles and doubles with perturbative triples model known as CC3 is shown to accurately reproduce the experimental excitation energies as well as the spacing of the vibrational transitions. In conclusion, the computationalmore » results are also shown to be systematically improved within the coupled cluster hierarchy, with the coupled cluster singles, doubles, triples, and quadruples method faithfully reproducing the experimental vibrational structure.« less
A theoretical and experimental benchmark study of core-excited states in nitrogen
DOE Office of Scientific and Technical Information (OSTI.GOV)
Myhre, Rolf H.; Wolf, Thomas J. A.; Cheng, Lan
The high resolution near edge X-ray absorption fine structure spectrum of nitrogen displays the vibrational structure of the core-excited states. This makes nitrogen well suited for assessing the accuracy of different electronic structure methods for core excitations. We report high resolution experimental measurements performed at the SOLEIL synchrotron facility. These are compared with theoretical spectra calculated using coupled cluster theory and algebraic diagrammatic construction theory. The coupled cluster singles and doubles with perturbative triples model known as CC3 is shown to accurately reproduce the experimental excitation energies as well as the spacing of the vibrational transitions. In conclusion, the computationalmore » results are also shown to be systematically improved within the coupled cluster hierarchy, with the coupled cluster singles, doubles, triples, and quadruples method faithfully reproducing the experimental vibrational structure.« less
Association schemes perspective of microbubble cluster in ultrasonic fields.
Behnia, S; Yahyavi, M; Habibpourbisafar, R
2018-06-01
Dynamics of a cluster of chaotic oscillators on a network are studied using coupled maps. By introducing the association schemes, we obtain coupling strength in the adjacency matrices form, which satisfies Markov matrices property. We remark that in general, the stability region of the cluster of oscillators at the synchronization state is characterized by Lyapunov exponent which can be defined based on the N-coupled map. As a detailed physical example, dynamics of microbubble cluster in an ultrasonic field are studied using coupled maps. Microbubble cluster dynamics have an indicative highly active nonlinear phenomenon, were not easy to be explained. In this paper, a cluster of microbubbles with a thin elastic shell based on the modified Keller-Herring equation in an ultrasonic field is demonstrated in the framework of the globally coupled map. On the other hand, a relation between the microbubble elements is replaced by a relation between the vertices. Based on this method, the stability region of microbubbles pulsations at complete synchronization state has been obtained analytically. In this way, distances between microbubbles as coupling strength play the crucial role. In the stability region, we thus observe that the problem of study of dynamics of N-microbubble oscillators reduce to that of a single microbubble. Therefore, the important parameters of the isolated microbubble such as applied pressure, driving frequency and the initial radius have effective behavior on the synchronization state. Copyright © 2018 Elsevier B.V. All rights reserved.
Bag of Lines (BoL) for Improved Aerial Scene Representation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sridharan, Harini; Cheriyadat, Anil M.
2014-09-22
Feature representation is a key step in automated visual content interpretation. In this letter, we present a robust feature representation technique, referred to as bag of lines (BoL), for high-resolution aerial scenes. The proposed technique involves extracting and compactly representing low-level line primitives from the scene. The compact scene representation is generated by counting the different types of lines representing various linear structures in the scene. Through extensive experiments, we show that the proposed scene representation is invariant to scale changes and scene conditions and can discriminate urban scene categories accurately. We compare the BoL representation with the popular scalemore » invariant feature transform (SIFT) and Gabor wavelets for their classification and clustering performance on an aerial scene database consisting of images acquired by sensors with different spatial resolutions. The proposed BoL representation outperforms the SIFT- and Gabor-based representations.« less
The Role of Semantic Clustering in Optimal Memory Foraging.
Montez, Priscilla; Thompson, Graham; Kello, Christopher T
2015-11-01
Recent studies of semantic memory have investigated two theories of optimal search adopted from the animal foraging literature: Lévy flights and marginal value theorem. Each theory makes different simplifying assumptions and addresses different findings in search behaviors. In this study, an experiment is conducted to test whether clustering in semantic memory may play a role in evidence for both theories. Labeled magnets and a whiteboard were used to elicit spatial representations of semantic knowledge about animals. Category recall sequences from a separate experiment were used to trace search paths over the spatial representations of animal knowledge. Results showed that spatial distances between animal names arranged on the whiteboard were correlated with inter-response intervals (IRIs) during category recall, and distributions of both dependent measures approximated inverse power laws associated with Lévy flights. In addition, IRIs were relatively shorter when paths first entered animal clusters, and longer when they exited clusters, which is consistent with marginal value theorem. In conclusion, area-restricted searches over clustered semantic spaces may account for two different patterns of results interpreted as supporting two different theories of optimal memory foraging. Copyright © 2015 Cognitive Science Society, Inc.
NASA Technical Reports Server (NTRS)
Lee, Timothy J.; Arnold, James O. (Technical Monitor)
1994-01-01
A new spin orbital basis is employed in the development of efficient open-shell coupled-cluster and perturbation theories that are based on a restricted Hartree-Fock (RHF) reference function. The spin orbital basis differs from the standard one in the spin functions that are associated with the singly occupied spatial orbital. The occupied orbital (in the spin orbital basis) is assigned the delta(+) = 1/square root of 2(alpha+Beta) spin function while the unoccupied orbital is assigned the delta(-) = 1/square root of 2(alpha-Beta) spin function. The doubly occupied and unoccupied orbitals (in the reference function) are assigned the standard alpha and Beta spin functions. The coupled-cluster and perturbation theory wave functions based on this set of "symmetric spin orbitals" exhibit much more symmetry than those based on the standard spin orbital basis. This, together with interacting space arguments, leads to a dramatic reduction in the computational cost for both coupled-cluster and perturbation theory. Additionally, perturbation theory based on "symmetric spin orbitals" obeys Brillouin's theorem provided that spin and spatial excitations are both considered. Other properties of the coupled-cluster and perturbation theory wave functions and models will be discussed.
Near-Edge X-ray Absorption Fine Structure within Multilevel Coupled Cluster Theory.
Myhre, Rolf H; Coriani, Sonia; Koch, Henrik
2016-06-14
Core excited states are challenging to calculate, mainly because they are embedded in a manifold of high-energy valence-excited states. However, their locality makes their determination ideal for local correlation methods. In this paper, we demonstrate the performance of multilevel coupled cluster theory in computing core spectra both within the core-valence separated and the asymmetric Lanczos implementations of coupled cluster linear response theory. We also propose a visualization tool to analyze the excitations using the difference between the ground-state and excited-state electron densities.
Coupling coefficients for tensor product representations of quantum SU(2)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Groenevelt, Wolter, E-mail: w.g.m.groenevelt@tudelft.nl
2014-10-15
We study tensor products of infinite dimensional irreducible {sup *}-representations (not corepresentations) of the SU(2) quantum group. We obtain (generalized) eigenvectors of certain self-adjoint elements using spectral analysis of Jacobi operators associated to well-known q-hypergeometric orthogonal polynomials. We also compute coupling coefficients between different eigenvectors corresponding to the same eigenvalue. Since the continuous spectrum has multiplicity two, the corresponding coupling coefficients can be considered as 2 × 2-matrix-valued orthogonal functions. We compute explicitly the matrix elements of these functions. The coupling coefficients can be considered as q-analogs of Bessel functions. As a results we obtain several q-integral identities involving q-hypergeometricmore » orthogonal polynomials and q-Bessel-type functions.« less
NASA Astrophysics Data System (ADS)
Menezes, R.; Nascimento, J. R. S.; Ribeiro, R. F.; Wotzasek, C.
2002-06-01
We study the equivalence between the /B∧F self-dual (SDB∧F) and the /B∧F topologically massive (TMB∧F) models including the coupling to dynamical, U(1) charged fermionic matter. This is done through an iterative procedure of gauge embedding that produces the dual mapping. In the interactive cases, the minimal coupling adopted for both vector and tensor fields in the self-dual representation is transformed into a non-minimal magnetic like coupling in the topologically massive representation but with the currents swapped. It is known that to establish this equivalence a current-current interaction term is needed to render the matter sector unchanged. We show that both terms arise naturally from the embedding procedure.
Complete characterization of the stability of cluster synchronization in complex dynamical networks.
Sorrentino, Francesco; Pecora, Louis M; Hagerstrom, Aaron M; Murphy, Thomas E; Roy, Rajarshi
2016-04-01
Synchronization is an important and prevalent phenomenon in natural and engineered systems. In many dynamical networks, the coupling is balanced or adjusted to admit global synchronization, a condition called Laplacian coupling. Many networks exhibit incomplete synchronization, where two or more clusters of synchronization persist, and computational group theory has recently proved to be valuable in discovering these cluster states based on the topology of the network. In the important case of Laplacian coupling, additional synchronization patterns can exist that would not be predicted from the group theory analysis alone. Understanding how and when clusters form, merge, and persist is essential for understanding collective dynamics, synchronization, and failure mechanisms of complex networks such as electric power grids, distributed control networks, and autonomous swarming vehicles. We describe a method to find and analyze all of the possible cluster synchronization patterns in a Laplacian-coupled network, by applying methods of computational group theory to dynamically equivalent networks. We present a general technique to evaluate the stability of each of the dynamically valid cluster synchronization patterns. Our results are validated in an optoelectronic experiment on a five-node network that confirms the synchronization patterns predicted by the theory.
Shenvi, Neil; van Aggelen, Helen; Yang, Yang; Yang, Weitao; Schwerdtfeger, Christine; Mazziotti, David
2013-08-07
Tensor hypercontraction is a method that allows the representation of a high-rank tensor as a product of lower-rank tensors. In this paper, we show how tensor hypercontraction can be applied to both the electron repulsion integral tensor and the two-particle excitation amplitudes used in the parametric 2-electron reduced density matrix (p2RDM) algorithm. Because only O(r) auxiliary functions are needed in both of these approximations, our overall algorithm can be shown to scale as O(r(4)), where r is the number of single-particle basis functions. We apply our algorithm to several small molecules, hydrogen chains, and alkanes to demonstrate its low formal scaling and practical utility. Provided we use enough auxiliary functions, we obtain accuracy similar to that of the standard p2RDM algorithm, somewhere between that of CCSD and CCSD(T).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peng, Bo; Kowalski, Karol
In this letter, we introduce the reverse Cuthill-McKee (RCM) algorithm, which is often used for the bandwidth reduction of sparse tensors, to transform the two-electron integral tensors to their block diagonal forms. By further applying the pivoted Cholesky decomposition (CD) on each of the diagonal blocks, we are able to represent the high-dimensional two-electron integral tensors in terms of permutation matrices and low-rank Cholesky vectors. This representation facilitates the low-rank factorization of the high-dimensional tensor contractions that are usually encountered in post-Hartree-Fock calculations. In this letter, we discuss the second-order Møller-Plesset (MP2) method and linear coupled- cluster model with doublesmore » (L-CCD) as two simple examples to demonstrate the efficiency of the RCM-CD technique in representing two-electron integrals in a compact form.« less
NASA Astrophysics Data System (ADS)
Bokhan, Denis; Trubnikov, Dmitrii N.; Perera, Ajith; Bartlett, Rodney J.
2018-04-01
An explicitly-correlated method of calculation of excited states with spin-orbit couplings, has been formulated and implemented. Developed approach utilizes left and right eigenvectors of equation-of-motion coupled-cluster model, which is based on the linearly approximated explicitly correlated coupled-cluster singles and doubles [CCSD(F12)] method. The spin-orbit interactions are introduced by using the spin-orbit mean field (SOMF) approximation of the Breit-Pauli Hamiltonian. Numerical tests for several atoms and molecules show good agreement between explicitly-correlated results and the corresponding values, calculated in complete basis set limit (CBS); the highly-accurate excitation energies can be obtained already at triple- ζ level.
Neurolinguistic approach to natural language processing with applications to medical text analysis.
Duch, Włodzisław; Matykiewicz, Paweł; Pestian, John
2008-12-01
Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts not found directly in the text. The approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector model. Concepts of similar type activate larger clusters of neurons, priming areas in the left and right hemisphere. Analysis of recent brain imaging experiments shows the importance of the right hemisphere non-verbal clusterization. Medical ontologies enable development of a large-scale practical algorithm to re-create pathways of spreading neural activations. First concepts of specific semantic type are identified in the text, and then all related concepts of the same type are added to the text, providing expanded representations. To avoid rapid growth of the extended feature space after each step only the most useful features that increase document clusterization are retained. Short hospital discharge summaries are used to illustrate how this process works on a real, very noisy data. Expanded texts show significantly improved clustering and may be classified with much higher accuracy. Although better approximations to the spreading of neural activations may be devised a practical approach presented in this paper helps to discover pathways used by the brain to process specific concepts, and may be used in large-scale applications.
NASA Astrophysics Data System (ADS)
Qiu, Yiheng; Henderson, Thomas M.; Scuseria, Gustavo E.
2017-05-01
Projected Hartree-Fock theory provides an accurate description of many kinds of strong correlations but does not properly describe weakly correlated systems. Coupled cluster theory, in contrast, does the opposite. It therefore seems natural to combine the two so as to describe both strong and weak correlations with high accuracy in a relatively black-box manner. Combining the two approaches, however, is made more difficult by the fact that the two techniques are formulated very differently. In earlier work, we showed how to write spin-projected Hartree-Fock in a coupled-cluster-like language. Here, we fill in the gaps in that earlier work. Further, we combine projected Hartree-Fock and coupled cluster theory in a variational formulation and show how the combination performs for the description of the Hubbard Hamiltonian and for several small molecular systems.
Tseng, Jui-Pin
2017-02-01
This investigation establishes the global cluster synchronization of complex networks with a community structure based on an iterative approach. The units comprising the network are described by differential equations, and can be non-autonomous and involve time delays. In addition, units in the different communities can be governed by different equations. The coupling configuration of the network is rather general. The coupling terms can be non-diffusive, nonlinear, asymmetric, and with heterogeneous coupling delays. Based on this approach, both delay-dependent and delay-independent criteria for global cluster synchronization are derived. We implement the present approach for a nonlinearly coupled neural network with heterogeneous coupling delays. Two numerical examples are given to show that neural networks can behave in a variety of new collective ways under the synchronization criteria. These examples also demonstrate that neural networks remain synchronized in spite of coupling delays between neurons across different communities; however, they may lose synchrony if the coupling delays between the neurons within the same community are too large, such that the synchronization criteria are violated. Copyright © 2016 Elsevier Ltd. All rights reserved.
Classification of compactified su( N c ) gauge theories with fermions in all representations
NASA Astrophysics Data System (ADS)
Anber, Mohamed M.; Vincent-Genod, Loïc
2017-12-01
We classify su( N c ) gauge theories on R^3× S^1 with massless fermions in higher representations obeying periodic boundary conditions along S^1 . In particular, we single out the class of theories that is asymptotically free and weakly coupled in the infrared, and therefore, is amenable to semi-classical treatment. Our study is conducted by carefully identifying the vacua inside the affine Weyl chamber using Verma bases and Frobenius formula techniques. Theories with fermions in pure representations are generally strongly coupled. The only exceptions are the four-index symmetric representation of su(2) and adjoint representation of su( N c ). However, we find a plethora of admissible theories with fermions in mixed representations. A sub-class of these theories have degenerate perturbative vacua separated by domain walls. In particular, su( N c ) theories with fermions in the mixed representations adjoint⊕fundamental and adjoint⊕two-index symmetric admit degenerate vacua that spontaneously break the parity P , charge conjugation C , and time reversal T symmetries. These are the first examples of strictly weakly coupled gauge theories on R^3× S^1 with spontaneously broken C , P , and T symmetries. We also compute the fermion zero modes in the background of monopole-instantons. The monopoles and their composites (topological molecules) proliferate in the vacuum leading to the confinement of electric charges. Interestingly enough, some theories have also accidental degenerate vacua, which are not related by any symmetry. These vacua admit different numbers of fermionic zero modes, and hence, different kinds of topological molecules. The lack of symmetry, however, indicates that such degeneracy might be lifted by higher order corrections. Finally, we study the general phase structure of adjoint⊕fundamental theories in the small circle and decompactification limits.
Biogeochemical Coupling between Ocean and Sea Ice
NASA Astrophysics Data System (ADS)
Wang, S.; Jeffery, N.; Maltrud, M. E.; Elliott, S.; Wolfe, J.
2016-12-01
Biogeochemical processes in ocean and sea ice are tightly coupled at high latitudes. Ongoing changes in Arctic and Antarctic sea ice domain likely influence the coupled system, not only through physical fields but also biogeochemical properties. Investigating the system and its changes requires representation of ocean and sea ice biogeochemical cycles, as well as their coupling in Earth System Models. Our work is based on ACME-HiLAT, a new offshoot of the Community Earth System Model (CESM), including a comprehensive representation of marine ecosystems in the form of the Biogeochemical Elemental Cycling Module (BEC). A full vertical column sea ice biogeochemical module has recently been incorporated into the sea ice component. We have further introduced code modifications to couple key growth-limiting nutrients (N, Si, Fe), dissolved and particulate organic matter, and phytoplankton classes that are important in polar regions between ocean and sea ice. The coupling of ocean and sea ice biology-chemistry will enable representation of key processes such as the release of important climate active constituents or seeding algae from melting sea ice into surface waters. Sensitivity tests suggest sea ice and ocean biogeochemical coupling influences phytoplankton competition, biological production, and the CO2 flux. Sea ice algal seeding plays an important role in determining phytoplankton composition of Arctic early spring blooms, since different groups show various responses to the seeding biomass. Iron coupling leads to increased phytoplankton biomass in the Southern Ocean, which also affects carbon uptake via the biological pump. The coupling of macronutrients and organic matter may have weaker influences on the marine ecosystem. Our developments will allow climate scientists to investigate the fully coupled responses of the sea ice-ocean BGC system to physical changes in polar climate.
Forbidden coherent transfer observed between two realizations of quasiharmonic spin systems
NASA Astrophysics Data System (ADS)
Bertaina, S.; Yue, G.; Dutoit, C.-E.; Chiorescu, I.
2017-07-01
The multilevel system
NASA Astrophysics Data System (ADS)
Guo, Xinwei; Qu, Zexing; Gao, Jiali
2018-01-01
The multi-state density functional theory (MSDFT) provides a convenient way to estimate electronic coupling of charge transfer processes based on a diabatic representation. Its performance has been benchmarked against the HAB11 database with a mean unsigned error (MUE) of 17 meV between MSDFT and ab initio methods. The small difference may be attributed to different representations, diabatic from MSDFT and adiabatic from ab initio calculations. In this discussion, we conclude that MSDFT provides a general and efficient way to estimate the electronic coupling for charge-transfer rate calculations based on the Marcus-Hush model.
Secure Base Narrative Representations and Intimate Partner Violence: A Dyadic Perspective
Karakurt, Gunnur; Silver, Kristin E.; Keiley, Margaret K.
2015-01-01
This study aimed to understand the relationship between secure base phenomena and dating violence among couples. Within a relationship, a secure base can be defined as a balancing act of proximity-seeking and exploration at various times and contexts with the assurance of a caregiver’s availability and responsiveness in emotionally distressing situations. Participants were 87 heterosexual couples. The Actor-Partner Interdependence Model was used to examine the relationship between each partner’s scores on secure base representational knowledge and intimate partner violence. Findings demonstrated that women’s secure base representational knowledge had a significant direct negative effect on the victimization of both men and women, while men’s secure base representational knowledge did not have any significant partner or actor effects. Therefore, findings suggest that women with insecure attachments may be more vulnerable to being both the victims and the perpetrators of PMID:27445432
On the adiabatic representation of Meyer-Miller electronic-nuclear dynamics
NASA Astrophysics Data System (ADS)
Cotton, Stephen J.; Liang, Ruibin; Miller, William H.
2017-08-01
The Meyer-Miller (MM) classical vibronic (electronic + nuclear) Hamiltonian for electronically non-adiabatic dynamics—as used, for example, with the recently developed symmetrical quasiclassical (SQC) windowing model—can be written in either a diabatic or an adiabatic representation of the electronic degrees of freedom, the two being a canonical transformation of each other, thus giving the same dynamics. Although most recent applications of this SQC/MM approach have been carried out in the diabatic representation—because most of the benchmark model problems that have exact quantum results available for comparison are typically defined in a diabatic representation—it will typically be much more convenient to work in the adiabatic representation, e.g., when using Born-Oppenheimer potential energy surfaces (PESs) and derivative couplings that come from electronic structure calculations. The canonical equations of motion (EOMs) (i.e., Hamilton's equations) that come from the adiabatic MM Hamiltonian, however, in addition to the common first-derivative couplings, also involve second-derivative non-adiabatic coupling terms (as does the quantum Schrödinger equation), and the latter are considerably more difficult to calculate. This paper thus revisits the adiabatic version of the MM Hamiltonian and describes a modification of the classical adiabatic EOMs that are entirely equivalent to Hamilton's equations but that do not involve the second-derivative couplings. The second-derivative coupling terms have not been neglected; they simply do not appear in these modified adiabatic EOMs. This means that SQC/MM calculations can be carried out in the adiabatic representation, without approximation, needing only the PESs and the first-derivative coupling elements. The results of example SQC/MM calculations are presented, which illustrate this point, and also the fact that simply neglecting the second-derivative couplings in Hamilton's equations (and presumably also in the Schrödinger equation) can cause very significant errors.
Symmetries and stability of chimera states in small, globally-coupled networks
NASA Astrophysics Data System (ADS)
Hart, Joseph D.; Bansal, Kanika; Murphy, Thomas E.; Roy, Rajarshi
It has recently been demonstrated that symmetries in a network's topology can help predict the patterns of synchronized clusters that can emerge in a network of coupled oscillators. This and related discoveries have led to increased interest in both network symmetries and cluster synchronization. In parallel with these discoveries, interest in chimera states-dynamical patterns in which a network separates into coherent and incoherent portions-has grown, and chimeras have now been observed in a variety of experimental systems. We present an opto-electronic experiment in which both chimera states and synchronized clusters are observed in a small, globally-coupled network. We show that the symmetries and sub-symmetries of the network permit the formation of the chimera and cluster states. A recently developed group theoretical approach enables us to predict the stability of the observed chimera and cluster states, and highlights the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization.
Protonation and Proton-Coupled Electron Transfer at S-Ligated [4Fe-4S] Clusters
Morris, Wesley D.; Darcy, Julia W.; Mayer, James M.
2015-01-01
Biological [Fe-S] clusters are increasingly recognized to undergo proton-coupled electron transfer (PCET), but the site of protonation, mechanism, and role for PCET remains largely unknown. Here we explore this reactivity with synthetic model clusters. Protonation of the arylthiolate-ligated [4Fe-4S] cluster [Fe4S4(SAr)4]2- (1, SAr = S-2,4-6-(iPr)3C6H2) leads to thiol dissociation, reversibly forming [Fe4S4(SAr)3L]1- (2) + ArSH (L = solvent, and/or conjugate base). Solutions of 2 + ArSH react with the nitroxyl radical TEMPO to give [Fe4S4(SAr)4]1- (1ox) and TEMPOH. This reaction involves PCET coupled to thiolate association and may proceed via the unobserved protonated cluster [Fe4S4(SAr)3(HSAr)]1-(1-H). Similar reactions with this and related clusters proceed comparably. An understanding of the PCET thermochemistry of this cluster system has been developed, encompassing three different redox levels and two protonation states. PMID:25965413
Influences of adding negative couplings between cliques of Kuramoto-like oscillators
NASA Astrophysics Data System (ADS)
Yang, Li-xin; Lin, Xiao-lin; Jiang, Jun
2018-06-01
We study the dynamics in a clustered network of coupled oscillators by considering positive and negative coupling schemes. Second order oscillators can be interpreted as a model of consumers and generators working in a power network. Numerical results indicate that coupling strategies play an important role in the synchronizability of the clustered power network. It is found that the synchronizability can be enhanced as the positive intragroup connections increase. Meanwhile, when the intragroup interactions are positive and the probability p that two nodes belonging to different clusters are connected is increased, the synchronization has better performance. Besides, when the intragroup connections are negative, it is observed that the power network has poor synchronizability as the probability p increases. Our simulation results can help us understand the collective behavior of the power network with positive and negative couplings.
A Probabilistic Clustering Theory of the Organization of Visual Short-Term Memory
ERIC Educational Resources Information Center
Orhan, A. Emin; Jacobs, Robert A.
2013-01-01
Experimental evidence suggests that the content of a memory for even a simple display encoded in visual short-term memory (VSTM) can be very complex. VSTM uses organizational processes that make the representation of an item dependent on the feature values of all displayed items as well as on these items' representations. Here, we develop a…
X-ray aspects of the DAFT/FADA clusters
NASA Astrophysics Data System (ADS)
Guennou, L.; Durret, F.; Lima Neto, G. B.; Adami, C.
2012-12-01
We have undertaken the DAFT/FADA survey with the aim of applying constraints on dark energy based on weak lensing tomography as well as obtaining homogeneous and high quality data for a sample of 91 massive clusters in the redshift range [0.4,0.9] for which there are HST archive data. We have analysed the XMM-Newton data available for 42 of these clusters to derive their X-ray temperatures and luminosities and search for substructures. This study was coupled with a dynamical analysis for the 26 clusters having at least 30 spectroscopic galaxy redshifts in the cluster range. We present preliminary results on the coupled X-ray and dynamical analyses of these clusters.
Compositional and phase relations among rare earth element minerals
NASA Technical Reports Server (NTRS)
Burt, D. M.
1990-01-01
This paper discusses the compositional and phase relationships among minerals in which rare earth elements (REE) occur as essential constituents (e.g., bastnaesite, monazite, xenotime, aeschynite, allanite). Particular consideration is given to the vector representation of complex coupled substitutions in selected REE-bearing minerals and to the REE partitioning between minerals as related to the acid-base tendencies and mineral stabilities. It is shown that the treatment of coupled substitutions as vector quantities facilitates graphical representation of mineral composition spaces.
Categorical clustering of the neural representation of color.
Brouwer, Gijs Joost; Heeger, David J
2013-09-25
Cortical activity was measured with functional magnetic resonance imaging (fMRI) while human subjects viewed 12 stimulus colors and performed either a color-naming or diverted attention task. A forward model was used to extract lower dimensional neural color spaces from the high-dimensional fMRI responses. The neural color spaces in two visual areas, human ventral V4 (V4v) and VO1, exhibited clustering (greater similarity between activity patterns evoked by stimulus colors within a perceptual category, compared to between-category colors) for the color-naming task, but not for the diverted attention task. Response amplitudes and signal-to-noise ratios were higher in most visual cortical areas for color naming compared to diverted attention. But only in V4v and VO1 did the cortical representation of color change to a categorical color space. A model is presented that induces such a categorical representation by changing the response gains of subpopulations of color-selective neurons.
Categorical Clustering of the Neural Representation of Color
Heeger, David J.
2013-01-01
Cortical activity was measured with functional magnetic resonance imaging (fMRI) while human subjects viewed 12 stimulus colors and performed either a color-naming or diverted attention task. A forward model was used to extract lower dimensional neural color spaces from the high-dimensional fMRI responses. The neural color spaces in two visual areas, human ventral V4 (V4v) and VO1, exhibited clustering (greater similarity between activity patterns evoked by stimulus colors within a perceptual category, compared to between-category colors) for the color-naming task, but not for the diverted attention task. Response amplitudes and signal-to-noise ratios were higher in most visual cortical areas for color naming compared to diverted attention. But only in V4v and VO1 did the cortical representation of color change to a categorical color space. A model is presented that induces such a categorical representation by changing the response gains of subpopulations of color-selective neurons. PMID:24068814
Reduced graphs and their applications in chemoinformatics.
Birchall, Kristian; Gillet, Valerie J
2011-01-01
Reduced graphs provide summary representations of chemical structures by collapsing groups of connected atoms into single nodes while preserving the topology of the original structures. This chapter reviews the extensive work that has been carried out on reduced graphs at The University of Sheffield and includes discussion of their application to the representation and search of Markush structures in patents, the varied approaches that have been implemented for similarity searching, their use in cluster representation, the different ways in which they have been applied to extract structure-activity relationships and their use in encoding bioisosteres.
Diagrammatic representation of scalar QCD and sign problem at nonzero chemical potential
NASA Astrophysics Data System (ADS)
Bruckmann, Falk; Wellnhofer, Jacob
2018-01-01
We consider QCD at strong coupling with scalar quarks coupled to a chemical potential. Performing the link integrals we present a diagrammatic representation of the path integral weight. It is based on mesonic and baryonic building blocks, in close analogy to fermionic QCD. Likewise, the baryon loops are subject to a manifest conservation of the baryon number. The sign problem is expected to disappear in this representation and we do confirm this for three flavors, where a scalar baryon can be built and, thus, a dependence on the chemical potential occurs. For higher flavor number, we analyze examples for a potential sign problem in the baryon sector and conjecture that all weights are positive upon exploring the current conservation of each flavor.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Chen, Guanrong
All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding ormore » deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.« less
NASA Astrophysics Data System (ADS)
Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong
2014-06-01
All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.
Synchronization as Aggregation: Cluster Kinetics of Pulse-Coupled Oscillators.
O'Keeffe, Kevin P; Krapivsky, P L; Strogatz, Steven H
2015-08-07
We consider models of identical pulse-coupled oscillators with global interactions. Previous work showed that under certain conditions such systems always end up in sync, but did not quantify how small clusters of synchronized oscillators progressively coalesce into larger ones. Using tools from the study of aggregation phenomena, we obtain exact results for the time-dependent distribution of cluster sizes as the system evolves from disorder to synchrony.
Configurational coupled cluster approach with applications to magnetic model systems
NASA Astrophysics Data System (ADS)
Wu, Siyuan; Nooijen, Marcel
2018-05-01
A general exponential, coupled cluster like, approach is discussed to extract an effective Hamiltonian in configurational space, as a sum of 1-body, 2-body up to n-body operators. The simplest two-body approach is illustrated by calculations on simple magnetic model systems. A key feature of the approach is that equations up to a certain rank do not depend on higher body cluster operators.
NASA Astrophysics Data System (ADS)
Derevianko, Andrei; Porsev, Sergey G.
2005-03-01
We consider evaluation of matrix elements with the coupled-cluster method. Such calculations formally involve infinite number of terms and we devise a method of partial summation (dressing) of the resulting series. Our formalism is built upon an expansion of the product C†C of cluster amplitudes C into a sum of n -body insertions. We consider two types of insertions: particle (hole) line insertion and two-particle (two-hole) random-phase-approximation-like insertion. We demonstrate how to “dress” these insertions and formulate iterative equations. We illustrate the dressing equations in the case when the cluster operator is truncated at single and double excitations. Using univalent systems as an example, we upgrade coupled-cluster diagrams for matrix elements with the dressed insertions and highlight a relation to pertinent fourth-order diagrams. We illustrate our formalism with relativistic calculations of the hyperfine constant A(6s) and the 6s1/2-6p1/2 electric-dipole transition amplitude for the Cs atom. Finally, we augment the truncated coupled-cluster calculations with otherwise omitted fourth order diagrams. The resulting analysis for Cs is complete through the fourth order of many-body perturbation theory and reveals an important role of triple and disconnected quadruple excitations.
The Impact of Air-Sea Interactions on the Representation of Tropical Precipitation Extremes
NASA Astrophysics Data System (ADS)
Hirons, L. C.; Klingaman, N. P.; Woolnough, S. J.
2018-02-01
The impacts of air-sea interactions on the representation of tropical precipitation extremes are investigated using an atmosphere-ocean-mixed-layer coupled model. The coupled model is compared to two atmosphere-only simulations driven by the coupled-model sea-surface temperatures (SSTs): one with 31 day running means (31 d), the other with a repeating mean annual cycle. This allows separation of the effects of interannual SST variability from those of coupled feedbacks on shorter timescales. Crucially, all simulations have a consistent mean state with very small SST biases against present-day climatology. 31d overestimates the frequency, intensity, and persistence of extreme tropical precipitation relative to the coupled model, likely due to excessive SST-forced precipitation variability. This implies that atmosphere-only attribution and time-slice experiments may overestimate the strength and duration of precipitation extremes. In the coupled model, air-sea feedbacks damp extreme precipitation, through negative local thermodynamic feedbacks between convection, surface fluxes, and SST.
Representation and presentation of requirements knowledge
NASA Technical Reports Server (NTRS)
Johnson, W. L.; Feather, Martin S.; Harris, David R.
1992-01-01
An approach to representation and presentation of knowledge used in the ARIES, an experimental requirements/specification environment, is described. The approach applies the notion of a representation architecture to the domain of software engineering and incorporates a strong coupling to a transformation system. It is characterized by a single highly expressive underlying representation, interfaced simultaneously to multiple presentations, each with notations of differing degrees of expressivity. This enables analysts to use multiple languages for describing systems and have these descriptions yield a single consistent model of the system.
NASA Astrophysics Data System (ADS)
Maitra, Rahul; Akinaga, Yoshinobu; Nakajima, Takahito
2017-08-01
A single reference coupled cluster theory that is capable of including the effect of connected triple excitations has been developed and implemented. This is achieved by regrouping the terms appearing in perturbation theory and parametrizing through two different sets of exponential operators: while one of the exponentials, involving general substitution operators, annihilates the ground state but has a non-vanishing effect when it acts on the excited determinant, the other is the regular single and double excitation operator in the sense of conventional coupled cluster theory, which acts on the Hartree-Fock ground state. The two sets of operators are solved as coupled non-linear equations in an iterative manner without significant increase in computational cost than the conventional coupled cluster theory with singles and doubles excitations. A number of physically motivated and computationally advantageous sufficiency conditions are invoked to arrive at the working equations and have been applied to determine the ground state energies of a number of small prototypical systems having weak multi-reference character. With the knowledge of the correlated ground state, we have reconstructed the triple excitation operator and have performed equation of motion with coupled cluster singles, doubles, and triples to obtain the ionization potential and excitation energies of these molecules as well. Our results suggest that this is quite a reasonable scheme to capture the effect of connected triple excitations as long as the ground state remains weakly multi-reference.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fransson, Thomas; Norman, Patrick; Coriani, Sonia
2013-03-28
Near carbon K-edge X-ray absorption fine structure spectra of a series of fluorine-substituted ethenes and acetone have been studied using coupled cluster and density functional theory (DFT) polarization propagator methods, as well as the static-exchange (STEX) approach. With the complex polarization propagator (CPP) implemented in coupled cluster theory, relaxation effects following the excitation of core electrons are accounted for in terms of electron correlation, enabling a systematic convergence of these effects with respect to electron excitations in the cluster operator. Coupled cluster results have been used as benchmarks for the assessment of propagator methods in DFT as well as themore » state-specific static-exchange approach. Calculations on ethene and 1,1-difluoroethene illustrate the possibility of using nonrelativistic coupled cluster singles and doubles (CCSD) with additional effects of electron correlation and relativity added as scalar shifts in energetics. It has been demonstrated that CPP spectra obtained with coupled cluster singles and approximate doubles (CC2), CCSD, and DFT (with a Coulomb attenuated exchange-correlation functional) yield excellent predictions of chemical shifts for vinylfluoride, 1,1-difluoroethene, trifluoroethene, as well as good spectral features for acetone in the case of CCSD and DFT. Following this, CPP-DFT is considered to be a viable option for the calculation of X-ray absorption spectra of larger {pi}-conjugated systems, and CC2 is deemed applicable for chemical shifts but not for studies of fine structure features. The CCSD method as well as the more approximate CC2 method are shown to yield spectral features relating to {pi}*-resonances in good agreement with experiment, not only for the aforementioned molecules but also for ethene, cis-1,2-difluoroethene, and tetrafluoroethene. The STEX approach is shown to underestimate {pi}*-peak separations due to spectral compressions, a characteristic which is inherent to this method.« less
Fransson, Thomas; Coriani, Sonia; Christiansen, Ove; Norman, Patrick
2013-03-28
Near carbon K-edge X-ray absorption fine structure spectra of a series of fluorine-substituted ethenes and acetone have been studied using coupled cluster and density functional theory (DFT) polarization propagator methods, as well as the static-exchange (STEX) approach. With the complex polarization propagator (CPP) implemented in coupled cluster theory, relaxation effects following the excitation of core electrons are accounted for in terms of electron correlation, enabling a systematic convergence of these effects with respect to electron excitations in the cluster operator. Coupled cluster results have been used as benchmarks for the assessment of propagator methods in DFT as well as the state-specific static-exchange approach. Calculations on ethene and 1,1-difluoroethene illustrate the possibility of using nonrelativistic coupled cluster singles and doubles (CCSD) with additional effects of electron correlation and relativity added as scalar shifts in energetics. It has been demonstrated that CPP spectra obtained with coupled cluster singles and approximate doubles (CC2), CCSD, and DFT (with a Coulomb attenuated exchange-correlation functional) yield excellent predictions of chemical shifts for vinylfluoride, 1,1-difluoroethene, trifluoroethene, as well as good spectral features for acetone in the case of CCSD and DFT. Following this, CPP-DFT is considered to be a viable option for the calculation of X-ray absorption spectra of larger π-conjugated systems, and CC2 is deemed applicable for chemical shifts but not for studies of fine structure features. The CCSD method as well as the more approximate CC2 method are shown to yield spectral features relating to π∗-resonances in good agreement with experiment, not only for the aforementioned molecules but also for ethene, cis-1,2-difluoroethene, and tetrafluoroethene. The STEX approach is shown to underestimate π∗-peak separations due to spectral compressions, a characteristic which is inherent to this method.
Transition properties from the Hermitian formulation of the coupled cluster polarization propagator
NASA Astrophysics Data System (ADS)
Tucholska, Aleksandra M.; Modrzejewski, Marcin; Moszynski, Robert
2014-09-01
Theory of one-electron transition density matrices has been formulated within the time-independent coupled cluster method for the polarization propagator [R. Moszynski, P. S. Żuchowski, and B. Jeziorski, Coll. Czech. Chem. Commun. 70, 1109 (2005)]. Working expressions have been obtained and implemented with the coupled cluster method limited to single, double, and linear triple excitations (CC3). Selected dipole and quadrupole transition probabilities of the alkali earth atoms, computed with the new transition density matrices are compared to the experimental data. Good agreement between theory and experiment is found. The results obtained with the new approach are of the same quality as the results obtained with the linear response coupled cluster theory. The one-electron density matrices for the ground state in the CC3 approximation have also been implemented. The dipole moments for a few representative diatomic molecules have been computed with several variants of the new approach, and the results are discussed to choose the approximation with the best balance between the accuracy and computational efficiency.
Neurolinguistic Approach to Natural Language Processing with Applications to Medical Text Analysis
Matykiewicz, Paweł; Pestian, John
2008-01-01
Understanding written or spoken language presumably involves spreading neural activation in the brain. This process may be approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts that are not found directly in the text. Approximation of this process is of great practical and theoretical interest. Although activations of neural circuits involved in representation of words rapidly change in time snapshots of these activations spreading through associative networks may be captured in a vector model. Concepts of similar type activate larger clusters of neurons, priming areas in the left and right hemisphere. Analysis of recent brain imaging experiments shows the importance of the right hemisphere non-verbal clusterization. Medical ontologies enable development of a large-scale practical algorithm to re-create pathways of spreading neural activations. First concepts of specific semantic type are identified in the text, and then all related concepts of the same type are added to the text, providing expanded representations. To avoid rapid growth of the extended feature space after each step only the most useful features that increase document clusterization are retained. Short hospital discharge summaries are used to illustrate how this process works on a real, very noisy data. Expanded texts show significantly improved clustering and may be classified with much higher accuracy. Although better approximations to the spreading of neural activations may be devised a practical approach presented in this paper helps to discover pathways used by the brain to process specific concepts, and may be used in large-scale applications. PMID:18614334
Ndome, Hameth; Eisfeld, Wolfgang
2012-08-14
A new method has been reported recently [H. Ndome, R. Welsch, and W. Eisfeld, J. Chem. Phys. 136, 034103 (2012)] that allows the efficient generation of fully coupled potential energy surfaces (PESs) including derivative and spin-orbit (SO) coupling. The method is based on the diabatic asymptotic representation of the molecular fine structure states and an effective relativistic coupling operator and therefore is called effective relativistic coupling by asymptotic representation (ERCAR). The resulting diabatic spin-orbit coupling matrix is constant and the geometry dependence of the coupling between the eigenstates is accounted for by the diabatization. This approach allows to generate an analytical model for the fully coupled PESs without performing any ab initio SO calculations (except perhaps for the atoms) and thus is very efficient. In the present work, we study the performance of this new method for the example of hydrogen iodide as a well-established test case. Details of the diabatization and the accuracy of the results are investigated in comparison to reference ab initio calculations. The energies of the adiabatic fine structure states are reproduced in excellent agreement with reference ab initio data. It is shown that the accuracy of the ERCAR approach mainly depends on the quality of the underlying ab initio data. This is also the case for dissociation and vibrational level energies, which are influenced by the SO coupling. A method is presented how one-electron operators and the corresponding properties can be evaluated in the framework of the ERCAR approach. This allows the computation of dipole and transition moments of the fine structure states in good agreement with ab initio data. The new method is shown to be very promising for the construction of fully coupled PESs for more complex polyatomic systems to be used in quantum dynamics studies.
Communication: Finite size correction in periodic coupled cluster theory calculations of solids.
Liao, Ke; Grüneis, Andreas
2016-10-14
We present a method to correct for finite size errors in coupled cluster theory calculations of solids. The outlined technique shares similarities with electronic structure factor interpolation methods used in quantum Monte Carlo calculations. However, our approach does not require the calculation of density matrices. Furthermore we show that the proposed finite size corrections achieve chemical accuracy in the convergence of second-order Møller-Plesset perturbation and coupled cluster singles and doubles correlation energies per atom for insulating solids with two atomic unit cells using 2 × 2 × 2 and 3 × 3 × 3 k-point meshes only.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eliav, E.; Kaldor, U.; Ishikawa, Y.
1994-12-31
Relativistic pair correlation energies of Xe were computed by employing a recently developed relativistic coupled cluster theory based on the no-pair Dirac-Coulomb-Breit Hamiltonian. The matrix Dirac-Fock-Breit SCF and relativistic coupled cluster calculations were performed by means of expansion in basis sets of well-tempered Gaussian spinors. A detailed study of the pair correlation energies in Xe is performed, in order to investigate the effects of the low-frequency Breit interaction on the correlation energies of Xe. Nonadditivity of correlation and relativistic (particularly Breit) effects is discussed.
A nonperturbative light-front coupled-cluster method
NASA Astrophysics Data System (ADS)
Hiller, J. R.
2012-10-01
The nonperturbative Hamiltonian eigenvalue problem for bound states of a quantum field theory is formulated in terms of Dirac's light-front coordinates and then approximated by the exponential-operator technique of the many-body coupled-cluster method. This approximation eliminates any need for the usual approximation of Fock-space truncation. Instead, the exponentiated operator is truncated, and the terms retained are determined by a set of nonlinear integral equations. These equations are solved simultaneously with an effective eigenvalue problem in the valence sector, where the number of constituents is small. Matrix elements can be calculated, with extensions of techniques from standard coupled-cluster theory, to obtain form factors and other observables.
Coulomb- and Antiferromagnetic-Induced Fission in Doubly Charged Cubelike Fe-S Clusters
NASA Astrophysics Data System (ADS)
Yang, Xin; Wang, Xue-Bin; Niu, Shuqiang; Pickett, Chris J.; Ichiye, Toshiko; Wang, Lai-Sheng
2002-09-01
We report the observation of symmetric fission in doubly charged Fe-S cluster anions, [Fe4S4X4]2- -->2[Fe2S2X2]- (X=Cl,Br), owing to both Coulomb repulsion and antiferromagnetic coupling. Photoelectron spectroscopy shows that both the parent and the fission fragments have similar electronic structures and confirms the inverted energy schemes due to the strong spin polarization of the Fe 3d levels. The current observation provides direct confirmation for the unusual spin couplings in the [Fe4S4X4]2- clusters, which contain two valent-delocalized and ferromagnetically coupled Fe2S2 subunits.
Solvatochromic shifts from coupled-cluster theory embedded in density functional theory
NASA Astrophysics Data System (ADS)
Höfener, Sebastian; Gomes, André Severo Pereira; Visscher, Lucas
2013-09-01
Building on the framework recently reported for determining general response properties for frozen-density embedding [S. Höfener, A. S. P. Gomes, and L. Visscher, J. Chem. Phys. 136, 044104 (2012)], 10.1063/1.3675845, in this work we report a first implementation of an embedded coupled-cluster in density-functional theory (CC-in-DFT) scheme for electronic excitations, where only the response of the active subsystem is taken into account. The formalism is applied to the calculation of coupled-cluster excitation energies of water and uracil in aqueous solution. We find that the CC-in-DFT results are in good agreement with reference calculations and experimental results. The accuracy of calculations is mainly sensitive to factors influencing the correlation treatment (basis set quality, truncation of the cluster operator) and to the embedding treatment of the ground-state (choice of density functionals). This allows for efficient approximations at the excited state calculation step without compromising the accuracy. This approximate scheme makes it possible to use a first principles approach to investigate environment effects with specific interactions at coupled-cluster level of theory at a cost comparable to that of calculations of the individual subsystems in vacuum.
Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.
Zhang, Guoqing; Sun, Huaijiang; Porikli, Fatih; Liu, Yazhou; Sun, Quansen
2017-08-29
In recent years, sparse representation based classification (SRC) is one of the most successful methods and has been shown impressive performance in various classification tasks. However, when the training data has a different distribution than the testing data, the learned sparse representation may not be optimal, and the performance of SRC will be degraded significantly. To address this problem, in this paper, we propose an optimal couple projections for domain-adaptive sparse representation-based classification (OCPD-SRC) method, in which the discriminative features of data in the two domains are simultaneously learned with the dictionary that can succinctly represent the training and testing data in the projected space. OCPD-SRC is designed based on the decision rule of SRC, with the objective to learn coupled projection matrices and a common discriminative dictionary such that the between-class sparse reconstruction residuals of data from both domains are maximized, and the within-class sparse reconstruction residuals of data are minimized in the projected low-dimensional space. Thus, the resulting representations can well fit SRC and simultaneously have a better discriminant ability. In addition, our method can be easily extended to multiple domains and can be kernelized to deal with the nonlinear structure of data. The optimal solution for the proposed method can be efficiently obtained following the alternative optimization method. Extensive experimental results on a series of benchmark databases show that our method is better or comparable to many state-of-the-art methods.
Description and evaluation of the Earth System Regional Climate Model (RegCM-ES)
NASA Astrophysics Data System (ADS)
Farneti, Riccardo; Sitz, Lina; Di Sante, Fabio; Fuentes-Franco, Ramon; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Giorgi, Filippo
2017-04-01
The increasing availability of satellite remote sensing data, of high temporal frequency and spatial resolution, has provided a new and enhanced view of the global ocean and atmosphere, revealing strong air-sea coupling processes throughout the ocean basins. In order to obtain an accurate representation and better understanding of the climate system, its variability and change, the inclusion of all mechanisms of interaction among the different sub-components, at high temporal and spatial resolution, becomes ever more desirable. Recently, global coupled models have been able to progressively refine their horizontal resolution to attempt to resolve smaller-scale processes. However, regional coupled ocean-atmosphere models can achieve even finer resolutions and provide additional information on the mechanisms of air-sea interactions and feedbacks. Here we describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES). RegCM-ES presently includes the coupling between atmosphere, ocean, land surface and sea-ice components, as well as an hydrological and ocean biogeochemistry model. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains. RegCM-ES has shown improvements in the representation of precipitation and SST fields over the tested domains, as well as realistic representations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source making it suitable for usage by the large scientific community.
X-ray and optical substructures of the DAFT/FADA survey clusters
NASA Astrophysics Data System (ADS)
Guennou, L.; Durret, F.; Adami, C.; Lima Neto, G. B.
2013-04-01
We have undertaken the DAFT/FADA survey with the double aim of setting constraints on dark energy based on weak lensing tomography and of obtaining homogeneous and high quality data for a sample of 91 massive clusters in the redshift range 0.4-0.9 for which there were HST archive data. We have analysed the XMM-Newton data available for 42 of these clusters to derive their X-ray temperatures and luminosities and search for substructures. Out of these, a spatial analysis was possible for 30 clusters, but only 23 had deep enough X-ray data for a really robust analysis. This study was coupled with a dynamical analysis for the 26 clusters having at least 30 spectroscopic galaxy redshifts in the cluster range. Altogether, the X-ray sample of 23 clusters and the optical sample of 26 clusters have 14 clusters in common. We present preliminary results on the coupled X-ray and dynamical analyses of these 14 clusters.
Tabrizi, Shadan Ghassemi; Pelmenschikov, Vladimir; Noodleman, Louis; Kaupp, Martin
2016-01-12
An unprecedented [4Fe-3S] cluster proximal to the regular [NiFe] active site has recently been found to be responsible for the ability of membrane-bound hydrogenases (MBHs) to oxidize dihydrogen in the presence of ambient levels of oxygen. Starting from proximal cluster models of a recent DFT study on the redox-dependent structural transformation of the [4Fe-3S] cluster, (57)Fe Mössbauer parameters (electric field gradients, isomer shifts, and nuclear hyperfine couplings) were calculated using DFT. Our results revise the previously reported correspondence of Mössbauer signals and iron centers in the [4Fe-3S](3+) reduced-state proximal cluster. Similar conflicting assignments are also resolved for the [4Fe-3S](5+) superoxidized state with particular regard to spin-coupling in the broken-symmetry DFT calculations. Calculated (57)Fe hyperfine coupling (HFC) tensors expose discrepancies in the experimental set of HFC tensors and substantiate the need for additional experimental work on the magnetic properties of the MBH proximal cluster in its reduced and superoxidized redox states.
Deep linear autoencoder and patch clustering-based unified one-dimensional coding of image and video
NASA Astrophysics Data System (ADS)
Li, Honggui
2017-09-01
This paper proposes a unified one-dimensional (1-D) coding framework of image and video, which depends on deep learning neural network and image patch clustering. First, an improved K-means clustering algorithm for image patches is employed to obtain the compact inputs of deep artificial neural network. Second, for the purpose of best reconstructing original image patches, deep linear autoencoder (DLA), a linear version of the classical deep nonlinear autoencoder, is introduced to achieve the 1-D representation of image blocks. Under the circumstances of 1-D representation, DLA is capable of attaining zero reconstruction error, which is impossible for the classical nonlinear dimensionality reduction methods. Third, a unified 1-D coding infrastructure for image, intraframe, interframe, multiview video, three-dimensional (3-D) video, and multiview 3-D video is built by incorporating different categories of videos into the inputs of patch clustering algorithm. Finally, it is shown in the results of simulation experiments that the proposed methods can simultaneously gain higher compression ratio and peak signal-to-noise ratio than those of the state-of-the-art methods in the situation of low bitrate transmission.
Izquierdo, Javier A; Sizova, Maria V; Lynd, Lee R
2010-06-01
The enrichment from nature of novel microbial communities with high cellulolytic activity is useful in the identification of novel organisms and novel functions that enhance the fundamental understanding of microbial cellulose degradation. In this work we identify predominant organisms in three cellulolytic enrichment cultures with thermophilic compost as an inoculum. Community structure based on 16S rRNA gene clone libraries featured extensive representation of clostridia from cluster III, with minor representation of clostridial clusters I and XIV and a novel Lutispora species cluster. Our studies reveal different levels of 16S rRNA gene diversity, ranging from 3 to 18 operational taxonomic units (OTUs), as well as variability in community membership across the three enrichment cultures. By comparison, glycosyl hydrolase family 48 (GHF48) diversity analyses revealed a narrower breadth of novel clostridial genes associated with cultured and uncultured cellulose degraders. The novel GHF48 genes identified in this study were related to the novel clostridia Clostridium straminisolvens and Clostridium clariflavum, with one cluster sharing as little as 73% sequence similarity with the closest known relative. In all, 14 new GHF48 gene sequences were added to the known diversity of 35 genes from cultured species.
Benchmark solutions for the galactic heavy-ion transport equations with energy and spatial coupling
NASA Technical Reports Server (NTRS)
Ganapol, Barry D.; Townsend, Lawrence W.; Lamkin, Stanley L.; Wilson, John W.
1991-01-01
Nontrivial benchmark solutions are developed for the galactic heavy ion transport equations in the straightahead approximation with energy and spatial coupling. Analytical representations of the ion fluxes are obtained for a variety of sources with the assumption that the nuclear interaction parameters are energy independent. The method utilizes an analytical LaPlace transform inversion to yield a closed form representation that is computationally efficient. The flux profiles are then used to predict ion dose profiles, which are important for shield design studies.
Anionic water pentamer and hexamer clusters: An extensive study of structures and energetics
NASA Astrophysics Data System (ADS)
Ünal, Aslı; Bozkaya, Uǧur
2018-03-01
An extensive study of structures and energetics for anionic pentamer and hexamer clusters is performed employing high level ab initio quantum chemical methods, such as the density-fitted orbital-optimized linearized coupled-cluster doubles (DF-OLCCD), coupled-cluster singles and doubles (CCSD), and coupled-cluster singles and doubles with perturbative triples [CCSD(T)] methods. In this study, sixteen anionic pentamer clusters and eighteen anionic hexamer clusters are reported. Relative, binding, and vertical detachment energies (VDE) are presented at the complete basis set limit (CBS), extrapolating energies of aug4-cc-pVTZ and aug4-cc-pVQZ custom basis sets. The largest VDE values obtained at the CCSD(T)/CBS level are 9.9 and 11.2 kcal mol-1 for pentamers and hexamers, respectively, which are in very good agreement with the experimental values of 9.5 and 11.1 kcal mol-1. Our binding energy results, at the CCSD(T)/CBS level, indicate strong bindings in anionic clusters due to hydrogen bond interactions. The average binding energy per water molecules is -5.0 and -5.3 kcal mol-1 for pentamers and hexamers, respectively. Furthermore, our results demonstrate that the DF-OLCCD method approaches to the CCSD(T) quality for anionic clusters. The inexpensive analytic gradients of DF-OLCCD compared to CCSD or CCSD(T) make it very attractive for high-accuracy studies.
Anionic water pentamer and hexamer clusters: An extensive study of structures and energetics.
Ünal, Aslı; Bozkaya, Uğur
2018-03-28
An extensive study of structures and energetics for anionic pentamer and hexamer clusters is performed employing high level ab initio quantum chemical methods, such as the density-fitted orbital-optimized linearized coupled-cluster doubles (DF-OLCCD), coupled-cluster singles and doubles (CCSD), and coupled-cluster singles and doubles with perturbative triples [CCSD(T)] methods. In this study, sixteen anionic pentamer clusters and eighteen anionic hexamer clusters are reported. Relative, binding, and vertical detachment energies (VDE) are presented at the complete basis set limit (CBS), extrapolating energies of aug4-cc-pVTZ and aug4-cc-pVQZ custom basis sets. The largest VDE values obtained at the CCSD(T)/CBS level are 9.9 and 11.2 kcal mol -1 for pentamers and hexamers, respectively, which are in very good agreement with the experimental values of 9.5 and 11.1 kcal mol -1 . Our binding energy results, at the CCSD(T)/CBS level, indicate strong bindings in anionic clusters due to hydrogen bond interactions. The average binding energy per water molecules is -5.0 and -5.3 kcal mol -1 for pentamers and hexamers, respectively. Furthermore, our results demonstrate that the DF-OLCCD method approaches to the CCSD(T) quality for anionic clusters. The inexpensive analytic gradients of DF-OLCCD compared to CCSD or CCSD(T) make it very attractive for high-accuracy studies.
Experimental observation of chimera and cluster states in a minimal globally coupled network
NASA Astrophysics Data System (ADS)
Hart, Joseph D.; Bansal, Kanika; Murphy, Thomas E.; Roy, Rajarshi
2016-09-01
A "chimera state" is a dynamical pattern that occurs in a network of coupled identical oscillators when the symmetry of the oscillator population is broken into synchronous and asynchronous parts. We report the experimental observation of chimera and cluster states in a network of four globally coupled chaotic opto-electronic oscillators. This is the minimal network that can support chimera states, and our study provides new insight into the fundamental mechanisms underlying their formation. We use a unified approach to determine the stability of all the observed partially synchronous patterns, highlighting the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization. Our approach is general in terms of network size and connectivity. We also find that chimera states often appear in regions of multistability between global, cluster, and desynchronized states.
Cluster dynamics of pulse coupled oscillators
NASA Astrophysics Data System (ADS)
O'Keeffe, Kevin; Strogatz, Steven; Krapivsky, Paul
2015-03-01
We study the dynamics of networks of pulse coupled oscillators. Much attention has been devoted to the ultimate fate of the system: which conditions lead to a steady state in which all the oscillators are firing synchronously. But little is known about how synchrony builds up from an initially incoherent state. The current work addresses this question. Oscillators start to synchronize by forming clusters of different sizes that fire in unison. First pairs of oscillators, then triplets and so on. These clusters progressively grow by coalescing with others, eventually resulting in the fully synchronized state. We study the mean field model in which the coupling between oscillators is all to all. We use probabilistic arguments to derive a recursive set of evolution equations for these clusters. Using a generating function formalism, we derive simple equations for the moments of these clusters. Our results are in good agreement simulation. We then numerically explore the effects of non-trivial connectivity. Our results have potential application to ultra-low power ``impulse radio'' & sensor networks.
Intelligent automated control of life support systems using proportional representations.
Wu, Annie S; Garibay, Ivan I
2004-06-01
Effective automatic control of Advanced Life Support Systems (ALSS) is a crucial component of space exploration. An ALSS is a coupled dynamical system which can be extremely sensitive and difficult to predict. As a result, such systems can be difficult to control using deliberative and deterministic methods. We investigate the performance of two machine learning algorithms, a genetic algorithm (GA) and a stochastic hill-climber (SH), on the problem of learning how to control an ALSS, and compare the impact of two different types of problem representations on the performance of both algorithms. We perform experiments on three ALSS optimization problems using five strategies with multiple variations of a proportional representation for a total of 120 experiments. Results indicate that although a proportional representation can effectively boost GA performance, it does not necessarily have the same effect on other algorithms such as SH. Results also support previous conclusions that multivector control strategies are an effective method for control of coupled dynamical systems.
Unified method of knowledge representation in the evolutionary artificial intelligence systems
NASA Astrophysics Data System (ADS)
Bykov, Nickolay M.; Bykova, Katherina N.
2003-03-01
The evolution of artificial intelligence systems called by complicating of their operation topics and science perfecting has resulted in a diversification of the methods both the algorithms of knowledge representation and usage in these systems. Often by this reason it is very difficult to design the effective methods of knowledge discovering and operation for such systems. In the given activity the authors offer a method of unitized representation of the systems knowledge about objects of an external world by rank transformation of their descriptions, made in the different features spaces: deterministic, probabilistic, fuzzy and other. The proof of a sufficiency of the information about the rank configuration of the object states in the features space for decision making is presented. It is shown that the geometrical and combinatorial model of the rank configurations set introduce their by group of some system of incidence, that allows to store the information on them in a convolute kind. The method of the rank configuration description by the DRP - code (distance rank preserving code) is offered. The problems of its completeness, information capacity, noise immunity and privacy are reviewed. It is shown, that the capacity of a transmission channel for such submission of the information is more than unit, as the code words contain the information both about the object states, and about the distance ranks between them. The effective algorithm of the data clustering for the object states identification, founded on the given code usage, is described. The knowledge representation with the help of the rank configurations allows to unitize and to simplify algorithms of the decision making by fulfillment of logic operations above the DRP - code words. Examples of the proposed clustering techniques operation on the given samples set, the rank configuration of resulted clusters and its DRP-codes are presented.
Saha, Abhijoy; Banerjee, Sayantan; Kurtek, Sebastian; Narang, Shivali; Lee, Joonsang; Rao, Ganesh; Martinez, Juan; Bharath, Karthik; Rao, Arvind U K; Baladandayuthapani, Veerabhadran
2016-01-01
Tumor heterogeneity is a crucial area of cancer research wherein inter- and intra-tumor differences are investigated to assess and monitor disease development and progression, especially in cancer. The proliferation of imaging and linked genomic data has enabled us to evaluate tumor heterogeneity on multiple levels. In this work, we examine magnetic resonance imaging (MRI) in patients with brain cancer to assess image-based tumor heterogeneity. Standard approaches to this problem use scalar summary measures (e.g., intensity-based histogram statistics) that do not adequately capture the complete and finer scale information in the voxel-level data. In this paper, we introduce a novel technique, DEMARCATE (DEnsity-based MAgnetic Resonance image Clustering for Assessing Tumor hEterogeneity) to explore the entire tumor heterogeneity density profiles (THDPs) obtained from the full tumor voxel space. THDPs are smoothed representations of the probability density function of the tumor images. We develop tools for analyzing such objects under the Fisher-Rao Riemannian framework that allows us to construct metrics for THDP comparisons across patients, which can be used in conjunction with standard clustering approaches. Our analyses of The Cancer Genome Atlas (TCGA) based Glioblastoma dataset reveal two significant clusters of patients with marked differences in tumor morphology, genomic characteristics and prognostic clinical outcomes. In addition, we see enrichment of image-based clusters with known molecular subtypes of glioblastoma multiforme, which further validates our representation of tumor heterogeneity and subsequent clustering techniques.
Stark, A; Meiner, Z; Lefkovitz, R; Levin, N
2012-04-01
Motor dysfunction and recovery following stroke and rehabilitation are associated with primary motor cortex plasticity. To better track these effects we studied two patients with sub-acute sub-cortical stroke causing hemiparesis, who underwent an effective behavioral treatment termed Constraint Induced Movement Therapy (CIMT). The therapy involves 2 weeks of intensive motor training of the hemiparetic limb coupled with immobilization of the unaffected limb. The study included a longitudinal series of clinical evaluations and fMRI scans, before and after the treatment. The fMRI task included wrist, elbow, or ankle movements. Activity in the M1 upper-limb region of control subjects was stable, strictly contralateral, and similar in amplitude for elbow and wrist movements. These findings reflect the well-known contralateral motor control and support the idea of overlapping representations of adjacent joints in M1. In both patients, pre-CIMT activation patterns in M1 were tested twice and did not change significantly, were contralateral, and included elbow-wrist differences. Following CIMT, the clinical condition of both patients improved and three fMRI-explored prototypes were found: First, cluster position remained constant; Second, ipsilateral activity appeared in the unaffected hemispheres during hemiparetic movements; Third, patient-specific elbow-wrist inter and intra hemispheric differences were modified. All effects were long-lasting. We suggest that overlapping representations of adjacent joints contributed to the cortical plasticity observed following CIMT. Our findings should be confirmed by studying larger groups of homogeneous patients. Nevertheless, this study introduces multi-joint imaging studies and shows that it is both possible and valuable to carry it out in stroke patients.
Learning Compact Binary Face Descriptor for Face Recognition.
Lu, Jiwen; Liong, Venice Erin; Zhou, Xiuzhuang; Zhou, Jie
2015-10-01
Binary feature descriptors such as local binary patterns (LBP) and its variations have been widely used in many face recognition systems due to their excellent robustness and strong discriminative power. However, most existing binary face descriptors are hand-crafted, which require strong prior knowledge to engineer them by hand. In this paper, we propose a compact binary face descriptor (CBFD) feature learning method for face representation and recognition. Given each face image, we first extract pixel difference vectors (PDVs) in local patches by computing the difference between each pixel and its neighboring pixels. Then, we learn a feature mapping to project these pixel difference vectors into low-dimensional binary vectors in an unsupervised manner, where 1) the variance of all binary codes in the training set is maximized, 2) the loss between the original real-valued codes and the learned binary codes is minimized, and 3) binary codes evenly distribute at each learned bin, so that the redundancy information in PDVs is removed and compact binary codes are obtained. Lastly, we cluster and pool these binary codes into a histogram feature as the final representation for each face image. Moreover, we propose a coupled CBFD (C-CBFD) method by reducing the modality gap of heterogeneous faces at the feature level to make our method applicable to heterogeneous face recognition. Extensive experimental results on five widely used face datasets show that our methods outperform state-of-the-art face descriptors.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brabec, Jiri; Banik, Subrata; Kowalski, Karol
2016-10-28
The implementation details of the universal state-selective (USS) multi-reference coupled cluster (MRCC) formalism with singles and doubles (USS(2)) are discussed on the example of several benchmark systems. We demonstrate that the USS(2) formalism is capable of improving accuracies of state specific multi-reference coupled-cluster (MRCC) methods based on the Brillouin-Wigner and Mukherjee’s sufficiency conditions. Additionally, it is shown that the USS(2) approach significantly alleviates problems associated with the lack of invariance of MRCC theories upon the rotation of active orbitals. We also discuss the perturbative USS(2) formulations that significantly reduce numerical overhead of the full USS(2) method.
Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics
NASA Astrophysics Data System (ADS)
Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.
2018-02-01
Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.
Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics.
Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L
2018-02-07
Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.
Constraining composite Higgs models using LHC data
NASA Astrophysics Data System (ADS)
Banerjee, Avik; Bhattacharyya, Gautam; Kumar, Nilanjana; Ray, Tirtha Sankar
2018-03-01
We systematically study the modifications in the couplings of the Higgs boson, when identified as a pseudo Nambu-Goldstone boson of a strong sector, in the light of LHC Run 1 and Run 2 data. For the minimal coset SO(5)/SO(4) of the strong sector, we focus on scenarios where the standard model left- and right-handed fermions (specifically, the top and bottom quarks) are either in 5 or in the symmetric 14 representation of SO(5). Going beyond the minimal 5 L - 5 R representation, to what we call here the `extended' models, we observe that it is possible to construct more than one invariant in the Yukawa sector. In such models, the Yukawa couplings of the 125 GeV Higgs boson undergo nontrivial modifications. The pattern of such modifications can be encoded in a generic phenomenological Lagrangian which applies to a wide class of such models. We show that the presence of more than one Yukawa invariant allows the gauge and Yukawa coupling modifiers to be decorrelated in the `extended' models, and this decorrelation leads to a relaxation of the bound on the compositeness scale ( f ≥ 640 GeV at 95% CL, as compared to f ≥ 1 TeV for the minimal 5 L - 5 R representation model). We also study the Yukawa coupling modifications in the context of the next-to-minimal strong sector coset SO(6)/SO(5) for fermion-embedding up to representations of dimension 20. While quantifying our observations, we have performed a detailed χ 2 fit using the ATLAS and CMS combined Run 1 and available Run 2 data.
Coupled multipolar interactions in small-particle metallic clusters.
Pustovit, Vitaly N; Sotelo, Juan A; Niklasson, Gunnar A
2002-03-01
We propose a new formalism for computing the optical properties of small clusters of particles. It is a generalization of the coupled dipole-dipole particle-interaction model and allows one in principle to take into account all multipolar interactions in the long-wavelength limit. The method is illustrated by computations of the optical properties of N = 6 particle clusters for different multipolar approximations. We examine the effect of separation between particles and compare the optical spectra with the discrete-dipole approximation and the generalized Mie theory.
Symmetry, Hopf bifurcation, and the emergence of cluster solutions in time delayed neural networks.
Wang, Zhen; Campbell, Sue Ann
2017-11-01
We consider the networks of N identical oscillators with time delayed, global circulant coupling, modeled by a system of delay differential equations with Z N symmetry. We first study the existence of Hopf bifurcations induced by the coupling time delay and then use symmetric Hopf bifurcation theory to determine how these bifurcations lead to different patterns of symmetric cluster oscillations. We apply our results to a case study: a network of FitzHugh-Nagumo neurons with diffusive coupling. For this model, we derive the asymptotic stability, global asymptotic stability, absolute instability, and stability switches of the equilibrium point in the plane of coupling time delay (τ) and excitability parameter (a). We investigate the patterns of cluster oscillations induced by the time delay and determine the direction and stability of the bifurcating periodic orbits by employing the multiple timescales method and normal form theory. We find that in the region where stability switching occurs, the dynamics of the system can be switched from the equilibrium point to any symmetric cluster oscillation, and back to equilibrium point as the time delay is increased.
NASA Astrophysics Data System (ADS)
Cheng, Lan; Wang, Fan; Stanton, John F.; Gauss, Jürgen
2018-01-01
A scheme is reported for the perturbative calculation of spin-orbit coupling (SOC) within the spin-free exact two-component theory in its one-electron variant (SFX2C-1e) in combination with the equation-of-motion coupled-cluster singles and doubles method. Benchmark calculations of the spin-orbit splittings in 2Π and 2P radicals show that the accurate inclusion of scalar-relativistic effects using the SFX2C-1e scheme extends the applicability of the perturbative treatment of SOC to molecules that contain heavy elements. The contributions from relaxation of the coupled-cluster amplitudes are shown to be relatively small; significant contributions from correlating the inner-core orbitals are observed in calculations involving third-row and heavier elements. The calculation of term energies for the low-lying electronic states of the PtH radical, which serves to exemplify heavy transition-metal containing systems, further demonstrates the quality that can be achieved with the pragmatic approach presented here.
Strategies to reduce the complexity of hydrologic data assimilation for high-dimensional models
NASA Astrophysics Data System (ADS)
Hernandez, F.; Liang, X.
2017-12-01
Probabilistic forecasts in the geosciences offer invaluable information by allowing to estimate the uncertainty of predicted conditions (including threats like floods and droughts). However, while forecast systems based on modern data assimilation algorithms are capable of producing multi-variate probability distributions of future conditions, the computational resources required to fully characterize the dependencies between the model's state variables render their applicability impractical for high-resolution cases. This occurs because of the quadratic space complexity of storing the covariance matrices that encode these dependencies and the cubic time complexity of performing inference operations with them. In this work we introduce two complementary strategies to reduce the size of the covariance matrices that are at the heart of Bayesian assimilation methods—like some variants of (ensemble) Kalman filters and of particle filters—and variational methods. The first strategy involves the optimized grouping of state variables by clustering individual cells of the model into "super-cells." A dynamic fuzzy clustering approach is used to take into account the states (e.g., soil moisture) and forcings (e.g., precipitation) of each cell at each time step. The second strategy consists in finding a compressed representation of the covariance matrix that still encodes the most relevant information but that can be more efficiently stored and processed. A learning and a belief-propagation inference algorithm are developed to take advantage of this modified low-rank representation. The two proposed strategies are incorporated into OPTIMISTS, a state-of-the-art hybrid Bayesian/variational data assimilation algorithm, and comparative streamflow forecasting tests are performed using two watersheds modeled with the Distributed Hydrology Soil Vegetation Model (DHSVM). Contrasts are made between the efficiency gains and forecast accuracy losses of each strategy used in isolation, and of those achieved through their coupling. We expect these developments to help catalyze improvements in the predictive accuracy of large-scale forecasting operations by lowering the costs of deploying advanced data assimilation techniques.
Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol
2007-11-27
A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries.
Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol
2007-01-01
Background A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Results Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Conclusion Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries. PMID:18047705
Chimeras and clusters in networks of hyperbolic chaotic oscillators
NASA Astrophysics Data System (ADS)
Cano, A. V.; Cosenza, M. G.
2017-03-01
We show that chimera states, where differentiated subsets of synchronized and desynchronized dynamical elements coexist, can emerge in networks of hyperbolic chaotic oscillators subject to global interactions. As local dynamics we employ Lozi maps, which possess hyperbolic chaotic attractors. We consider a globally coupled system of these maps and use two statistical quantities to describe its collective behavior: the average fraction of elements belonging to clusters and the average standard deviation of state variables. Chimera states, clusters, complete synchronization, and incoherence are thus characterized on the space of parameters of the system. We find that chimera states are related to the formation of clusters in the system. In addition, we show that chimera states arise for a sufficiently long range of interactions in nonlocally coupled networks of these maps. Our results reveal that, under some circumstances, hyperbolicity does not impede the formation of chimera states in networks of coupled chaotic systems, as it had been previously hypothesized.
Experimental observation of chimera and cluster states in a minimal globally coupled network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hart, Joseph D.; Department of Physics, University of Maryland, College Park, Maryland 20742; Bansal, Kanika
A “chimera state” is a dynamical pattern that occurs in a network of coupled identical oscillators when the symmetry of the oscillator population is broken into synchronous and asynchronous parts. We report the experimental observation of chimera and cluster states in a network of four globally coupled chaotic opto-electronic oscillators. This is the minimal network that can support chimera states, and our study provides new insight into the fundamental mechanisms underlying their formation. We use a unified approach to determine the stability of all the observed partially synchronous patterns, highlighting the close relationship between chimera and cluster states as belongingmore » to the broader phenomenon of partial synchronization. Our approach is general in terms of network size and connectivity. We also find that chimera states often appear in regions of multistability between global, cluster, and desynchronized states.« less
Organizing Books and Authors by Multilayer SOM.
Zhang, Haijun; Chow, Tommy W S; Wu, Q M Jonathan
2016-12-01
This paper introduces a new framework for the organization of electronic books (e-books) and their corresponding authors using a multilayer self-organizing map (MLSOM). An author is modeled by a rich tree-structured representation, and an MLSOM-based system is used as an efficient solution to the organizational problem of structured data. The tree-structured representation formulates author features in a hierarchy of author biography, books, pages, and paragraphs. To efficiently tackle the tree-structured representation, we used an MLSOM algorithm that serves as a clustering technique to handle e-books and their corresponding authors. A book and author recommender system is then implemented using the proposed framework. The effectiveness of our approach was examined in a large-scale data set containing 3868 authors along with the 10500 e-books that they wrote. We also provided visualization results of MLSOM for revealing the relevance patterns hidden from presented author clusters. The experimental results corroborate that the proposed method outperforms other content-based models (e.g., rate adapting poisson, latent Dirichlet allocation, probabilistic latent semantic indexing, and so on) and offers a promising solution to book recommendation, author recommendation, and visualization.
Palii, Andrei V; Reu, Oleg S; Ostrovsky, Sergei M; Klokishner, Sophia I; Tsukerblat, Boris S; Hilfiger, Matthew; Shatruk, Michael; Prosvirin, Andrey; Dunbar, Kim R
2009-06-25
This article is a part of our efforts to control the magnetic anisotropy in cyanide-based exchange-coupled systems with the eventual goal to obtain single-molecule magnets with higher blocking temperatures. We give the theoretical interpretation of the magnetic properties of the new pentanuclear complex {[Ni(II)(tmphen)(2)](3)[Os(III)(CN)(6)](2)} x 6 CH(3)CN (Ni(II)(3)Os(III)(2) cluster). Because the system contains the heavy Os(III) ions, spin-orbit coupling considerably exceeds the contributions from the low-symmetry crystal field and exchange coupling. The magnetic properties of the Ni(II)(3)Os(III)(2) cluster are described in the framework of a highly anisotropic pseudo-spin Hamiltonian that corresponds to the limit of strong spin-orbital coupling and takes into account the complex molecular structure. The model provides a good fit to the experimental data and allows the conclusion that the trigonal axis of the bipyramidal Ni(II)(3)Os(III)(2) cluster is a hard axis of magnetization. This explains the fact that in contrast with the isostructural trigonal bipyramidal Mn(III)(2)Mn(II)(3) cluster, the Ni(II)(3)Os(III)(2) system does not exhibit the single-molecule magnetic behavior.
Synchronization between two coupled direct current glow discharge plasma sources
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chaubey, Neeraj; Mukherjee, S.; Sen, A.
2015-02-15
Experimental results on the nonlinear dynamics of two coupled glow discharge plasma sources are presented. A variety of nonlinear phenomena including frequency synchronization and frequency pulling are observed as the coupling strength is varied. Numerical solutions of a model representation of the experiment consisting of two coupled asymmetric Van der Pol type equations are found to be in good agreement with the observed results.
Systematization of actinides using cluster analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kopyrin, A.A.; Terent`eva, T.N.; Khramov, N.N.
1994-11-01
A representation of the actinides in multidimensional property space is proposed for systematization of these elements using cluster analysis. Literature data for their atomic properties are used. Owing to the wide variation of published ionization potentials, medians are used to estimate them. Vertical dendograms are used for classification on the basis of distances between the actinides in atomic-property space. The properties of actinium and lawrencium are furthest removed from the main group. Thorium and mendelevium exhibit individualized properties. A cluster based on the einsteinium-fermium pair is joined by californium.
The quantum dynamics of electronically nonadiabatic chemical reactions
NASA Technical Reports Server (NTRS)
Truhlar, Donald G.
1993-01-01
Considerable progress was achieved on the quantum mechanical treatment of electronically nonadiabatic collisions involving energy transfer and chemical reaction in the collision of an electronically excited atom with a molecule. In the first step, a new diabatic representation for the coupled potential energy surfaces was created. A two-state diabatic representation was developed which was designed to realistically reproduce the two lowest adiabatic states of the valence bond model and also to have the following three desirable features: (1) it is more economical to evaluate; (2) it is more portable; and (3) all spline fits are replaced by analytic functions. The new representation consists of a set of two coupled diabatic potential energy surfaces plus a coupling surface. It is suitable for dynamics calculations on both the electronic quenching and reaction processes in collisions of Na(3p2p) with H2. The new two-state representation was obtained by a three-step process from a modified eight-state diatomics-in-molecules (DIM) representation of Blais. The second step required the development of new dynamical methods. A formalism was developed for treating reactions with very general basis functions including electronically excited states. Our formalism is based on the generalized Newton, scattered wave, and outgoing wave variational principles that were used previously for reactive collisions on a single potential energy surface, and it incorporates three new features: (1) the basis functions include electronic degrees of freedom, as required to treat reactions involving electronic excitation and two or more coupled potential energy surfaces; (2) the primitive electronic basis is assumed to be diabatic, and it is not assumed that it diagonalizes the electronic Hamiltonian even asymptotically; and (3) contracted basis functions for vibrational-rotational-orbital degrees of freedom are included in a very general way, similar to previous prescriptions for locally adiabatic functions in various quantum scattering algorithms.
Unification with vector-like fermions and signals at LHC
NASA Astrophysics Data System (ADS)
Bhattacherjee, Biplob; Byakti, Pritibhajan; Kushwaha, Ashwani; Vempati, Sudhir K.
2018-05-01
We look for minimal extensions of Standard Model with vector like fermions leading to precision unification of gauge couplings. Constraints from proton decay, Higgs stability and perturbativity are considered. The simplest models contain several copies of vector fermions in two different (incomplete) representations. Some of these models encompass Type III seesaw mechanism for neutrino masses whereas some others have a dark matter candidate. In all the models, at least one of the candidates has non-trivial representation under SU(3)color. In the limit of vanishing Yukawa couplings, new QCD bound states are formed, which can be probed at LHC. The present limits based on results from 13 TeV already probe these particles for masses around a TeV. Similar models can be constructed with three or four vector representations, examples of which are presented.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morozov, Vitaly A.; Petrova, Marina V.; Lukzen, Nikita N., E-mail: luk@tomo.nsc.ru
2015-08-15
Family of “breathing crystals” is the polymer-chain complexes of Cu(hfac){sub 2} with nitroxides. The polymer chains consist of one-, two- or three-spin clusters. The “breathing crystals” experience simultaneous magnetic and Jahn-Teller type structural phase transitions with change of total cluster spin and drastic change of bond lengths (ca. 10-12%). For the first time the intra-cluster magnetic couplings in ”breathing crystals” have been calculated both by band structure methods GGA + U and hybrid DFT (B3LYP and PBE0) for the isolated exchange clusters. The temperature dependence of the magnetic coupling constant was calculated for two polymer-chain compounds of the “breathing crystal”more » family - C{sub 21}H{sub 19}CuF{sub 12}N{sub 4}O{sub 6} with the chains containing two-spin clusters and C{sub 22}H{sub 21}CuF{sub 12}N{sub 4}O{sub 6} with the chains of alternating three-spin clusters and one-spin sites. It was found that adding a Hubbard-like parameter not only to the copper 3d electrons but also to the oxygen 2p electrons (GGA + U{sub d} + U{sub p} approach) results in an improved description of exchange coupling in the “breathing crystal” compounds. At the same time treatment of the isolated clusters by a large basis hybrid DFT with high computational cost provides a similar quality fit of the experimental magneto-chemical data as that for the GGA + U{sub d} + U{sub p} band structure calculation scheme. Our calculations also showed that in spite of the abrupt transformation of the magnetic coupling constant under the phase transition, the band gap in the “breathing crystals” remains about the same value with temperature decrease.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Egashira, Kazuhiro, E-mail: egashira@clusterlab.jp; Yamada, Yurika; Kita, Yukiumi
2015-02-07
The magnetic coupling of the chromium dimer cation, Cr{sub 2}{sup +}, has been an outstanding problem for decades. An optical absorption spectrum of Cr{sub 2}{sup +} has been obtained by photodissociation spectroscopy in the photon-energy range from 2.0 to 5.0 eV. Besides, calculations have been performed by the equation-of-motion coupled-cluster singles and doubles method for vertical excitation of the species. Their coincidence supports our assignment that the ground electronic state exhibits a ferromagnetic spin coupling, which is contrary to those of neutral and negatively charged dimers, Cr{sub 2} and Cr{sub 2}{sup −}, in their lowest spin states.
Geometrical interpretation for the outer SU(3) outer multiplicity label
NASA Technical Reports Server (NTRS)
Draayer, Jerry P.; Troltenier, D.
1995-01-01
A geometrical interpretation for the outer multiplicity rho that occurs in a reduction of the product of two SU(3) representations, (lambda(sub pi), mu(sub pi)) x (lambda(sub nu), mu(sub nu)) approaches sigma(sub rho)(lambda, mu)(sub rho), is introduced. This coupling of proton (pi) and neutron (nu) representations arises, for example, in both boson and fermion descriptions of heavy deformed nuclei. Attributing a geometry to the coupling raises the possibility of introducing a simple interaction that provides a physically meaningful way for distinguishing multiple occurrences of (lambda, mu) values that can arise in such products.
NASA Technical Reports Server (NTRS)
Lee, Timothy J.; Langhoff, Stephen R. (Technical Monitor)
1997-01-01
Recent work on the development of single-reference perturbation theories for the study of excited electronic states will be discussed. The utility of these methods will be demonstrated by comparison to linear-response coupled-cluster excitation energies. Results for some halogen molecules of interest in stratospheric chemistry will be presented.
Multifrequency multi-qubit entanglement based on plasmonic hot spots
Ren, Jun; Wu, Tong; Zhang, Xiangdong
2015-01-01
The theoretical method to study strong coupling between an ensemble of quantum emitters (QEs) and surface plasmons excited by the nanoparticle cluster has been presented by using a rigorous first-principles electromagnetic Green’s tensor technique. We have demonstrated that multi-qubit entanglements for two-level QEs can be produced at different coupling resonance frequencies, when they locate in the hot spots of the metallic nanoparticle cluster. The duration of quantum beats for such an entanglement can reach two orders longer than that for the entanglement in a photonic cavity. The phenomenon originates from collective coupling resonance excitation of the cluster. At the frequency of single scattering resonance, the entanglement cannot be produced although the single QE spontaneous decay rate is very big. PMID:26350051
NASA Astrophysics Data System (ADS)
Wang, Yi-Min; Li, Cheng-Zu
2010-01-01
We propose theoretical schemes to generate highly entangled cluster state with superconducting qubits in a circuit QED architecture. Charge qubits are located inside a superconducting transmission line, which serves as a quantum data bus. We show that large clusters state can be efficiently generated in just one step with the long-range Ising-like unitary operators. The quantum operations which are generally realized by two coupling mechanisms: either voltage coupling or current coupling, depend only on global geometric features and are insensitive not only to the thermal state of the transmission line but also to certain random operation errors. Thus high-fidelity one-way quantum computation can be achieved.
Applying the Coupled-Cluster Ansatz to Solids and Surfaces in the Thermodynamic Limit
NASA Astrophysics Data System (ADS)
Gruber, Thomas; Liao, Ke; Tsatsoulis, Theodoros; Hummel, Felix; Grüneis, Andreas
2018-04-01
Modern electronic structure theories can predict and simulate a wealth of phenomena in surface science and solid-state physics. In order to allow for a direct comparison with experiment, such ab initio predictions have to be made in the thermodynamic limit, substantially increasing the computational cost of many-electron wave-function theories. Here, we present a method that achieves thermodynamic limit results for solids and surfaces using the "gold standard" coupled cluster ansatz of quantum chemistry with unprecedented efficiency. We study the energy difference between carbon diamond and graphite crystals, adsorption energies of water on h -BN, as well as the cohesive energy of the Ne solid, demonstrating the increased efficiency and accuracy of coupled cluster theory for solids and surfaces.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rishi, Varun; Perera, Ajith; Bartlett, Rodney J., E-mail: bartlett@qtp.ufl.edu
2016-03-28
Obtaining the correct potential energy curves for the dissociation of multiple bonds is a challenging problem for ab initio methods which are affected by the choice of a spin-restricted reference function. Coupled cluster (CC) methods such as CCSD (coupled cluster singles and doubles model) and CCSD(T) (CCSD + perturbative triples) correctly predict the geometry and properties at equilibrium but the process of bond dissociation, particularly when more than one bond is simultaneously broken, is much more complicated. New modifications of CC theory suggest that the deleterious role of the reference function can be diminished, provided a particular subset of termsmore » is retained in the CC equations. The Distinguishable Cluster (DC) approach of Kats and Manby [J. Chem. Phys. 139, 021102 (2013)], seemingly overcomes the deficiencies for some bond-dissociation problems and might be of use in quasi-degenerate situations in general. DC along with other approximate coupled cluster methods such as ACCD (approximate coupled cluster doubles), ACP-D45, ACP-D14, 2CC, and pCCSD(α, β) (all defined in text) falls under a category of methods that are basically obtained by the deletion of some quadratic terms in the double excitation amplitude equation for CCD/CCSD (coupled cluster doubles model/coupled cluster singles and doubles model). Here these approximate methods, particularly those based on the DC approach, are studied in detail for the nitrogen molecule bond-breaking. The N{sub 2} problem is further addressed with conventional single reference methods but based on spatial symmetry-broken restricted Hartree–Fock (HF) solutions to assess the use of these references for correlated calculations in the situation where CC methods using fully symmetry adapted SCF solutions fail. The distinguishable cluster method is generalized: 1) to different orbitals for different spins (unrestricted HF based DCD and DCSD), 2) by adding triples correction perturbatively (DCSD(T)) and iteratively (DCSDT-n), and 3) via an excited state approximation through the equation of motion (EOM) approach (EOM-DCD, EOM-DCSD). The EOM-CC method is used to identify lower-energy CC solutions to overcome singularities in the CC potential energy curves. It is also shown that UHF based CC and DC methods behave very similarly in bond-breaking of N{sub 2}, and that using spatially broken but spin preserving SCF references makes the CCSD solutions better than those for DCSD.« less
Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.
Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R
2015-12-01
The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.
Hawkins, Amy L; Haskett, Mary E
2014-01-01
Abused children's internal working models (IWM) of relationships are known to relate to their socioemotional adjustment, but mechanisms through which negative representations increase vulnerability to maladjustment have not been explored. We sought to expand the understanding of individual differences in IWM of abused children and investigate the mediating role of self-regulation in links between IWM and adjustment. Cluster analysis was used to subgroup 74 physically abused children based on their IWM. Internal working models were identified by children's representations, as measured by a narrative story stem task. Self-regulation was assessed by teacher report and a behavioral task, and adjustment was measured by teacher report. Cluster analyses indicated two subgroups of abused children with distinct patterns of IWMs. Cluster membership predicted internalizing and externalizing problems. Associations between cluster membership and adjustment were mediated by children's regulation, as measured by teacher reports of many aspects of regulation. There was no support for mediation when regulation was measured by a behavioral task that tapped more narrow facets of regulation. Abused children exhibit clinically relevant individual differences in their IWMs; these models are linked to adjustment in the school setting, possibly through children's self-regulation. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.
Manchaiah, Vinaya; Zhao, Fei; Oladeji, Susan; Ratinaud, Pierre
2018-01-01
Purpose: The current study was aimed at understanding the patterns in the social representation of loud music reported by young adults in different countries. Materials and Methods: The study included a sample of 534 young adults (18–25 years) from India, Iran, Portugal, United Kingdom, and United States. Participants were recruited using a convince sampling, and data were collected using the free association task. Participants were asked to provide up to five words or phrases that come to mind when thinking about “loud music.” The data were first analyzed using the qualitative content analysis. This was followed by quantitative cluster analysis and chi-square analysis. Results: The content analysis suggested 19 main categories of responses related to loud music. The cluster analysis resulted in for main clusters, namely: (1) emotional oriented perception; (2) problem oriented perception; (3) music and enjoyment oriented perception; and (4) positive emotional and recreation-oriented perception. Country of origin was associated with the likelihood of participants being in each of these clusters. Conclusion: The current study highlights the differences and similarities in young adults’ perception of loud music. These results may have implications to hearing health education to facilitate healthy listening habits. PMID:29457602
Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S
2007-05-01
The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.
Towards the use of similarity distances to music genre classification: A comparative study.
Goienetxea, Izaro; Martínez-Otzeta, José María; Sierra, Basilio; Mendialdua, Iñigo
2018-01-01
Music genre classification is a challenging research concept, for which open questions remain regarding classification approach, music piece representation, distances between/within genres, and so on. In this paper an investigation on the classification of generated music pieces is performed, based on the idea that grouping close related known pieces in different sets -or clusters- and then generating in an automatic way a new song which is somehow "inspired" in each set, the new song would be more likely to be classified as belonging to the set which inspired it, based on the same distance used to separate the clusters. Different music pieces representations and distances among pieces are used; obtained results are promising, and indicate the appropriateness of the used approach even in a such a subjective area as music genre classification is.
Nonredundant sparse feature extraction using autoencoders with receptive fields clustering.
Ayinde, Babajide O; Zurada, Jacek M
2017-09-01
This paper proposes new techniques for data representation in the context of deep learning using agglomerative clustering. Existing autoencoder-based data representation techniques tend to produce a number of encoding and decoding receptive fields of layered autoencoders that are duplicative, thereby leading to extraction of similar features, thus resulting in filtering redundancy. We propose a way to address this problem and show that such redundancy can be eliminated. This yields smaller networks and produces unique receptive fields that extract distinct features. It is also shown that autoencoders with nonnegativity constraints on weights are capable of extracting fewer redundant features than conventional sparse autoencoders. The concept is illustrated using conventional sparse autoencoder and nonnegativity-constrained autoencoders with MNIST digits recognition, NORB normalized-uniform object data and Yale face dataset. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mid-course multi-target tracking using continuous representation
NASA Technical Reports Server (NTRS)
Zak, Michail; Toomarian, Nikzad
1991-01-01
The thrust of this paper is to present a new approach to multi-target tracking for the mid-course stage of the Strategic Defense Initiative (SDI). This approach is based upon a continuum representation of a cluster of flying objects. We assume that the velocities of the flying objects can be embedded into a smooth velocity field. This assumption is based upon the impossibility of encounters in a high density cluster between the flying objects. Therefore, the problem is reduced to an identification of a moving continuum based upon consecutive time frame observations. In contradistinction to the previous approaches, here each target is considered as a center of a small continuous neighborhood subjected to a local-affine transformation, and therefore, the target trajectories do not mix. Obviously, their mixture in plane of sensor view is apparent. The approach is illustrated by an example.
Broad phonetic class definition driven by phone confusions
NASA Astrophysics Data System (ADS)
Lopes, Carla; Perdigão, Fernando
2012-12-01
Intermediate representations between the speech signal and phones may be used to improve discrimination among phones that are often confused. These representations are usually found according to broad phonetic classes, which are defined by a phonetician. This article proposes an alternative data-driven method to generate these classes. Phone confusion information from the analysis of the output of a phone recognition system is used to find clusters at high risk of mutual confusion. A metric is defined to compute the distance between phones. The results, using TIMIT data, show that the proposed confusion-driven phone clustering method is an attractive alternative to the approaches based on human knowledge. A hierarchical classification structure to improve phone recognition is also proposed using a discriminative weight training method. Experiments show improvements in phone recognition on the TIMIT database compared to a baseline system.
Gender Divergence in Academics' Representation and Research Productivity: A Nigerian Case Study
ERIC Educational Resources Information Center
Opesade, Adeola Omobola; Famurewa, Kofoworola Folakemi; Igwe, Ebelechukwu Gloria
2017-01-01
Gender equity is increasingly seen as an indicator of development and global acceptance in networks of higher education. Despite this, gender divergence in research productivity of academics coupled with under-representation of women in science has been reported to beset female's scholarly activities. Previous studies provide differing results,…
Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning.
Peng, Yong; Lu, Bao-Liang; Wang, Suhang
2015-05-01
Constructing an informative and discriminative graph plays an important role in various pattern recognition tasks such as clustering and classification. Among the existing graph-based learning models, low-rank representation (LRR) is a very competitive one, which has been extensively employed in spectral clustering and semi-supervised learning (SSL). In SSL, the graph is composed of both labeled and unlabeled samples, where the edge weights are calculated based on the LRR coefficients. However, most of existing LRR related approaches fail to consider the geometrical structure of data, which has been shown beneficial for discriminative tasks. In this paper, we propose an enhanced LRR via sparse manifold adaption, termed manifold low-rank representation (MLRR), to learn low-rank data representation. MLRR can explicitly take the data local manifold structure into consideration, which can be identified by the geometric sparsity idea; specifically, the local tangent space of each data point was sought by solving a sparse representation objective. Therefore, the graph to depict the relationship of data points can be built once the manifold information is obtained. We incorporate a regularizer into LRR to make the learned coefficients preserve the geometric constraints revealed in the data space. As a result, MLRR combines both the global information emphasized by low-rank property and the local information emphasized by the identified manifold structure. Extensive experimental results on semi-supervised classification tasks demonstrate that MLRR is an excellent method in comparison with several state-of-the-art graph construction approaches. Copyright © 2015 Elsevier Ltd. All rights reserved.
Cluster synchronization in networks of neurons with chemical synapses
DOE Office of Scientific and Technical Information (OSTI.GOV)
Juang, Jonq, E-mail: jjuang@math.nctu.edu.tw; Liang, Yu-Hao, E-mail: moonsea.am96g@g2.nctu.edu.tw
2014-03-15
In this work, we study the cluster synchronization of chemically coupled and generally formulated networks which are allowed to be nonidentical. The sufficient condition for the existence of stably synchronous clusters is derived. Specifically, we only need to check the stability of the origins of m decoupled linear systems. Here, m is the number of subpopulations. Examples of nonidentical networks such as Hindmarsh-Rose (HR) neurons with various choices of parameters in different subpopulations, or HR neurons in one subpopulation and FitzHugh-Nagumo neurons in the other subpopulation are provided. Explicit threshold for the coupling strength that guarantees the stably cluster synchronizationmore » can be obtained.« less
Ricard, Guénola; McEwan, Neil R; Dutilh, Bas E; Jouany, Jean-Pierre; Macheboeuf, Didier; Mitsumori, Makoto; McIntosh, Freda M; Michalowski, Tadeusz; Nagamine, Takafumi; Nelson, Nancy; Newbold, Charles J; Nsabimana, Eli; Takenaka, Akio; Thomas, Nadine A; Ushida, Kazunari; Hackstein, Johannes HP; Huynen, Martijn A
2006-01-01
Background The horizontal transfer of expressed genes from Bacteria into Ciliates which live in close contact with each other in the rumen (the foregut of ruminants) was studied using ciliate Expressed Sequence Tags (ESTs). More than 4000 ESTs were sequenced from representatives of the two major groups of rumen Cilates: the order Entodiniomorphida (Entodinium simplex, Entodinium caudatum, Eudiplodinium maggii, Metadinium medium, Diploplastron affine, Polyplastron multivesiculatum and Epidinium ecaudatum) and the order Vestibuliferida, previously called Holotricha (Isotricha prostoma, Isotricha intestinalis and Dasytricha ruminantium). Results A comparison of the sequences with the completely sequenced genomes of Eukaryotes and Prokaryotes, followed by large-scale construction and analysis of phylogenies, identified 148 ciliate genes that specifically cluster with genes from the Bacteria and Archaea. The phylogenetic clustering with bacterial genes, coupled with the absence of close relatives of these genes in the Ciliate Tetrahymena thermophila, indicates that they have been acquired via Horizontal Gene Transfer (HGT) after the colonization of the gut by the rumen Ciliates. Conclusion Among the HGT candidates, we found an over-representation (>75%) of genes involved in metabolism, specifically in the catabolism of complex carbohydrates, a rich food source in the rumen. We propose that the acquisition of these genes has greatly facilitated the Ciliates' colonization of the rumen providing evidence for the role of HGT in the adaptation to new niches. PMID:16472398
Ricard, Guénola; McEwan, Neil R; Dutilh, Bas E; Jouany, Jean-Pierre; Macheboeuf, Didier; Mitsumori, Makoto; McIntosh, Freda M; Michalowski, Tadeusz; Nagamine, Takafumi; Nelson, Nancy; Newbold, Charles J; Nsabimana, Eli; Takenaka, Akio; Thomas, Nadine A; Ushida, Kazunari; Hackstein, Johannes H P; Huynen, Martijn A
2006-02-10
The horizontal transfer of expressed genes from Bacteria into Ciliates which live in close contact with each other in the rumen (the foregut of ruminants) was studied using ciliate Expressed Sequence Tags (ESTs). More than 4000 ESTs were sequenced from representatives of the two major groups of rumen Cilates: the order Entodiniomorphida (Entodinium simplex, Entodinium caudatum, Eudiplodinium maggii, Metadinium medium, Diploplastron affine, Polyplastron multivesiculatum and Epidinium ecaudatum) and the order Vestibuliferida, previously called Holotricha (Isotricha prostoma, Isotricha intestinalis and Dasytricha ruminantium). A comparison of the sequences with the completely sequenced genomes of Eukaryotes and Prokaryotes, followed by large-scale construction and analysis of phylogenies, identified 148 ciliate genes that specifically cluster with genes from the Bacteria and Archaea. The phylogenetic clustering with bacterial genes, coupled with the absence of close relatives of these genes in the Ciliate Tetrahymena thermophila, indicates that they have been acquired via Horizontal Gene Transfer (HGT) after the colonization of the gut by the rumen Ciliates. Among the HGT candidates, we found an over-representation (>75%) of genes involved in metabolism, specifically in the catabolism of complex carbohydrates, a rich food source in the rumen. We propose that the acquisition of these genes has greatly facilitated the Ciliates' colonization of the rumen providing evidence for the role of HGT in the adaptation to new niches.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Degroote, M.; Henderson, T. M.; Zhao, J.
We present a similarity transformation theory based on a polynomial form of a particle-hole pair excitation operator. In the weakly correlated limit, this polynomial becomes an exponential, leading to coupled cluster doubles. In the opposite strongly correlated limit, the polynomial becomes an extended Bessel expansion and yields the projected BCS wavefunction. In between, we interpolate using a single parameter. The e ective Hamiltonian is non-hermitian and this Polynomial Similarity Transformation Theory follows the philosophy of traditional coupled cluster, left projecting the transformed Hamiltonian onto subspaces of the Hilbert space in which the wave function variance is forced to be zero.more » Similarly, the interpolation parameter is obtained through minimizing the next residual in the projective hierarchy. We rationalize and demonstrate how and why coupled cluster doubles is ill suited to the strongly correlated limit whereas the Bessel expansion remains well behaved. The model provides accurate wave functions with energy errors that in its best variant are smaller than 1% across all interaction stengths. The numerical cost is polynomial in system size and the theory can be straightforwardly applied to any realistic Hamiltonian.« less
Autonomous cycling between excitatory and inhibitory coupling in photosensitive chemical oscillators
NASA Astrophysics Data System (ADS)
Yengi, Desmond; Tinsley, Mark R.; Showalter, Kenneth
2018-04-01
Photochemically coupled Belousov-Zhabotinsky micro-oscillators are studied in experiments and simulations. The photosensitive oscillators exhibit excitatory or inhibitory coupling depending on the surrounding reaction mixture composition, which can be systematically varied. In-phase or out-of-phase synchronization is observed with predominantly excitatory or inhibitory coupling, respectively, and complex frequency cycling between excitatory and inhibitory coupling is found between these extremes. The dynamical behavior is characterized in terms of the corresponding phase response curves, and a map representation of the dynamics is presented.
2015-02-04
dislocation dynamics models ( DDD ), continuum representations). Coupling of these models is difficult. Coupling of atomistics and DDD models has been...explored to some extent, but the coupling between DDD and continuum models of the evolution of large populations of dislocations is essentially unexplored
Toda Systems, Cluster Characters, and Spectral Networks
NASA Astrophysics Data System (ADS)
Williams, Harold
2016-11-01
We show that the Hamiltonians of the open relativistic Toda system are elements of the generic basis of a cluster algebra, and in particular are cluster characters of nonrigid representations of a quiver with potential. Using cluster coordinates defined via spectral networks, we identify the phase space of this system with the wild character variety related to the periodic nonrelativistic Toda system by the wild nonabelian Hodge correspondence. We show that this identification takes the relativistic Toda Hamiltonians to traces of holonomies around a simple closed curve. In particular, this provides nontrivial examples of cluster coordinates on SL n -character varieties for n > 2 where canonical functions associated to simple closed curves can be computed in terms of quivers with potential, extending known results in the SL 2 case.
Zaporozhets, Irina A.; Ivanov, Vladimir V.; Lyakh, Dmitry I.; ...
2015-07-13
The earlier proposed multi-reference state-specific coupled-cluster theory with the complete active space reference suffered from a problem of energy discontinuities when the formal reference state was changing in the calculation of the potential energy curve (PEC). A simple remedy to the discontinuity problem is found and is presented in this work. It involves using natural complete active space self-consistent field active orbitals in the complete active space coupled-cluster calculations. As a result, the approach gives smooth PECs for different types of dissociation problems, as illustrated in the calculations of the dissociation of the single bond in the hydrogen fluorine moleculemore » and of the symmetric double-bond dissociation in the water molecule.« less
Disease clusters, exact distributions of maxima, and P-values.
Grimson, R C
1993-10-01
This paper presents combinatorial (exact) methods that are useful in the analysis of disease cluster data obtained from small environments, such as buildings and neighbourhoods. Maxwell-Boltzmann and Fermi-Dirac occupancy models are compared in terms of appropriateness of representation of disease incidence patterns (space and/or time) in these environments. The methods are illustrated by a statistical analysis of the incidence pattern of bone fractures in a setting wherein fracture clustering was alleged to be occurring. One of the methodological results derived in this paper is the exact distribution of the maximum cell frequency in occupancy models.
Logo image clustering based on advanced statistics
NASA Astrophysics Data System (ADS)
Wei, Yi; Kamel, Mohamed; He, Yiwei
2007-11-01
In recent years, there has been a growing interest in the research of image content description techniques. Among those, image clustering is one of the most frequently discussed topics. Similar to image recognition, image clustering is also a high-level representation technique. However it focuses on the coarse categorization rather than the accurate recognition. Based on wavelet transform (WT) and advanced statistics, the authors propose a novel approach that divides various shaped logo images into groups according to the external boundary of each logo image. Experimental results show that the presented method is accurate, fast and insensitive to defects.
Effect of a chameleon scalar field on the cosmic microwave background
DOE Office of Scientific and Technical Information (OSTI.GOV)
Davis, Anne-Christine; Schelpe, Camilla A. O.; Shaw, Douglas J.
2009-09-15
We show that a direct coupling between a chameleonlike scalar field and photons can give rise to a modified Sunyaev-Zel'dovich (SZ) effect in the cosmic microwave background (CMB). The coupling induces a mixing between chameleon particles and the CMB photons when they pass through the magnetic field of a galaxy cluster. Both the intensity and the polarization of the radiation are modified. The degree of modification depends strongly on the properties of the galaxy cluster such as magnetic field strength and electron number density. Existing SZ measurements of the Coma cluster enable us to place constraints on the photon-chameleon coupling.more » The constrained conversion probability in the cluster is P{sub Coma}(204 GHz)<6.2x10{sup -5} at 95% confidence, corresponding to an upper bound on the coupling strength of g{sub eff}{sup (cell)}<2.2x10{sup -8} GeV{sup -1} or g{sub eff}{sup (Kolmo)}<(7.2-32.5)x10{sup -10} GeV{sup -1}, depending on the model that is assumed for the cluster magnetic field structure. We predict the radial profile of the chameleonic CMB intensity decrement. We find that the chameleon effect extends farther toward the edges of the cluster than the thermal SZ effect. Thus we might see a discrepancy between the x-ray emission data and the observed SZ intensity decrement. We further predict the expected change to the CMB polarization arising from the existence of a chameleonlike scalar field. These predictions could be verified or constrained by future CMB experiments.« less
Autocorrelation and Regularization of Query-Based Information Retrieval Scores
2008-02-01
of the most general information retrieval models [ Salton , 1968]. By treating a query as a very short document, documents and queries can be rep... Salton , 1971]. In the context of single link hierarchical clustering, Jardine and van Rijsbergen showed that ranking all k clusters and retrieving a...a document about “dogs”, then the system will always miss this document when a user queries “dog”. Salton recognized that a document’s representation
On the dual equivalence of the self-dual and topologically massive /p-form models
NASA Astrophysics Data System (ADS)
Menezes, R.; Nascimento, J. R. S.; Ribeiro, R. F.; Wotzasek, C.
2003-07-01
We study the duality symmetry in p-form models containing a generalized Bq∧Fp+1 term in spacetime manifolds of arbitrary dimensions. The equivalence between the Bq∧Fp+1 self-dual (SDB∧F) and the Bq∧Fp+1 topologically massive (TMB∧F) models is established using a gauge embedding procedure, including the minimal coupling to conserved charged matter current. The minimal coupling adopted for both tensor fields in the self-dual representation is transformed into a non-minimal magnetic like coupling in the topologically massive representation but with the currents swapped. It is known that to establish this equivalence a current-current interaction term is needed to render the matter sector unchanged. We show that both terms arise naturally from the embedding adopted. Comparison with Higgs/Julia-Toulouse duality is established.
NASA Astrophysics Data System (ADS)
Joseph, Dwayne C.; Saha, Bidhan C.
2012-11-01
Charge transfer cross sections are calculated by employing both the quantal and semiclassical ɛ(R) molecular orbital close coupling (MOCC) approximations in the adiabatic representation and compared with other theoretical and experimental results
Signature of nonadiabatic coupling in excited-state vibrational modes.
Soler, Miguel A; Nelson, Tammie; Roitberg, Adrian E; Tretiak, Sergei; Fernandez-Alberti, Sebastian
2014-11-13
Using analytical excited-state gradients, vibrational normal modes have been calculated at the minimum of the electronic excited-state potential energy surfaces for a set of extended conjugated molecules with different coupling between them. Molecular model systems composed of units of polyphenylene ethynylene (PPE), polyphenylenevinylene (PPV), and naphthacene/pentacene (NP) have been considered. In all cases except the NP model, the influence of the nonadiabatic coupling on the excited-state equilibrium normal modes is revealed as a unique highest frequency adiabatic vibrational mode that overlaps with the coupling vector. This feature is removed by using a locally diabatic representation in which the effect of NA interaction is removed. Comparison of the original adiabatic modes with a set of vibrational modes computed in the locally diabatic representation demonstrates that the effect of nonadiabaticity is confined to only a few modes. This suggests that the nonadiabatic character of a molecular system may be detected spectroscopically by identifying these unique state-specific high frequency vibrational modes.
NASA Astrophysics Data System (ADS)
Kori, Hiroshi; Kiss, István Z.; Jain, Swati; Hudson, John L.
2018-04-01
Experiments and supporting theoretical analysis are presented to describe the synchronization patterns that can be observed with a population of globally coupled electrochemical oscillators close to a homoclinic, saddle-loop bifurcation, where the coupling is repulsive in the electrode potential. While attractive coupling generates phase clusters and desynchronized states, repulsive coupling results in synchronized oscillations. The experiments are interpreted with a phenomenological model that captures the waveform of the oscillations (exponential increase) followed by a refractory period. The globally coupled autocatalytic integrate-and-fire model predicts the development of partially synchronized states that occur through attracting heteroclinic cycles between out-of-phase two-cluster states. Similar behavior can be expected in many other systems where the oscillations occur close to a saddle-loop bifurcation, e.g., with Morris-Lecar neurons.
Title: Chimeras in small, globally coupled networks: Experiments and stability analysis
NASA Astrophysics Data System (ADS)
Hart, Joseph D.; Bansal, Kanika; Murphy, Thomas E.; Roy, Rajarshi
Since the initial observation of chimera states, there has been much discussion of the conditions under which these states emerge. The emphasis thus far has mainly been to analyze large networks of coupled oscillators; however, recent studies have begun to focus on the opposite limit: what is the smallest system of coupled oscillators in which chimeras can exist? We experimentally observe chimeras and other partially synchronous patterns in a network of four globally-coupled chaotic opto-electronic oscillators. By examining the equations of motion, we demonstrate that symmetries in the network topology allow a variety of synchronous states to exist, including cluster synchronous states and a chimera state. Using the group theoretical approach recently developed for analyzing cluster synchronization, we show how to derive the variational equations for these synchronous patterns and calculate their linear stability. The stability analysis gives good agreement with our experimental results. Both experiments and simulations suggest that these chimera states often appear in regions of multistability between global, cluster, and desynchronized states.
Han, J; Koutmos, M; Ahmad, S A; Coucouvanis, D
2001-11-05
A general method for the synthesis of high nuclearity Mo/Fe/S clusters is presented and involves the reductive coupling of the (Et(4)N)(2)[(Cl(4)-cat)MoOFeS(2)Cl(2)] (I) and (Et(4)N)(2)[Fe(2)S(2)Cl(4)] (II) clusters. The reaction of I and II with Fe(PR(3))(2)Cl(2) or sodium salts of noncoordinating anions such as NaPF(6) or NaBPh(4) in the presence of PR(3) (R = Et, (n)Pr, or (n)Bu) affords (Cl(4)-cat)(2)Mo(2)Fe(6)S(8)(PR(3))(6) [R = Et (IIIa), (n)Pr (IIIb), (n)Bu (IIIc)], Fe(6)S(6)(PEt(3))(4)Cl(2) (IV) and (PF(6))[Fe(6)S(8)(P(n)Pr(3))(6)] (V) as byproducts. The isolation of (Et(4)N)[Fe(PEt(3))Cl(3)] (VI), NaCl, and SPEt(3) supports a reductive coupling mechanism. Cluster IV and V also have been synthesized by the reductive self-coupling of compound II. The reductive coupling reaction between I and II by PEt(3) and NaPF(6) in a 1:1 ratio produces the (Et(4)N)(2)[(Cl(4)-cat)Mo(L)Fe(3)S(4)Cl(3)] clusters [L = MeCN (VIIa), THF (VIIb)]. The hitherto unknown [(Cl(4)-cat)(2)Mo(2)Fe(2)S(3)O(PEt(3))(3)Cl](+) cluster (VIII) has been isolated as the 2:1 salt of the (Fe(PEt(3))(2)(MeCN)(4))(2+) cation after the reductive self-coupling reaction of I in the presence of Fe(PEt(3))(2)Cl(2). Cluster VIII crystallizes in the monoclinic space group P2(1)/c with a = 11.098(3) A, b = 22.827(6) A, c = 25.855(6) A, beta = 91.680(4) degrees, and Z = 4. The formal oxidation states of metal atoms in VIII have been assigned as Mo(III), Mo(IV), Fe(II), and Fe(III) on the basis of zero-field Mössbauer spectra. The Fe(PEt(3))(2)(MeCN)(4) cation of VIII is also synthesized independently, isolated as the BPh(4)(-) salt (IX), and has been structurally characterized. The reductive coupling of compound I also affords in low yield the new (Cl(4)-cat)(2)Mo(2)Fe(3)S(5)(PEt(3))(5) cluster (X) as a byproduct. Cluster X crystallizes in the monoclinic space group P2(1)/n with a = 14.811(3) A, b = 22.188(4) A, c = 21.864(4) A, beta = 100.124(3) degrees, and Z = 4 and the structure shows very short Mo-Fe, Fe-Fe, Mo-S, Fe-S bonds. The oxidation states of the metal atoms in this neutral cluster (X) have been assigned as Mo(IV)Mo(III)Fe(II)Fe(II)Fe(III) based on zero-field Mössbauer and magnetic measurement. All Fe atoms are high spin and two of the three Fe-Fe distances are found at 2.4683(9) A and 2.4721(9) A.
Sampling designs for HIV molecular epidemiology with application to Honduras.
Shepherd, Bryan E; Rossini, Anthony J; Soto, Ramon Jeremias; De Rivera, Ivette Lorenzana; Mullins, James I
2005-11-01
Proper sampling is essential to characterize the molecular epidemiology of human immunodeficiency virus (HIV). HIV sampling frames are difficult to identify, so most studies use convenience samples. We discuss statistically valid and feasible sampling techniques that overcome some of the potential for bias due to convenience sampling and ensure better representation of the study population. We employ a sampling design called stratified cluster sampling. This first divides the population into geographical and/or social strata. Within each stratum, a population of clusters is chosen from groups, locations, or facilities where HIV-positive individuals might be found. Some clusters are randomly selected within strata and individuals are randomly selected within clusters. Variation and cost help determine the number of clusters and the number of individuals within clusters that are to be sampled. We illustrate the approach through a study designed to survey the heterogeneity of subtype B strains in Honduras.
Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition
Cui, Zhiming; Zhao, Pengpeng
2014-01-01
A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045
Mamme, Mesfin Haile; Köhn, Christoph; Deconinck, Johan; Ustarroz, Jon
2018-04-19
Fundamental understanding of the early stages of electrodeposition at the nanoscale is key to address the challenges in a wide range of applications. Despite having been studied for decades, a comprehensive understanding of the whole process is still out of reach. In this work, we introduce a novel modelling approach that couples a finite element method (FEM) with a random walk algorithm, to study the early stages of nanocluster formation, aggregation and growth, during electrochemical deposition. This approach takes into account not only electrochemical kinetics and transport of active species, but also the surface diffusion and aggregation of adatoms and small nanoclusters. The simulation results reveal that the relative surface mobility of the nanoclusters compared to that of the adatoms plays a crucial role in the early growth stages. The number of clusters, their size and their size dispersion are influenced more significantly by nanocluster mobility than by the applied overpotential itself. Increasing the overpotential results in shorter induction times and leads to aggregation prevalence at shorter times. A higher mobility results in longer induction times, a delayed transition from nucleation to aggregation prevalence, and as a consequence, a larger surface coverage of smaller clusters with a smaller size dispersion. As a consequence, it is shown that a classical first-order nucleation kinetics equation cannot describe the evolution of the number of clusters with time, N(t), in potentiostatic electrodeposition. Instead, a more accurate representation of N(t) is provided. We show that an evaluation of N(t), which neglects the effect of nanocluster mobility and aggregation, can induce errors of several orders of magnitude in the determination of nucleation rate constants. These findings are extremely important towards evaluating the elementary electrodeposition processes, considering not only adatoms, but also nanoclusters as building blocks.
Solution of the sign problem in the Potts model at fixed fermion number
NASA Astrophysics Data System (ADS)
Alexandru, Andrei; Bergner, Georg; Schaich, David; Wenger, Urs
2018-06-01
We consider the heavy-dense limit of QCD at finite fermion density in the canonical formulation and approximate it by a three-state Potts model. In the strong-coupling limit, the model is free of the sign problem. Away from the strong coupling, the sign problem is solved by employing a cluster algorithm which allows to average each cluster over the Z (3 ) sectors. Improved estimators for physical quantities can be constructed by taking into account the triality of the clusters, that is, their transformation properties with respect to Z (3 ) transformations.
Integrable hierarchies of Heisenberg ferromagnet equation
NASA Astrophysics Data System (ADS)
Nugmanova, G.; Azimkhanova, A.
2016-08-01
In this paper we consider the coupled Kadomtsev-Petviashvili system. From compatibility conditions we obtain the form of matrix operators. After using a gauge transformation, obtained a new type of Lax representation for the hierarchy of Heisenberg ferromagnet equation, which is equivalent to the gauge coupled Kadomtsev-Petviashvili system.
Graphical Representations and Cluster Algorithms for Ice Rule Vertex Models.
NASA Astrophysics Data System (ADS)
Shtengel, Kirill; Chayes, L.
2002-03-01
We introduce a new class of polymer models which is closely related to loop models, recently a topic of intensive studies. These particular models arise as graphical representations for ice-rule vertex models. The associated cluster algorithms provide a unification and generalisation of most of the existing algorithms. For many lattices, percolation in the polymer models evidently indicates first order phase transitions in the vertex models. Critical phases can be understood as being susceptible to colour symmetry breaking in the polymer models. The analysis includes, but is certainly not limited to the square lattice six-vertex model. In particular, analytic criteria can be found for low temperature phases in other even coordinated 2D lattices such as the triangular lattice, or higher dimensional lattices such as the hyper-cubic lattices of arbitrary dimensionality. Finally, our approach can be generalised to the vertex models that do not obey the ice rule, such as the eight-vertex model.
New Beginnings for mothers and babies in prison: A cluster randomized controlled trial
Sleed, Michelle; Baradon, Tessa; Fonagy, Peter
2013-01-01
Mothers in prison represent a high-risk parenting population. New Beginnings is an attachment-based group intervention designed specifically for mothers and babies in prison. This cluster randomized trial examined the outcomes for 88 mothers and babies participating in the New Beginnings program and 75 dyads residing in prisons where the intervention did not take place. Outcomes were measured in terms of parental reflective functioning, the quality of parent–infant interaction, maternal depression, and maternal representations. Mothers in the control group deteriorated in their level of reflective functioning and behavioral interaction with their babies over time, whereas the mothers in the intervention group did not. There were no significant group effects on levels of maternal depression or mothers' self-reported representations of their babies over time. An attachment-based intervention may mitigate some of the risks to the quality of the parent–infant relationship for these dyads. PMID:23550526
NASA Astrophysics Data System (ADS)
Wälz, Gero; Kats, Daniel; Usvyat, Denis; Korona, Tatiana; Schütz, Martin
2012-11-01
Linear-response methods, based on the time-dependent variational coupled-cluster or the unitary coupled-cluster model, and truncated at the second order according to the Møller-Plesset partitioning, i.e., the TD-VCC[2] and TD-UCC[2] linear-response methods, are presented and compared. For both of these methods a Hermitian eigenvalue problem has to be solved to obtain excitation energies and state eigenvectors. The excitation energies thus are guaranteed always to be real valued, and the eigenvectors are mutually orthogonal, in contrast to response theories based on “traditional” coupled-cluster models. It turned out that the TD-UCC[2] working equations for excitation energies and polarizabilities are equivalent to those of the second-order algebraic diagrammatic construction scheme ADC(2). Numerical tests are carried out by calculating TD-VCC[2] and TD-UCC[2] excitation energies and frequency-dependent dipole polarizabilities for several test systems and by comparing them to the corresponding values obtained from other second- and higher-order methods. It turns out that the TD-VCC[2] polarizabilities in the frequency regions away from the poles are of a similar accuracy as for other second-order methods, as expected from the perturbative analysis of the TD-VCC[2] polarizability expression. On the other hand, the TD-VCC[2] excitation energies are systematically too low relative to other second-order methods (including TD-UCC[2]). On the basis of these results and an analysis presented in this work, we conjecture that the perturbative expansion of the Jacobian converges more slowly for the TD-VCC formalism than for TD-UCC or for response theories based on traditional coupled-cluster models.
Li, Ping; Ma, Zhiying; Wang, Weihua; Zhai, Yazhou; Sun, Haitao; Bi, Siwei; Bu, Yuxiang
2011-01-21
A detailed knowledge of coupling interactions among sulfuric acid (H(2)SO(4)), the hydroperoxyl radical (HOO˙), and water molecules (H(2)O) is crucial for the better understanding of the uptake of HOO˙ radicals by sulfuric acid aerosols at different atmospheric humidities. In the present study, the equilibrium structures, binding energies, equilibrium distributions, and the nature of the coupling interactions in H(2)SO(4)···HOO˙···(H(2)O)(n) (n = 0-2) clusters have been systematically investigated at the B3LYP/6-311++G(3df,3pd) level of theory in combination with the atoms in molecules (AIM) theory, natural bond orbital (NBO) method, energy decomposition analyses, and ab initio molecular dynamics. Two binary, five ternary, and twelve tetramer clusters possessing multiple intermolecular H-bonds have been located on their potential energy surfaces. Two different modes for water molecules have been observed to influence the coupling interactions between H(2)SO(4) and HOO˙ through the formations of intermolecular H-bonds with or without breaking the original intermolecular H-bonds in the binary H(2)SO(4)···HOO˙ cluster. It was found that the introduction of one or two water molecules can efficiently enhance the interactions between H(2)SO(4) and HOO˙, implying the positive role of water molecules in the uptake of the HOO˙ radical by sulfuric acid aerosols. Additionally, the coupling interaction modes of the most stable clusters under study have been verified by the ab initio molecular dynamics.
Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma.
Young, Jonathan D; Cai, Chunhui; Lu, Xinghua
2017-10-03
One approach to improving the personalized treatment of cancer is to understand the cellular signaling transduction pathways that cause cancer at the level of the individual patient. In this study, we used unsupervised deep learning to learn the hierarchical structure within cancer gene expression data. Deep learning is a group of machine learning algorithms that use multiple layers of hidden units to capture hierarchically related, alternative representations of the input data. We hypothesize that this hierarchical structure learned by deep learning will be related to the cellular signaling system. Robust deep learning model selection identified a network architecture that is biologically plausible. Our model selection results indicated that the 1st hidden layer of our deep learning model should contain about 1300 hidden units to most effectively capture the covariance structure of the input data. This agrees with the estimated number of human transcription factors, which is approximately 1400. This result lends support to our hypothesis that the 1st hidden layer of a deep learning model trained on gene expression data may represent signals related to transcription factor activation. Using the 3rd hidden layer representation of each tumor as learned by our unsupervised deep learning model, we performed consensus clustering on all tumor samples-leading to the discovery of clusters of glioblastoma multiforme with differential survival. One of these clusters contained all of the glioblastoma samples with G-CIMP, a known methylation phenotype driven by the IDH1 mutation and associated with favorable prognosis, suggesting that the hidden units in the 3rd hidden layer representations captured a methylation signal without explicitly using methylation data as input. We also found differentially expressed genes and well-known mutations (NF1, IDH1, EGFR) that were uniquely correlated with each of these clusters. Exploring these unique genes and mutations will allow us to further investigate the disease mechanisms underlying each of these clusters. In summary, we show that a deep learning model can be trained to represent biologically and clinically meaningful abstractions of cancer gene expression data. Understanding what additional relationships these hidden layer abstractions have with the cancer cellular signaling system could have a significant impact on the understanding and treatment of cancer.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Varghese, Jithin J.; Mushrif, Samir H., E-mail: shmushrif@ntu.edu.sg
Small metal clusters exhibit unique size and morphology dependent catalytic activity. The search for alternate minimum energy pathways and catalysts to transform methane to more useful chemicals and carbon nanomaterials led us to investigate collision induced dissociation of methane on small Cu clusters. We report here for the first time, the free energy barriers for the collision induced activation, dissociation, and coupling of methane on small Cu clusters (Cu{sub n} where n = 2–12) using ab initio molecular dynamics and metadynamics simulations. The collision induced activation of the stretching and bending vibrations of methane significantly reduces the free energy barriermore » for its dissociation. Increase in the cluster size reduces the barrier for dissociation of methane due to the corresponding increase in delocalisation of electron density within the cluster, as demonstrated using the electron localisation function topology analysis. This enables higher probability of favourable alignment of the C–H stretching vibration of methane towards regions of high electron density within the cluster and makes higher number of sites available for the chemisorption of CH{sub 3} and H upon dissociation. These characteristics contribute in lowering the barrier for dissociation of methane. Distortion and reorganisation of cluster geometry due to high temperature collision dynamics disturb electron delocalisation within them and increase the barrier for dissociation. Coupling reactions of CH{sub x} (x = 1–3) species and recombination of H with CH{sub x} have free energy barriers significantly lower than complete dehydrogenation of methane to carbon. Thus, competition favours the former reactions at high hydrogen saturation on the clusters.« less
Cluster assembly in nitrogenase.
Sickerman, Nathaniel S; Rettberg, Lee A; Lee, Chi Chung; Hu, Yilin; Ribbe, Markus W
2017-05-09
The versatile enzyme system nitrogenase accomplishes the challenging reduction of N 2 and other substrates through the use of two main metalloclusters. For molybdenum nitrogenase, the catalytic component NifDK contains the [Fe 8 S 7 ]-core P-cluster and a [MoFe 7 S 9 C-homocitrate] cofactor called the M-cluster. These chemically unprecedented metalloclusters play a critical role in the reduction of N 2 , and both originate from [Fe 4 S 4 ] clusters produced by the actions of NifS and NifU. Maturation of P-cluster begins with a pair of these [Fe 4 S 4 ] clusters on NifDK called the P*-cluster. An accessory protein NifZ aids in P-cluster fusion, and reductive coupling is facilitated by NifH in a stepwise manner to form P-cluster on each half of NifDK. For M-cluster biosynthesis, two [Fe 4 S 4 ] clusters on NifB are coupled with a carbon atom in a radical-SAM dependent process, and concomitant addition of a 'ninth' sulfur atom generates the [Fe 8 S 9 C]-core L-cluster. On the scaffold protein NifEN, L-cluster is matured to M-cluster by the addition of Mo and homocitrate provided by NifH. Finally, matured M-cluster in NifEN is directly transferred to NifDK, where a conformational change locks the cofactor in place. Mechanistic insights into these fascinating biosynthetic processes are detailed in this chapter. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.
Pulse-coupled mixed-mode oscillators: Cluster states and extreme noise sensitivity
NASA Astrophysics Data System (ADS)
Karamchandani, Avinash J.; Graham, James N.; Riecke, Hermann
2018-04-01
Motivated by rhythms in the olfactory system of the brain, we investigate the synchronization of all-to-all pulse-coupled neuronal oscillators exhibiting various types of mixed-mode oscillations (MMOs) composed of sub-threshold oscillations (STOs) and action potentials ("spikes"). We focus particularly on the impact of the delay in the interaction. In the weak-coupling regime, we reduce the system to a Kuramoto-type equation with non-sinusoidal phase coupling and the associated Fokker-Planck equation. Its linear stability analysis identifies the appearance of various cluster states. Their type depends sensitively on the delay and the width of the pulses. Interestingly, long delays do not imply slow population rhythms, and the number of emerging clusters only loosely depends on the number of STOs. Direct simulations of the oscillator equations reveal that for quantitative agreement of the weak-coupling theory the coupling strength and the noise have to be extremely small. Even moderate noise leads to significant skipping of STO cycles, which can enhance the diffusion coefficient in the Fokker-Planck equation by two orders of magnitude. Introducing an effective diffusion coefficient extends the range of agreement significantly. Numerical simulations of the Fokker-Planck equation reveal bistability and solutions with oscillatory order parameters that result from nonlinear mode interactions. These are confirmed in simulations of the full spiking model.
NASA Astrophysics Data System (ADS)
Namdar, Bahadir; Shen, Ji
2016-05-01
Using multiple representations and argumentation are two fundamental processes in science. With the advancements of information communication technologies, these two processes are blended more so than ever before. However, little is known about how these two processes interact with each other in student learning. Hence, we conducted a design-based study in order to distill the relationship between these two processes. Specifically, we designed a learning unit on nuclear energy and implemented it with a group of preservice middle school teachers. The participants used a web-based knowledge organization platform that incorporated three representational modes: textual, concept map, and pictorial. The participants organized their knowledge on nuclear energy by searching, sorting, clustering information through the use of these representational modes and argued about the nuclear energy issue. We found that the use of multiple representations and argumentation interacted with each other in a complex way. Based on our findings, we argue that the complexity can be unfolded in two aspects: (a) the use of multiple representations mediates argumentation in different forms and for different purposes; (b) the type of argumentation that leads to refinement of the use of multiple representations is often non-mediated and drawn from personal experience.
Chimera states in nonlocally coupled phase oscillators with biharmonic interaction
NASA Astrophysics Data System (ADS)
Cheng, Hongyan; Dai, Qionglin; Wu, Nianping; Feng, Yuee; Li, Haihong; Yang, Junzhong
2018-03-01
Chimera states, which consist of coexisting domains of coherent and incoherent parts, have been observed in a variety of systems. Most of previous works on chimera states have taken into account specific form of interaction between oscillators, for example, sinusoidal coupling or diffusive coupling. Here, we investigate chimera dynamics in nonlocally coupled phase oscillators with biharmonic interaction. We find novel chimera states with features such as that oscillators in the same coherent cluster may split into two groups with a phase difference around π/2 and that oscillators in adjacent coherent clusters may have a phase difference close to π/2. The different impacts of the coupling ranges in the first and the second harmonic interactions on chimera dynamics are investigated based on the synchronous dynamics in globally coupled phase oscillators. Our study suggests a new direction in the field of chimera dynamics.
Event-based cluster synchronization of coupled genetic regulatory networks
NASA Astrophysics Data System (ADS)
Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang
2017-09-01
In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.
NASA Astrophysics Data System (ADS)
Candela, A.; Brigandì, G.; Aronica, G. T.
2014-07-01
In this paper a procedure to derive synthetic flood design hydrographs (SFDH) using a bivariate representation of rainfall forcing (rainfall duration and intensity) via copulas, which describes and models the correlation between two variables independently of the marginal laws involved, coupled with a distributed rainfall-runoff model, is presented. Rainfall-runoff modelling (R-R modelling) for estimating the hydrological response at the outlet of a catchment was performed by using a conceptual fully distributed procedure based on the Soil Conservation Service - Curve Number method as an excess rainfall model and on a distributed unit hydrograph with climatic dependencies for the flow routing. Travel time computation, based on the distributed unit hydrograph definition, was performed by implementing a procedure based on flow paths, determined from a digital elevation model (DEM) and roughness parameters obtained from distributed geographical information. In order to estimate the primary return period of the SFDH, which provides the probability of occurrence of a hydrograph flood, peaks and flow volumes obtained through R-R modelling were treated statistically using copulas. Finally, the shapes of hydrographs have been generated on the basis of historically significant flood events, via cluster analysis. An application of the procedure described above has been carried out and results presented for the case study of the Imera catchment in Sicily, Italy.
NASA Astrophysics Data System (ADS)
Sahoo, B. K.; Das, B. P.
2018-05-01
Recent relativistic coupled-cluster (RCC) calculations of electric dipole moments (EDMs) of diamagnetic atoms due to parity and time-reversal violating (P ,T -odd) interactions, which are essential ingredients for probing new physics beyond the standard model of particle interactions, differ substantially from the previous theoretical results. It is therefore necessary to perform an independent test of the validity of these results. In view of this, the normal coupled-cluster method has been extended to the relativistic regime [relativistic normal coupled-cluster (RNCC) method] to calculate the EDMs of atoms by simultaneously incorporating the electrostatic and P ,T -odd interactions in order to overcome the shortcomings of the ordinary RCC method. This new relativistic method has been applied to 199Hg, which currently has a lower EDM limit than that of any other system. The results of our RNCC and self-consistent RCC calculations of the EDM of this atom are found to be close. The discrepancies between these two results on the one hand and those of previous calculations on the other are elucidated. Furthermore, the electric dipole polarizability of this atom, which has computational similarities with the EDM, is evaluated and it is in very good agreement with its measured value.
Sahoo, B K; Das, B P
2018-05-18
Recent relativistic coupled-cluster (RCC) calculations of electric dipole moments (EDMs) of diamagnetic atoms due to parity and time-reversal violating (P,T-odd) interactions, which are essential ingredients for probing new physics beyond the standard model of particle interactions, differ substantially from the previous theoretical results. It is therefore necessary to perform an independent test of the validity of these results. In view of this, the normal coupled-cluster method has been extended to the relativistic regime [relativistic normal coupled-cluster (RNCC) method] to calculate the EDMs of atoms by simultaneously incorporating the electrostatic and P,T-odd interactions in order to overcome the shortcomings of the ordinary RCC method. This new relativistic method has been applied to ^{199}Hg, which currently has a lower EDM limit than that of any other system. The results of our RNCC and self-consistent RCC calculations of the EDM of this atom are found to be close. The discrepancies between these two results on the one hand and those of previous calculations on the other are elucidated. Furthermore, the electric dipole polarizability of this atom, which has computational similarities with the EDM, is evaluated and it is in very good agreement with its measured value.
Tecmer, Paweł; Gomes, André Severo Pereira; Knecht, Stefan; Visscher, Lucas
2014-07-28
We present a study of the electronic structure of the [UO2](+), [UO2](2 +), [UO2](3 +), NUO, [NUO](+), [NUO](2 +), [NUN](-), NUN, and [NUN](+) molecules with the intermediate Hamiltonian Fock-space coupled cluster method. The accuracy of mean-field approaches based on the eXact-2-Component Hamiltonian to incorporate spin-orbit coupling and Gaunt interactions are compared to results obtained with the Dirac-Coulomb Hamiltonian. Furthermore, we assess the reliability of calculations employing approximate density functionals in describing electronic spectra and quantities useful in rationalizing Uranium (VI) species reactivity (hardness, electronegativity, and electrophilicity).
NASA Astrophysics Data System (ADS)
Tecmer, Paweł; Severo Pereira Gomes, André; Knecht, Stefan; Visscher, Lucas
2014-07-01
We present a study of the electronic structure of the [UO2]+, [UO2]2 +, [UO2]3 +, NUO, [NUO]+, [NUO]2 +, [NUN]-, NUN, and [NUN]+ molecules with the intermediate Hamiltonian Fock-space coupled cluster method. The accuracy of mean-field approaches based on the eXact-2-Component Hamiltonian to incorporate spin-orbit coupling and Gaunt interactions are compared to results obtained with the Dirac-Coulomb Hamiltonian. Furthermore, we assess the reliability of calculations employing approximate density functionals in describing electronic spectra and quantities useful in rationalizing Uranium (VI) species reactivity (hardness, electronegativity, and electrophilicity).
AIC identifies optimal representation of longitudinal dietary variables.
VanBuren, John; Cavanaugh, Joseph; Marshall, Teresa; Warren, John; Levy, Steven M
2017-09-01
The Akaike Information Criterion (AIC) is a well-known tool for variable selection in multivariable modeling as well as a tool to help identify the optimal representation of explanatory variables. However, it has been discussed infrequently in the dental literature. The purpose of this paper is to demonstrate the use of AIC in determining the optimal representation of dietary variables in a longitudinal dental study. The Iowa Fluoride Study enrolled children at birth and dental examinations were conducted at ages 5, 9, 13, and 17. Decayed or filled surfaces (DFS) trend clusters were created based on age 13 DFS counts and age 13-17 DFS increments. Dietary intake data (water, milk, 100 percent-juice, and sugar sweetened beverages) were collected semiannually using a food frequency questionnaire. Multinomial logistic regression models were fit to predict DFS cluster membership (n=344). Multiple approaches could be used to represent the dietary data including averaging across all collected surveys or over different shorter time periods to capture age-specific trends or using the individual time points of dietary data. AIC helped identify the optimal representation. Averaging data for all four dietary variables for the whole period from age 9.0 to 17.0 provided a better representation in the multivariable full model (AIC=745.0) compared to other methods assessed in full models (AICs=750.6 for age 9 and 9-13 increment dietary measurements and AIC=762.3 for age 9, 13, and 17 individual measurements). The results illustrate that AIC can help researchers identify the optimal way to summarize information for inclusion in a statistical model. The method presented here can be used by researchers performing statistical modeling in dental research. This method provides an alternative approach for assessing the propriety of variable representation to significance-based procedures, which could potentially lead to improved research in the dental community. © 2017 American Association of Public Health Dentistry.
Schneider, Daniel; Barth, Anna; Wascher, Edmund
2017-11-15
Attention can be allocated toward mental representations in working memory also after the initial encoding of information has been completed. It was shown that focusing on only one item within working memory transfers this representation into a protected state, reducing its susceptibility to interference by incoming signals. The present study investigated the nature of this retroactive cue (retro-cue) benefit by means of oscillatory activity in the EEG. In a working memory task with a retro-cue indicating one, two or three memory representations as relevant and a block-wise distractor display presented after the retro-cue, participants had to remember the orientation of a colored bar. On behavioral level, we found that the interfering effect of the distractor display on memory performance could be prevented when a retro-cue reduced the number of attended representations in working memory. However, only the one-item retro-cue led to an overall increase in task performance compared to a condition without a retro-cue. The neural basis of this special representational status was investigated by means of oscillatory parameters in the EEG and a clustering approach on level of the independent components (ICs) in the signal. The retroactive reduction of attended working memory representations was reflected in a suppression of alpha power over right parietal and parieto-occipital sites. In addition, we found that an IC cluster representing oscillatory activity in the mu/beta range (10-12 Hz and 20-24 Hz) with a source in sensorimotor cortex revealed a power suppression already prior to the memory probe following the one-item retro-cue. This suggests that the retro-cue benefit results in large parts from the possibility to focus attention on one particular item in working memory and initiate motor planning processes already ahead of the probe stimulus indicating the respective response. Copyright © 2017 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Souleymanou, Abbagari; Thomas, B. Bouetou; Timoleon, C. Kofane
2013-08-01
The prolongation structure methodologies of Wahlquist—Estabrook [H.D. Wahlquist and F.B. Estabrook, J. Math. Phys. 16 (1975) 1] for nonlinear differential equations are applied to a more general set of coupled integrable dispersionless system. Based on the obtained prolongation structure, a Lie-Algebra valued connection of a closed ideal of exterior differential forms related to the above system is constructed. A Lie-Algebra representation of some hidden structural symmetries of the previous system, its Bäcklund transformation using the Riccati form of the linear eigenvalue problem and their general corresponding Lax-representation are derived. In the wake of the previous results, we extend the above prolongation scheme to higher-dimensional systems from which a new (2 + 1)-dimensional coupled integrable dispersionless system is unveiled along with its inverse scattering formulation, which applications are straightforward in nonlinear optics where additional propagating dimension deserves some attention.
Ligare, Martin
2016-05-01
Multiple-pulse NMR experiments are a powerful tool for the investigation of molecules with coupled nuclear spins. The product operator formalism provides a way to understand the quantum evolution of an ensemble of weakly coupled spins in such experiments using some of the more intuitive concepts of classical physics and semi-classical vector representations. In this paper I present a new way in which to interpret the quantum evolution of an ensemble of spins. I recast the quantum problem in terms of mixtures of pure states of two spins whose expectation values evolve identically to those of classical moments. Pictorial representations of these classically evolving states provide a way to calculate the time evolution of ensembles of weakly coupled spins without the full machinery of quantum mechanics, offering insight to anyone who understands precession of magnetic moments in magnetic fields.
The neural code for face orientation in the human fusiform face area.
Ramírez, Fernando M; Cichy, Radoslaw M; Allefeld, Carsten; Haynes, John-Dylan
2014-09-03
Humans recognize faces and objects with high speed and accuracy regardless of their orientation. Recent studies have proposed that orientation invariance in face recognition involves an intermediate representation where neural responses are similar for mirror-symmetric views. Here, we used fMRI, multivariate pattern analysis, and computational modeling to investigate the neural encoding of faces and vehicles at different rotational angles. Corroborating previous studies, we demonstrate a representation of face orientation in the fusiform face-selective area (FFA). We go beyond these studies by showing that this representation is category-selective and tolerant to retinal translation. Critically, by controlling for low-level confounds, we found the representation of orientation in FFA to be compatible with a linear angle code. Aspects of mirror-symmetric coding cannot be ruled out when FFA mean activity levels are considered as a dimension of coding. Finally, we used a parametric family of computational models, involving a biased sampling of view-tuned neuronal clusters, to compare different face angle encoding models. The best fitting model exhibited a predominance of neuronal clusters tuned to frontal views of faces. In sum, our findings suggest a category-selective and monotonic code of face orientation in the human FFA, in line with primate electrophysiology studies that observed mirror-symmetric tuning of neural responses at higher stages of the visual system, beyond the putative homolog of human FFA. Copyright © 2014 the authors 0270-6474/14/3412155-13$15.00/0.
NASA Astrophysics Data System (ADS)
Pan, Patricia Wang; Dickson, Russell J.; Gordon, Heather L.; Rothstein, Stuart M.; Tanaka, Shigenori
2005-01-01
Functionally relevant motion of proteins has been associated with a number of atoms moving in a concerted fashion along so-called "collective coordinates." We present an approach to extract collective coordinates from conformations obtained from molecular dynamics simulations. The power of this technique for differentiating local structural fuctuations between classes of conformers obtained by clustering is illustrated by analyzing nanosecond-long trajectories for the response regulator protein Spo0F of Bacillus subtilis, generated both in vacuo and using an implicit-solvent representation. Conformational clustering is performed using automated histogram filtering of the inter-Cα distances. Orthogonal (varimax) rotation of the vectors obtained by principal component analysis of these interresidue distances for the members of individual clusters is key to the interpretation of collective coordinates dominating each conformational class. The rotated loadings plots isolate significant variation in interresidue distances, and these are associated with entire mobile secondary structure elements. From this we infer concerted motions of these structural elements. For the Spo0F simulations employing an implicit-solvent representation, collective coordinates obtained in this fashion are consistent with the location of the protein's known active sites and experimentally determined mobile regions.
NASA Astrophysics Data System (ADS)
Wang, Wei; Coombs, Tim
2018-04-01
We have uncovered at the macroscopic scale a magnetic coupling phenomenon in a superconducting YBa2Cu3O7 -δ (YBCO) film, which physically explains the mechanism of the high-temperature superconducting flux pump. The coupling occurs between the applied magnetic poles and clusters of vortices induced in the YBCO film, with each cluster containing millions of vortices. The coupling energy is verified to originate from the inhomogeneous field of the magnetic poles, which reshapes the vortex distribution, aggregates millions of vortices into a single cluster, and accordingly moves with the poles. A contrast study is designed to verify that, to provide the effective coupling energy, the applied wavelength must be short while the field amplitude must be strong, i.e., local-field inhomogeneity is the crucial factor. This finding broadens our understanding of the collective vortex behavior in an applied magnetic field with strong local inhomogeneity. Moreover, this phenomenon largely increases the controlled vortex flow rate by several orders of magnitude compared with existing methods, providing motivation for and physical support to a new branch of wireless superconducting dc power sources, i.e., the high-temperature superconducting flux pump.
Global, Multi-Objective Trajectory Optimization With Parametric Spreading
NASA Technical Reports Server (NTRS)
Vavrina, Matthew A.; Englander, Jacob A.; Phillips, Sean M.; Hughes, Kyle M.
2017-01-01
Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.
Optical domain analog to digital conversion methods and apparatus
Vawter, Gregory A
2014-05-13
Methods and apparatus for optical analog to digital conversion are disclosed. An optical signal is converted by mapping the optical analog signal onto a wavelength modulated optical beam, passing the mapped beam through interferometers to generate analog bit representation signals, and converting the analog bit representation signals into an optical digital signal. A photodiode receives an optical analog signal, a wavelength modulated laser coupled to the photodiode maps the optical analog signal to a wavelength modulated optical beam, interferometers produce an analog bit representation signal from the mapped wavelength modulated optical beam, and sample and threshold circuits corresponding to the interferometers produce a digital bit signal from the analog bit representation signal.
Generation of strongly coupled Xe cluster nanoplasmas by low intensive soft x-ray laser irradiation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Namba, S.; Hasegawa, N.; Kishimoto, M.
A seeding gas jet including Xe clusters was irradiated with a laser-driven plasma soft x-ray laser pulse ({lambda}=13.9 nm, {approx}7 ps, {<=}5 Multiplication-Sign 10{sup 9} W/cm{sup 2}), where the laser photon energy is high enough to ionize 4d core electrons. In order to clarify how the innershell ionization followed by the Auger electron emission is affected under the intense laser irradiation, the electron energy distribution was measured. Photoelectron spectra showed that the peak position attributed to 4d hole shifted to lower energy and the spectral width was broadened with increasing cluster size. Moreover, the energy distribution exhibited that a stronglymore » coupled cluster nanoplasma with several eV was generated.« less
Stability and Noise-induced Transitions in an Ensemble of Nonlocally Coupled Chaotic Maps
NASA Astrophysics Data System (ADS)
Bukh, Andrei V.; Slepnev, Andrei V.; Anishchenko, Vadim S.; Vadivasova, Tatiana E.
2018-05-01
The influence of noise on chimera states arising in ensembles of nonlocally coupled chaotic maps is studied. There are two types of chimera structures that can be obtained in such ensembles: phase and amplitude chimera states. In this work, a series of numerical experiments is carried out to uncover the impact of noise on both types of chimeras. The noise influence on a chimera state in the regime of periodic dynamics results in the transition to chaotic dynamics. At the same time, the transformation of incoherence clusters of the phase chimera to incoherence clusters of the amplitude chimera occurs. Moreover, it is established that the noise impact may result in the appearance of a cluster with incoherent behavior in the middle of a coherence cluster.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Govind, Niranjan; Sushko, Petr V.; Hess, Wayne P.
2009-03-05
We present a study of the electronic excitations in insulating materials using an embedded- cluster method. The excited states of the embedded cluster are studied systematically using time-dependent density functional theory (TDDFT) and high-level equation-of-motion coupled cluster (EOMCC) methods. In particular, we have used EOMCC models with singles and doubles (EOMCCSD) and two approaches which account for the e®ect of triply excited con¯gurations in non-iterative and iterative fashions. We present calculations of the lowest surface excitations of the well-studied potassium bromide (KBr) system and compare our results with experiment. The bulk-surface exciton shift is also calculated at the TDDFT levelmore » and compared with experiment.« less
Omens of coupled model biases in the CMIP5 AMIP simulations
NASA Astrophysics Data System (ADS)
Găinuşă-Bogdan, Alina; Hourdin, Frédéric; Traore, Abdoul Khadre; Braconnot, Pascale
2018-02-01
Despite decades of efforts and improvements in the representation of processes as well as in model resolution, current global climate models still suffer from a set of important, systematic biases in sea surface temperature (SST), not much different from the previous generation of climate models. Many studies have looked at errors in the wind field, cloud representation or oceanic upwelling in coupled models to explain the SST errors. In this paper we highlight the relationship between latent heat flux (LH) biases in forced atmospheric simulations and the SST biases models develop in coupled mode, at the scale of the entire intertropical domain. By analyzing 22 pairs of forced atmospheric and coupled ocean-atmosphere simulations from the CMIP5 database, we show a systematic, negative correlation between the spatial patterns of these two biases. This link between forced and coupled bias patterns is also confirmed by two sets of dedicated sensitivity experiments with the IPSL-CM5A-LR model. The analysis of the sources of the atmospheric LH bias pattern reveals that the near-surface wind speed bias dominates the zonal structure of the LH bias and that the near-surface relative humidity dominates the east-west contrasts.
Yao, Jincao; Yu, Huimin; Hu, Roland
2017-01-01
This paper introduces a new implicit-kernel-sparse-shape-representation-based object segmentation framework. Given an input object whose shape is similar to some of the elements in the training set, the proposed model can automatically find a cluster of implicit kernel sparse neighbors to approximately represent the input shape and guide the segmentation. A distance-constrained probabilistic definition together with a dualization energy term is developed to connect high-level shape representation and low-level image information. We theoretically prove that our model not only derives from two projected convex sets but is also equivalent to a sparse-reconstruction-error-based representation in the Hilbert space. Finally, a "wake-sleep"-based segmentation framework is applied to drive the evolutionary curve to recover the original shape of the object. We test our model on two public datasets. Numerical experiments on both synthetic images and real applications show the superior capabilities of the proposed framework.
Multilayer Extreme Learning Machine With Subnetwork Nodes for Representation Learning.
Yang, Yimin; Wu, Q M Jonathan
2016-11-01
The extreme learning machine (ELM), which was originally proposed for "generalized" single-hidden layer feedforward neural networks, provides efficient unified learning solutions for the applications of clustering, regression, and classification. It presents competitive accuracy with superb efficiency in many applications. However, ELM with subnetwork nodes architecture has not attracted much research attentions. Recently, many methods have been proposed for supervised/unsupervised dimension reduction or representation learning, but these methods normally only work for one type of problem. This paper studies the general architecture of multilayer ELM (ML-ELM) with subnetwork nodes, showing that: 1) the proposed method provides a representation learning platform with unsupervised/supervised and compressed/sparse representation learning and 2) experimental results on ten image datasets and 16 classification datasets show that, compared to other conventional feature learning methods, the proposed ML-ELM with subnetwork nodes performs competitively or much better than other feature learning methods.
Impact of symmetry breaking in networks of globally coupled oscillators
NASA Astrophysics Data System (ADS)
Premalatha, K.; Chandrasekar, V. K.; Senthilvelan, M.; Lakshmanan, M.
2015-05-01
We analyze the consequences of symmetry breaking in the coupling in a network of globally coupled identical Stuart-Landau oscillators. We observe that symmetry breaking leads to increased disorderliness in the dynamical behavior of oscillatory states and consequently results in a rich variety of dynamical states. Depending on the strength of the nonisochronicity parameter, we find various dynamical states such as amplitude chimera, amplitude cluster, frequency chimera, and frequency cluster states. In addition we also find disparate transition routes to recently observed chimera death states in the presence of symmetry breaking even with global coupling. We also analytically verify the chimera death region, which corroborates the numerical results. These results are compared with that of the symmetry-preserving case as well.
Samsir, Sri A'jilah; Bunawan, Hamidun; Yen, Choong Chee; Noor, Normah Mohd
2016-09-01
In this dataset, we distinguish 15 accessions of Garcinia mangostana from Peninsular Malaysia using Fourier transform-infrared spectroscopy coupled with chemometric analysis. We found that the position and intensity of characteristic peaks at 3600-3100 cm(-) (1) in IR spectra allowed discrimination of G. mangostana from different locations. Further principal component analysis (PCA) of all the accessions suggests the two main clusters were formed: samples from Johor, Melaka, and Negeri Sembilan (South) were clustered together in one group while samples from Perak, Kedah, Penang, Selangor, Kelantan, and Terengganu (North and East Coast) were in another clustered group.
NASA Astrophysics Data System (ADS)
Rupel, Dylan
2015-03-01
The first goal of this note is to extend the well-known Feigin homomorphisms taking quantum groups to quantum polynomial algebras. More precisely, we define generalized Feigin homomorphisms from a quantum shuffle algebra to quantum polynomial algebras which extend the classical Feigin homomorphisms along the embedding of the quantum group into said quantum shuffle algebra. In a recent work of Berenstein and the author, analogous extensions of Feigin homomorphisms from the dual Hall-Ringel algebra of a valued quiver to quantum polynomial algebras were defined. To relate these constructions, we establish a homomorphism, dubbed the quantum shuffle character, from the dual Hall-Ringel algebra to the quantum shuffle algebra which relates the generalized Feigin homomorphisms. These constructions can be compactly described by a commuting tetrahedron of maps beginning with the quantum group and terminating in a quantum polynomial algebra. The second goal in this project is to better understand the dual canonical basis conjecture for skew-symmetrizable quantum cluster algebras. In the symmetrizable types it is known that dual canonical basis elements need not have positive multiplicative structure constants, while this is still suspected to hold for skew-symmetrizable quantum cluster algebras. We propose an alternate conjecture for the symmetrizable types: the cluster monomials should correspond to irreducible characters of a KLR algebra. Indeed, the main conjecture of this note would establish this ''KLR conjecture'' for acyclic skew-symmetrizable quantum cluster algebras: that is, we conjecture that the images of rigid representations under the quantum shuffle character give irreducible characters for KLR algebras. We sketch a proof in the symmetric case giving an alternative to the proof of Kimura-Qin that all non-initial cluster variables in an acyclic skew-symmetric quantum cluster algebra are contained in the dual canonical basis. With these results in mind we interpret the cluster mutations directly in terms of the representation theory of the KLR algebra.
Parental divorce and adult children's attachment representations and marital status.
Crowell, Judith A; Treboux, Dominique; Brockmeyer, Susan
2009-01-01
The purpose of this study was to explore adult attachment as a means of understanding the intergenerational transmission of divorce, that is, the propensity for the children of divorce to end their own marriages. Participants included 157 couples assessed 3 months prior to their weddings and 6 years later. Participants completed the Adult Attachment Interview and questionnaires about their relationships, and were videotaped with their partners in a couple interaction task. Results indicated that, in this sample, adult children of divorce were not more likely to divorce within the first 6 years of marriage. However, parental divorce increased the likelihood of having an insecure adult attachment status. For women, age at the time of their parents' divorce was related to adult attachment status, and the influence on attachment representations may be more enduring. Among adult children of divorce, those who were classified as secure in their attachment representations were less likely to divorce in the early years of marriage than insecure participants.
Phase-amplitude coupling supports phase coding in human ECoG
Watrous, Andrew J; Deuker, Lorena; Fell, Juergen; Axmacher, Nikolai
2015-01-01
Prior studies have shown that high-frequency activity (HFA) is modulated by the phase of low-frequency activity. This phenomenon of phase-amplitude coupling (PAC) is often interpreted as reflecting phase coding of neural representations, although evidence for this link is still lacking in humans. Here, we show that PAC indeed supports phase-dependent stimulus representations for categories. Six patients with medication-resistant epilepsy viewed images of faces, tools, houses, and scenes during simultaneous acquisition of intracranial recordings. Analyzing 167 electrodes, we observed PAC at 43% of electrodes. Further inspection of PAC revealed that category specific HFA modulations occurred at different phases and frequencies of the underlying low-frequency rhythm, permitting decoding of categorical information using the phase at which HFA events occurred. These results provide evidence for categorical phase-coded neural representations and are the first to show that PAC coincides with phase-dependent coding in the human brain. DOI: http://dx.doi.org/10.7554/eLife.07886.001 PMID:26308582
Metastable Autoionizing States of Molecules and Radicals in Highly Energetic Environment
2016-03-22
electronic states. The specific aims are to develop and calibrate complex-scaled equation-of-motion coupled cluster (cs-EOM- CC ) and CAP (complex...absorbing potential) augmented EOM- CC methods. We have implemented and benchmarked cs-EOM-CCSD and CAP- augmented EOM-CCSD methods for excitation energies...motion coupled cluster (cs-EOM- CC ) and CAP (complex absorbing potential) augmented EOM- CC methods. We have implemented and benchmarked cs-EOM-CCSD and
Communication: Biological applications of coupled-cluster frozen-density embedding
NASA Astrophysics Data System (ADS)
Heuser, Johannes; Höfener, Sebastian
2018-04-01
We report the implementation of the Laplace-transform scaled opposite-spin (LT-SOS) resolution-of-the-identity second-order approximate coupled-cluster singles and doubles (RICC2) combined with frozen-density embedding for excitation energies and molecular properties. In the present work, we furthermore employ the Hartree-Fock density for the interaction energy leading to a simplified Lagrangian which is linear in the Lagrangian multipliers. This approximation has the key advantage of a decoupling of the coupled-cluster amplitude and multipliers, leading also to a significant reduction in computation time. Using the new simplified Lagrangian in combination with efficient wavefunction models such as RICC2 or LT-SOS-RICC2 and density-functional theory (DFT) for the environment molecules (CC2-in-DFT) enables the efficient study of biological applications such as the rhodopsin and visual cone pigments using ab initio methods as routine applications.
NASA Astrophysics Data System (ADS)
Gomez, John A.; Henderson, Thomas M.; Scuseria, Gustavo E.
2017-11-01
In electronic structure theory, restricted single-reference coupled cluster (CC) captures weak correlation but fails catastrophically under strong correlation. Spin-projected unrestricted Hartree-Fock (SUHF), on the other hand, misses weak correlation but captures a large portion of strong correlation. The theoretical description of many important processes, e.g. molecular dissociation, requires a method capable of accurately capturing both weak and strong correlation simultaneously, and would likely benefit from a combined CC-SUHF approach. Based on what we have recently learned about SUHF written as particle-hole excitations out of a symmetry-adapted reference determinant, we here propose a heuristic CC doubles model to attenuate the dominant spin collective channel of the quadratic terms in the CC equations. Proof of principle results presented here are encouraging and point to several paths forward for improving the method further.
Yu, Yang; Li, Chen; Yin, Bing; Li, Jian-Li; Huang, Yuan-He; Wen, Zhen-Yi; Jiang, Zhen-Yi
2013-08-07
The structures, relative stabilities, vertical electron detachment energies, and magnetic properties of a series of trinuclear clusters are explored via combined broken-symmetry density functional theory and ab initio study. Several exchange-correlation functionals are utilized to investigate the effects of different halogen elements and central atoms on the properties of the clusters. These clusters are shown to possess stronger superhalogen properties than previously reported dinuclear superhalogens. The calculated exchange coupling constants indicate the antiferromagnetic coupling between the transition metal ions. Spin density analysis demonstrates the importance of spin delocalization in determining the strengths of various couplings. Spin frustration is shown to occur in some of the trinuclear superhalogens. The coexistence of strong superhalogen properties and spin frustration implies the possibility of trinuclear superhalogens working as the building block of new materials of novel magnetic properties.
Xu, Enhua; Ten-No, Seiichiro L
2018-06-05
Partially linearized external models to active-space coupled-cluster through hextuple excitations, for example, CC{SDtqph} L , CCSD{tqph} L , and CCSD{tqph} hyb, are implemented and compared with the full active-space CCSDtqph. The computational scaling of CCSDtqph coincides with that for the standard coupled-cluster singles and doubles (CCSD), yet with a much large prefactor. The approximate schemes to linearize the external excitations higher than doubles are significantly cheaper than the full CCSDtqph model. These models are applied to investigate the bond dissociation energies of diatomic molecules (HF, F 2 , CuH, and CuF), and the potential energy surfaces of the bond dissociation processes of HF, CuH, H 2 O, and C 2 H 4 . Among the approximate models, CCSD{tqph} hyb provides very accurate descriptions compared with CCSDtqph for all of the tested systems. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.
Spin-orbit coupling effect on structural and magnetic properties of ConRh13-n (n = 0-13) clusters
NASA Astrophysics Data System (ADS)
Bai, Xi; Lv, Jin; Zhang, Fu-Qiang; Jia, Jian-Feng; Wu, Hai-Shun
2018-04-01
The effect of spin-orbit interaction on the structures and magnetism of ConRh13-n (n = 0-13) clusters have been systematically investigated by using the spin-orbit coupling (SOC) implementation of the density functional theory (DFT). The results calculated without SOC (NSOC) show that Rh13 prefers the double simple-cubic configuration, and icosahedron is the favorable structure for n = 1-9, while n ≥ 10, clusters favor the hexagonal bilayer structure. The inclusion of SOC in calculation does not change the geometries of clusters. Compared with that in NSOC calculation, although the binding energy per atom in clusters with same composition decreases in SOC calculation, the relative stability of clusters with different compositions does not change. An interesting result is that the spin moments of clusters for n = 1-9 are almost constant (21 μB). Spin-orbit interaction recovers orbital moment and its anisotropy by removing crystal-field effect in calculation. The destruction of bonding symmetry and relaxation of bonding account for high anisotropies of orbital moments in Co11Rh2 and CoRh12 clusters. With atomic composition (Co/Rh) around 4/9-5/8 and 9/4, the Co-Rh clusters exhibit high magnetic anisotropy energies.
Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; MacEachren, Alan M
2008-01-01
Background Kulldorff's spatial scan statistic and its software implementation – SaTScan – are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. Results We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. Conclusion The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. Method We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit. PMID:18992163
Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M
2008-11-07
Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit.
Emergent patterns in interacting neuronal sub-populations
NASA Astrophysics Data System (ADS)
Kamal, Neeraj Kumar; Sinha, Sudeshna
2015-05-01
We investigate an ensemble of coupled model neurons, consisting of groups of varying sizes and intrinsic dynamics, ranging from periodic to chaotic, where the inter-group coupling interaction is effectively like a dynamic signal from a different sub-population. We observe that the minority group can significantly influence the majority group. For instance, when a small chaotic group is coupled to a large periodic group, the chaotic group de-synchronizes. However, counter-intuitively, when a small periodic group couples strongly to a large chaotic group, it leads to complete synchronization in the majority chaotic population, which also spikes at the frequency of the small periodic group. It then appears that the small group of periodic neurons can act like a pacemaker for the whole network. Further, we report the existence of varied clustering patterns, ranging from sets of synchronized clusters to anti-phase clusters, governed by the interplay of the relative sizes and dynamics of the sub-populations. So these results have relevance in understanding how a group can influence the synchrony of another group of dynamically different elements, reminiscent of event-related synchronization/de-synchronization in complex networks.
NASA Technical Reports Server (NTRS)
Guseynov, F. G.; Abbasova, E. M.
1977-01-01
The equivalent representation of brakes and coupling by lumped circuits is investigated. Analytical equations are derived for relating the indices of the transients to the parameters of the equivalent circuits for arbitrary rotor speed. A computer algorithm is given for the calculations.
USDA-ARS?s Scientific Manuscript database
The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...
Allowed Vales of J in jj coupling of Equivalent Electrons.
ERIC Educational Resources Information Center
Tuttle, E. R.
1980-01-01
Provides a simple method for finding the values of the total angular momentum J for configurations of equivalent electrons in jj coupling. Shows how a knowledge of both the LS and jj terms can contribute to the students' understanding of the role of different representations in quantum mechanics. (Author/GS)
NASA Astrophysics Data System (ADS)
Zhang, Tianzhen; Wang, Xiumei; Gao, Xinbo
2018-04-01
Nowadays, several datasets are demonstrated by multi-view, which usually include shared and complementary information. Multi-view clustering methods integrate the information of multi-view to obtain better clustering results. Nonnegative matrix factorization has become an essential and popular tool in clustering methods because of its interpretation. However, existing nonnegative matrix factorization based multi-view clustering algorithms do not consider the disagreement between views and neglects the fact that different views will have different contributions to the data distribution. In this paper, we propose a new multi-view clustering method, named adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization. The proposed algorithm can obtain the parts-based representation of multi-view data by nonnegative matrix factorization. Then, pairwise co-regularization is used to measure the disagreement between views. There is only one parameter to auto learning the weight values according to the contribution of each view to data distribution. Experimental results show that the proposed algorithm outperforms several state-of-the-arts algorithms for multi-view clustering.
Single- or multi-flavor Kondo effect in graphene
NASA Astrophysics Data System (ADS)
Zhu, Zhen-Gang; Ding, Kai-He; Berakdar, Jamal
2010-06-01
Based on the tight-binding formalism, we investigate the Anderson and the Kondo model for an adatom magnetic impurity above graphene. Different impurity positions are analyzed. Employing a partial-wave representation we study the nature of the coupling between the impurity and the conducting electrons. The components from the two Dirac points are mixed while interacting with the impurity. Two configurations are considered explicitly: the adatom is above one atom (ADA), the other case is the adatom above the center the honeycomb (ADC). For ADA the impurity is coupled with one flavor for both A and B sublattice and both Dirac points. For ADC the impurity couples with multi-flavor states for a spinor state of the impurity. We show, explicitly for a 3d magnetic atom, dz2, (dxz,dyz), and (dx2- y2,dxy) couple respectively with the Γ1, Γ5(E1), and Γ6(E2) representations (reps) of C6v group in ADC case. The bases for these reps of graphene are also derived explicitly. For ADA we calculate the Kondo temperature.
Osumi, M; Ichinose, A; Sumitani, M; Wake, N; Sano, Y; Yozu, A; Kumagaya, S; Kuniyoshi, Y; Morioka, S
2017-01-01
We developed a quantitative method to measure movement representations of a phantom upper limb using a bimanual circle-line coordination task (BCT). We investigated whether short-term neurorehabilitation with a virtual reality (VR) system would restore voluntary movement representations and alleviate phantom limb pain (PLP). Eight PLP patients were enrolled. In the BCT, they repeatedly drew vertical lines using the intact hand and intended to draw circles using the phantom limb. Drawing circles mentally using the phantom limb led to the emergence of an oval transfiguration of the vertical lines ('bimanual-coupling' effect). We quantitatively measured the degree of this bimanual-coupling effect as movement representations of the phantom limb before and immediately after short-term VR neurorehabilitation. This was achieved using an 11-point numerical rating scale (NRS) for PLP intensity and the Short-Form McGill Pain Questionnaire (SF-MPQ). During VR neurorehabilitation, patients wore a head-mounted display that showed a mirror-reversed computer graphic image of an intact arm (the virtual phantom limb). By intending to move both limbs simultaneously and similarly, the patients perceived voluntary execution of movement in their phantom limb. Short-term VR neurorehabilitation promptly restored voluntary movement representations in the BCT and alleviated PLP (NRS: p = 0.015; 39.1 ± 28.4% relief, SF-MPQ: p = 0.015; 61.5 ± 48.5% relief). Restoration of phantom limb movement representations and reduced PLP intensity were linearly correlated (p < 0.05). VR rehabilitation may encourage patient's motivation and multimodal sensorimotor re-integration of a phantom limb and subsequently have a potent analgesic effect. There was no objective evidence that restoring movement representation by neurorehabilitation with virtual reality alleviated phantom limb pain. This study revealed quantitatively that restoring movement representation with virtual reality rehabilitation using a bimanual coordination task correlated with alleviation of phantom limb pain. © 2016 European Pain Federation - EFIC®.
Kølvraa, Mathias; Müller, Felix C; Jahnsen, Henrik; Rekling, Jens C
2014-01-01
Abstract The inferior olivary nucleus (IO) in in vitro slices from postnatal mice (P5.5–P15.5) spontaneously generates clusters of neurons with synchronous calcium transients, and intracellular recordings from IO neurons suggest that electrical coupling between neighbouring IO neurons may serve as a synchronizing mechanism. Here, we studied the cluster-forming mechanism and find that clusters overlap extensively with an overlap distribution that resembles the distribution for a random overlap model. The average somatodendritic field size of single curly IO neurons was ∼6400 μm2, which is slightly smaller than the average IO cluster size. Eighty-seven neurons with overlapping dendrites were estimated to be contained in the principal olive mean cluster size, and about six non-overlapping curly IO neurons could be contained within the largest clusters. Clusters could also be induced by iontophoresis with glutamate. Induced clusters were inhibited by tetrodotoxin, carbenoxelone and 18β-glycyrrhetinic acid, suggesting that sodium action potentials and electrical coupling are involved in glutamate-induced cluster formation, which could also be induced by activation of N-methyl-d-aspartate and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors. Spikelets and a small transient depolarizing response were observed during glutamate-induced cluster formation. Calcium transients spread with decreasing velocity during cluster formation, and somatic action potentials and cluster formation are accompanied by large dendritic calcium transients. In conclusion, cluster formation depends on gap junctions, sodium action potentials and spontaneous clusters occur randomly throughout the IO. The relative slow signal spread during cluster formation, combined with a strong dendritic influx of calcium, may signify that active dendritic properties contribute to cluster formation. PMID:24042500
The Structure and Stability of Bn(+) Clusters
NASA Technical Reports Server (NTRS)
Ricca, Alessandra; Bauschlicher, Charles W., Jr.; Langhoff, Stephen R. (Technical Monitor)
1995-01-01
The geometries of B+n clusters for n less than 14 have been optimized using density functional theory with the B3LYP functional. The most stable structure for each cluster is planar or quasi-planar. The B3LYP fragmentation energies are calibrated using coupled cluster theory. Overall, our corrected fragmentation energies are in reasonable agreement with experiment. Our results are compared with previous theoretical results.
NASA Technical Reports Server (NTRS)
Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.
1992-01-01
The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.
Clustering of financial time series
NASA Astrophysics Data System (ADS)
D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo
2013-05-01
This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.
Pattern Selection and Super-Patterns in Opinion Dynamics
NASA Astrophysics Data System (ADS)
Ben-Naim, Eli; Scheel, Arnd
We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.
Gruenenfelder, Thomas M; Recchia, Gabriel; Rubin, Tim; Jones, Michael N
2016-08-01
We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others on an associative network (POC) successfully predicted all of the network properties and predicted a word's top five associates as well as or better than the better of the two constituent models. The results suggest that participants switch between a contextual representation and an associative network when generating free associations. We discuss the role that each of these representations may play in lexical semantic memory. Concordant with recent multicomponent theories of semantic memory, the associative network may encode coordinate relations between concepts (e.g., the relation between pea and bean, or between sparrow and robin), and contextual representations may be used to process information about more abstract concepts. Copyright © 2015 Cognitive Science Society, Inc.
Model validation of simple-graph representations of metabolism
Holme, Petter
2009-01-01
The large-scale properties of chemical reaction systems, such as metabolism, can be studied with graph-based methods. To do this, one needs to reduce the information, lists of chemical reactions, available in databases. Even for the simplest type of graph representation, this reduction can be done in several ways. We investigate different simple network representations by testing how well they encode information about one biologically important network structure—network modularity (the propensity for edges to be clustered into dense groups that are sparsely connected between each other). To achieve this goal, we design a model of reaction systems where network modularity can be controlled and measure how well the reduction to simple graphs captures the modular structure of the model reaction system. We find that the network types that best capture the modular structure of the reaction system are substrate–product networks (where substrates are linked to products of a reaction) and substance networks (with edges between all substances participating in a reaction). Furthermore, we argue that the proposed model for reaction systems with tunable clustering is a general framework for studies of how reaction systems are affected by modularity. To this end, we investigate statistical properties of the model and find, among other things, that it recreates correlations between degree and mass of the molecules. PMID:19158012
Consensus of satellite cluster flight using an energy-matching optimal control method
NASA Astrophysics Data System (ADS)
Luo, Jianjun; Zhou, Liang; Zhang, Bo
2017-11-01
This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.
Orbital-ordering-driven multiferroicity and magnetoelectric coupling in GeV₄S₈.
Singh, Kiran; Simon, Charles; Cannuccia, Elena; Lepetit, Marie-Bernadette; Corraze, Benoit; Janod, Etienne; Cario, Laurent
2014-09-26
We report here the discovery of multiferroicity and large magnetoelectric coupling in the type I orbital order system GeV₄S₈. Our study demonstrates that this clustered compound displays a para-ferroelectric transition at 32 K. This transition originates from an orbital ordering which reorganizes the charge within the transition metal clusters. Below the antiferromagnetic transition at 17 K, the application of a magnetic field significantly affects the ferroelectric polarization, revealing thus a large magnetoelectric coupling. Our study suggests that the application of a magnetic field induces a metamagnetic transition which significantly affects the ferroelectric polarization thanks to an exchange striction phenomenon.
Discrete modelling of front propagation in backward piping erosion
NASA Astrophysics Data System (ADS)
Tran, Duc-Kien; Prime, Noémie; Froiio, Francesco; Callari, Carlo; Vincens, Eric
2017-06-01
A preliminary discrete numerical model of a REV at the front region of an erosion pipe in a cohesive granular soil is briefly presented. The results reported herein refer to a simulation carried out by coupling the Discrete Element Method (DEM) with the Lattice Boltzmann Method (LBM) for the representation of the granular and fluid phases, respectively. The numerical specimen, consisiting of bonded grains, is tested under fully-saturated conditions and increasing pressure difference between the inlet (confined) and the outlet (unconfined) flow regions. The key role of compression arches of force chains that transversely cross the sample and carry most part of the hydrodynamic actions is pointed out. These arches partition the REV into an upstream region that remains almost intact and a downstream region that gradually degrades and is subsequently eroded in the form of a cluster. Eventually, the collapse of the compression arches causes the upstream region to be also eroded, abruptly, as a whole. A complete presentation of the numerical model and of the results of the simulation can be found in [12].
Titan's Ionic Species: Theoretical Treatment of N2H+ and Related Ions
NASA Astrophysics Data System (ADS)
Brites, V.; Hochlaf, M.
2009-06-01
We use different ab initio methods to compute the three-dimensional potential energy surface (3D-PES) of the ground state of N2H+. This includes the standard coupled cluster, the complete active space self-consistent field, the internally contacted multi reference configuration interaction, and the newly developed CCSD(T)-F12 methods. For the description of H and N atoms, several basis sets are tested. Then, we incorporate the 3D-PES analytical representations into variational calculations of the rovibrational spectrum of N2H+(X˜1Σ+) up to 7200 cm-1 above the zero point vibrational energy. Our data show that the CCSD(T)-F12/aug-cc-pVTZ approach represents a compromise for good description of the PES and computation cost. This technique is recommended for full dimensional PES generation of atmospheric and astrophysical relevant polyatomic systems. We applied this method to derive the rovibrational spectra of N2H+(X˜1Σ+) and of N2H++(X˜2Σ+). Finally, we discuss the existence of the N2H++(X˜2Σ+) in Titan's atmosphere.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wykes, M., E-mail: mikewykes@gmail.com; Parambil, R.; Gierschner, J.
Here, we present a general approach to treating vibronic coupling in molecular crystals based on atomistic simulations of large clusters. Such clusters comprise model aggregates treated at the quantum chemical level embedded within a realistic environment treated at the molecular mechanics level. As we calculate ground and excited state equilibrium geometries and vibrational modes of model aggregates, our approach is able to capture effects arising from coupling to intermolecular degrees of freedom, absent from existing models relying on geometries and normal modes of single molecules. Using the geometries and vibrational modes of clusters, we are able to simulate the fluorescencemore » spectra of aggregates for which the lowest excited state bears negligible oscillator strength (as is the case, e.g., ideal H-aggregates) by including both Franck-Condon (FC) and Herzberg-Teller (HT) vibronic transitions. The latter terms allow the adiabatic excited state of the cluster to couple with vibrations in a perturbative fashion via derivatives of the transition dipole moment along nuclear coordinates. While vibronic coupling simulations employing FC and HT terms are well established for single-molecules, to our knowledge this is the first time they are applied to molecular aggregates. Here, we apply this approach to the simulation of the low-temperature fluorescence spectrum of para-distyrylbenzene single-crystal H-aggregates and draw comparisons with coarse-grained Frenkel-Holstein approaches previously extensively applied to such systems.« less
A quasiparticle-based multi-reference coupled-cluster method.
Rolik, Zoltán; Kállay, Mihály
2014-10-07
The purpose of this paper is to introduce a quasiparticle-based multi-reference coupled-cluster (MRCC) approach. The quasiparticles are introduced via a unitary transformation which allows us to represent a complete active space reference function and other elements of an orthonormal multi-reference (MR) basis in a determinant-like form. The quasiparticle creation and annihilation operators satisfy the fermion anti-commutation relations. On the basis of these quasiparticles, a generalization of the normal-ordered operator products for the MR case can be introduced as an alternative to the approach of Mukherjee and Kutzelnigg [Recent Prog. Many-Body Theor. 4, 127 (1995); Mukherjee and Kutzelnigg, J. Chem. Phys. 107, 432 (1997)]. Based on the new normal ordering any quasiparticle-based theory can be formulated using the well-known diagram techniques. Beyond the general quasiparticle framework we also present a possible realization of the unitary transformation. The suggested transformation has an exponential form where the parameters, holding exclusively active indices, are defined in a form similar to the wave operator of the unitary coupled-cluster approach. The definition of our quasiparticle-based MRCC approach strictly follows the form of the single-reference coupled-cluster method and retains several of its beneficial properties. Test results for small systems are presented using a pilot implementation of the new approach and compared to those obtained by other MR methods.
Alpha-cluster preformation factor within cluster-formation model for odd-A and odd-odd heavy nuclei
NASA Astrophysics Data System (ADS)
Saleh Ahmed, Saad M.
2017-06-01
The alpha-cluster probability that represents the preformation of alpha particle in alpha-decay nuclei was determined for high-intensity alpha-decay mode odd-A and odd-odd heavy nuclei, 82 < Z < 114, 111 < N < 174. This probability was calculated using the energy-dependent formula derived from the formulation of clusterisation states representation (CSR) and the hypothesised cluster-formation model (CFM) as in our previous work. Our previous successful determination of phenomenological values of alpha-cluster preformation factors for even-even nuclei motivated us to expand the work to cover other types of nuclei. The formation energy of interior alpha cluster needed to be derived for the different nuclear systems with considering the unpaired-nucleon effect. The results showed the phenomenological value of alpha preformation probability and reflected the unpaired nucleon effect and the magic and sub-magic effects in nuclei. These results and their analyses presented are very useful for future work concerning the calculation of the alpha decay constants and the progress of its theory.
Automated atlas-based clustering of white matter fiber tracts from DTMRI.
Maddah, Mahnaz; Mewes, Andrea U J; Haker, Steven; Grimson, W Eric L; Warfield, Simon K
2005-01-01
A new framework is presented for clustering fiber tracts into anatomically known bundles. This work is motivated by medical applications in which variation analysis of known bundles of fiber tracts in the human brain is desired. To include the anatomical knowledge in the clustering, we invoke an atlas of fiber tracts, labeled by the number of bundles of interest. In this work, we construct such an atlas and use it to cluster all fiber tracts in the white matter. To build the atlas, we start with a set of labeled ROIs specified by an expert and extract the fiber tracts initiating from each ROI. Affine registration is used to project the extracted fiber tracts of each subject to the atlas, whereas their B-spline representation is used to efficiently compare them to the fiber tracts in the atlas and assign cluster labels. Expert visual inspection of the result confirms that the proposed method is very promising and efficient in clustering of the known bundles of fiber tracts.
Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell
2009-02-01
Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.
Electrostatic effects on clustering and ion dynamics in ionomer melts
NASA Astrophysics Data System (ADS)
Ma, Boran; Nguyen, Trung; Pryamitsyn, Victor; Olvera de La Cruz, Monica
An understanding of the relationships between ionomer chain morphology, dynamics and counter-ion mobility is a key factor in the design of ion conducting membranes for battery applications. In this study, we investigate the influence of electrostatic coupling between randomly charged copolymers (ionomers) and counter ions on the structural and dynamic features of a model system of ionomer melts. Using coarse-grained molecular dynamics (CGMD) simulations, we found that variations in electrostatic coupling strength (Γ) remarkably affect the formation of ion-counter ion clusters, ion mobility, and polymer dynamics for a range of charged monomer fractions. Specifically, an increase in Γ leads to larger ionic cluster sizes and reduced polymer and ion mobility. Analysis of the distribution of the radius of gyration of the clusters further reveals that the fractal dimension of the ion clusters is nearly independent from Γ for all the cases studied. Finally, at sufficiently high values of Γ, we observed arrested heterogeneous ions mobility, which is correlated with an increase in ion cluster size. These findings provide insight into the role of electrostatics in governing the nanostructures formed by ionomers.
Heterogeneous delays making parents synchronized: A coupled maps on Cayley tree model
NASA Astrophysics Data System (ADS)
Singh, Aradhana; Jalan, Sarika
2014-06-01
We study the phase synchronized clusters in the diffusively coupled maps on the Cayley tree networks for heterogeneous delay values. Cayley tree networks comprise of two parts: the inner nodes and the boundary nodes. We find that heterogeneous delays lead to various cluster states, such as; (a) cluster state consisting of inner nodes and boundary nodes, and (b) cluster state consisting of only boundary nodes. The former state may comprise of nodes from all the generations forming self-organized cluster or nodes from few generations yielding driven clusters depending upon on the parity of heterogeneous delay values. Furthermore, heterogeneity in delays leads to the lag synchronization between the siblings lying on the boundary by destroying the exact synchronization among them. The time lag being equal to the difference in the delay values. The Lyapunov function analysis sheds light on the destruction of the exact synchrony among the last generation nodes. To the end we discuss the relevance of our results with respect to their applications in the family business as well as in understanding the occurrence of genetic diseases.
NASA Technical Reports Server (NTRS)
Bauschlicher, Charles W., Jr.; Partridge, Harry; Scuseria, Gustavo E.
1992-01-01
The correlation contribution to the M-C binding energy for the MCH2(+) systems can exceed 100 kcal/mol. At the self-consistent field (SCF) level, these systems can be more than 50 kcal/mol above the fragment energies. In spite of the poor zeroth-order reference, the coupled cluster single and double excitation method with a perturbational estimate of triple excitations, CCSD(T), method is shown to provide an accurate description of these systems. The maximum difference between the CCSD(T) and internally contracted averaged coupled-pair functional binding energies is 1.5 kcal/mol for CrCH2(+), with the remaining systems agreeing to within 1.0 kcal/mol.
Pattern formation for NO+N H3 on Pt(100): Two-dimensional numerical results
NASA Astrophysics Data System (ADS)
Uecker, Hannes
2005-01-01
The Lombardo-Fink-Imbihl model of the NO+NH3 reaction on a Pt(100) surface consists of seven coupled ordinary differential equations (ODE) and shows stable relaxation oscillations with sharp transitions in the relevant temperature range. Here we study numerically the effect of coupling of these oscillators by surface diffusion in two dimensions. We find different types of patterns, in particular phase clusters and standing waves. In models of related surface reactions such clustered solutions are known to exist only under a global coupling through the gas phase. This global coupling is replaced here by relatively fast diffusion of two variables which are kinetically slaved in the ODE. We also compare our simulations with experimental results and discuss some shortcomings of the model.
NASA Astrophysics Data System (ADS)
Loppini, A.; Pedersen, M. G.; Braun, M.; Filippi, S.
2017-09-01
The importance of gap-junction coupling between β cells in pancreatic islets is well established in mouse. Such ultrastructural connections synchronize cellular activity, confine biological heterogeneity, and enhance insulin pulsatility. Dysfunction of coupling has been associated with diabetes and altered β -cell function. However, the role of gap junctions between human β cells is still largely unexplored. By using patch-clamp recordings of β cells from human donors, we previously estimated electrical properties of these channels by mathematical modeling of pairs of human β cells. In this work we revise our estimate by modeling triplet configurations and larger heterogeneous clusters. We find that a coupling conductance in the range 0.005 -0.020 nS/pF can reproduce experiments in almost all the simulated arrangements. We finally explore the consequence of gap-junction coupling of this magnitude between β cells with mutant variants of the ATP-sensitive potassium channels involved in some metabolic disorders and diabetic conditions, translating studies performed on rodents to the human case. Our results are finally discussed from the perspective of therapeutic strategies. In summary, modeling of more realistic clusters with more than two β cells slightly lowers our previous estimate of gap-junction conductance and gives rise to patterns that more closely resemble experimental traces.
NASA Astrophysics Data System (ADS)
Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Li, Xiang; Yan, Ruqiang
2016-04-01
Fault information of aero-engine bearings presents two particular phenomena, i.e., waveform distortion and impulsive feature frequency band dispersion, which leads to a challenging problem for current techniques of bearing fault diagnosis. Moreover, although many progresses of sparse representation theory have been made in feature extraction of fault information, the theory also confronts inevitable performance degradation due to the fact that relatively weak fault information has not sufficiently prominent and sparse representations. Therefore, a novel nonlocal sparse model (coined NLSM) and its algorithm framework has been proposed in this paper, which goes beyond simple sparsity by introducing more intrinsic structures of feature information. This work adequately exploits the underlying prior information that feature information exhibits nonlocal self-similarity through clustering similar signal fragments and stacking them together into groups. Within this framework, the prior information is transformed into a regularization term and a sparse optimization problem, which could be solved through block coordinate descent method (BCD), is formulated. Additionally, the adaptive structural clustering sparse dictionary learning technique, which utilizes k-Nearest-Neighbor (kNN) clustering and principal component analysis (PCA) learning, is adopted to further enable sufficient sparsity of feature information. Moreover, the selection rule of regularization parameter and computational complexity are described in detail. The performance of the proposed framework is evaluated through numerical experiment and its superiority with respect to the state-of-the-art method in the field is demonstrated through the vibration signals of experimental rig of aircraft engine bearings.
Analysis of Fiber Clustering in Composite Materials Using High-Fidelity Multiscale Micromechanics
NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.
2015-01-01
A new multiscale micromechanical approach is developed for the prediction of the behavior of fiber reinforced composites in presence of fiber clustering. The developed method is based on a coupled two-scale implementation of the High-Fidelity Generalized Method of Cells theory, wherein both the local and global scales are represented using this micromechanical method. Concentration tensors and effective constitutive equations are established on both scales and linked to establish the required coupling, thus providing the local fields throughout the composite as well as the global properties and effective nonlinear response. Two nondimensional parameters, in conjunction with actual composite micrographs, are used to characterize the clustering of fibers in the composite. Based on the predicted local fields, initial yield and damage envelopes are generated for various clustering parameters for a polymer matrix composite with both carbon and glass fibers. Nonlinear epoxy matrix behavior is also considered, with results in the form of effective nonlinear response curves, with varying fiber clustering and for two sets of nonlinear matrix parameters.
Xu, Peng; Gordon, Mark S
2014-09-04
Anionic water clusters are generally considered to be extremely challenging to model using fragmentation approaches due to the diffuse nature of the excess electron distribution. The local correlation coupled cluster (CC) framework cluster-in-molecule (CIM) approach combined with the completely renormalized CR-CC(2,3) method [abbreviated CIM/CR-CC(2,3)] is shown to be a viable alternative for computing the vertical electron binding energies (VEBE). CIM/CR-CC(2,3) with the threshold parameter ζ set to 0.001, as a trade-off between accuracy and computational cost, demonstrates the reliability of predicting the VEBE, with an average percentage error of ∼15% compared to the full ab initio calculation at the same level of theory. The errors are predominantly from the electron correlation energy. The CIM/CR-CC(2,3) approach provides the ease of a black-box type calculation with few threshold parameters to manipulate. The cluster sizes that can be studied by high-level ab initio methods are significantly increased in comparison with full CC calculations. Therefore, the VEBE computed by the CIM/CR-CC(2,3) method can be used as benchmarks for testing model potential approaches in small-to-intermediate-sized water clusters.
Multi-Objective Scheduling for the Cluster II Constellation
NASA Technical Reports Server (NTRS)
Johnston, Mark D.; Giuliano, Mark
2011-01-01
This paper describes the application of the MUSE multiobjecctive scheduling framework to the Cluster II WBD scheduling domain. Cluster II is an ESA four-spacecraft constellation designed to study the plasma environment of the Earth and it's magnetosphere. One of the instruments on each of the four spacecraft is the Wide Band Data (WBD) plasma wave experiment. We have applied the MUSE evolutionary algorithm to the scheduling problem represented by this instrument, and the result has been adopted and utilized by the WBD schedulers for nearly a year. This paper describes the WBD scheduling problem, its representation in MUSE, and some of the visualization elements that provide insight into objective value tradeoffs.
NASA Astrophysics Data System (ADS)
Lutich, Andrey
2017-07-01
This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.
Bruno, C; Dudkiewicz-Sibony, C; Berthaut, I; Weil, E; Brunet, L; Fortier, C; Pfeffer, J; Ravel, C; Fauque, P; Mathieu, E; Antoine, J M; Kotti, S; Mandelbaum, J
2016-07-01
In couples who have chosen and confirmed the fate of surplus frozen embryos, which factors influence their decision, with a special emphasis on their symbolic representation of the embryo(s)? Embryo representation and gamete donation use significantly influence the fate of surplus cryopreserved embryos. Previous studies report difficulties for couples to decide whether or not to continue storing their frozen embryo(s) and different factors have been already highlighted which influence their decision, including embryo conceptualization, information and support provided by the medical institution, quality of embryo(s) and life events. Little is known, however, about couples who definitely decided to stop their parental project and finalized the process of decision-making about the fate of their cryopreserved embryo(s). This prospective study was conducted over a period of 3 years (2007-2010) and included IVF/ICSI patients with surplus frozen embryos, who made a final embryo disposition decision. Among the 280 eligible IVF/ICSI patients, 247 agreed to participate in the study. According to the available options, 91 persons chose to 'stop cryopreservation', 77 chose donation to 'research' and 48 'embryo donation' to infertile couples. Furthermore, 31 participants who chose embryo donation for a parental project were refused by the center as not compatible with their mandatory medical conditions. Among them, 27 participants then selected donation to research as a new option and were included in a fourth group: 'donation to research after Refusal of Embryo Donation for parental project' or 'research-RED' (n = 27). Four participants chose 'stop cryopreservation', however, given the small number of subjects this latter group was not included in the analysis. In all, 243 participants who made a final choice concerning the fate of their cryopreserved embryos were included in this study. Participants were sent a letter of invitation to a semi-structured interview of 30 min with a psychologist. Interviews were conducted separately for each partner, including a questionnaire with a common part and a specific part, according to the chosen option, and allowing a quantitative evaluation. A multivariate logistic regression model was used to assess the link between their embryo representation and their decision about their embryos' fate. After adjustment for age, gender, gamete donation, number of children and the different embryo representations, a choice to 'stop cryopreservation' is more frequent if the embryo is represented as a child [odds ratio (OR) adjusted = 3.29, 95% confidence interval (CI) = 1.62-6.66], P = 0.0009. Representing the embryo as a project prompts patients to choose 'donation to research' [OR adjusted = 3.76, 95% CI = 1.56-9.06], P = 0.0032. Respondents are more likely to choose 'embryo donation' if they represent the embryo as a potential person [OR adjusted = 3.77, 95% CI = 1.45-9.80], P = 0.0064. Furthermore, patients who benefited from gamete donation are ∼10 times more likely to donate their embryos to another couple [OR adjusted = 10.62, 95% CI = 3.99-28.30], P < 0.0001. For more than half the participants (57%) the decision-making was easy, however, deciding to stop cryopreservation was significantly more difficult than choosing research or embryo donation (P < 0.0001). Socio-economic status, moral and religious affiliations are known to influence the choice of couples but analyzing these factors was not an aim of the present study. When couples definitely decide to stop their parental project, the embryo symbolic representation remains the main factor that influences the fate of their frozen embryo(s). Moreover, this representation can evolve when influenced by external events and information provided. In order to support patients who are making this difficult decision, it could be helpful to explore this symbolic representation early in the IVF/ICSI procedure, before surplus embryo freezing, as a new tool enhancing the accuracy of counseling. this study was supported by a grant from the 'Agence de la biomedicine (ABM)', the national regulatory ART agency, under the authority of the French Ministry of Health. The authors have no conflict of interest to declare. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Development of a Typology of Dual-Earner Couples Caring for Children and Aging Parents
ERIC Educational Resources Information Center
Cullen, Jennifer C.; Hammer, Leslie B.; Neal, Margaret B.; Sinclair, Robert R.
2009-01-01
Using a national sample of 267 couples, the authors identify distinct profiles of dual-earner couples in the sandwiched generation (i.e., those caring for children and aging parents) using cluster analysis and then assess the relationship between these profiles and work-family conflict. The profiles are defined by characteristics of couples' child…
Representing and computing regular languages on massively parallel networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Miller, M.I.; O'Sullivan, J.A.; Boysam, B.
1991-01-01
This paper proposes a general method for incorporating rule-based constraints corresponding to regular languages into stochastic inference problems, thereby allowing for a unified representation of stochastic and syntactic pattern constraints. The authors' approach first established the formal connection of rules to Chomsky grammars, and generalizes the original work of Shannon on the encoding of rule-based channel sequences to Markov chains of maximum entropy. This maximum entropy probabilistic view leads to Gibb's representations with potentials which have their number of minima growing at precisely the exponential rate that the language of deterministically constrained sequences grow. These representations are coupled to stochasticmore » diffusion algorithms, which sample the language-constrained sequences by visiting the energy minima according to the underlying Gibbs' probability law. The coupling to stochastic search methods yields the all-important practical result that fully parallel stochastic cellular automata may be derived to generate samples from the rule-based constraint sets. The production rules and neighborhood state structure of the language of sequences directly determines the necessary connection structures of the required parallel computing surface. Representations of this type have been mapped to the DAP-510 massively-parallel processor consisting of 1024 mesh-connected bit-serial processing elements for performing automated segmentation of electron-micrograph images.« less
Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems.
Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A
2017-03-01
The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework.
Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems
Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A.
2017-01-01
Abstract The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework. PMID:28328252
Crepaldi, Davide; Berlingeri, Manuela; Cattinelli, Isabella; Borghese, Nunzio A.; Luzzatti, Claudio; Paulesu, Eraldo
2013-01-01
Although it is widely accepted that nouns and verbs are functionally independent linguistic entities, it is less clear whether their processing recruits different brain areas. This issue is particularly relevant for those theories of lexical semantics (and, more in general, of cognition) that suggest the embodiment of abstract concepts, i.e., based strongly on perceptual and motoric representations. This paper presents a formal meta-analysis of the neuroimaging evidence on noun and verb processing in order to address this dichotomy more effectively at the anatomical level. We used a hierarchical clustering algorithm that grouped fMRI/PET activation peaks solely on the basis of spatial proximity. Cluster specificity for grammatical class was then tested on the basis of the noun-verb distribution of the activation peaks included in each cluster. Thirty-two clusters were identified: three were associated with nouns across different tasks (in the right inferior temporal gyrus, the left angular gyrus, and the left inferior parietal gyrus); one with verbs across different tasks (in the posterior part of the right middle temporal gyrus); and three showed verb specificity in some tasks and noun specificity in others (in the left and right inferior frontal gyrus and the left insula). These results do not support the popular tenets that verb processing is predominantly based in the left frontal cortex and noun processing relies specifically on temporal regions; nor do they support the idea that verb lexical-semantic representations are heavily based on embodied motoric information. Our findings suggest instead that the cerebral circuits deputed to noun and verb processing lie in close spatial proximity in a wide network including frontal, parietal, and temporal regions. The data also indicate a predominant—but not exclusive—left lateralization of the network. PMID:23825451
Clustervision: Visual Supervision of Unsupervised Clustering.
Kwon, Bum Chul; Eysenbach, Ben; Verma, Janu; Ng, Kenney; De Filippi, Christopher; Stewart, Walter F; Perer, Adam
2018-01-01
Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.
Ding, Jiarui; Condon, Anne; Shah, Sohrab P
2018-05-21
Single-cell RNA-sequencing has great potential to discover cell types, identify cell states, trace development lineages, and reconstruct the spatial organization of cells. However, dimension reduction to interpret structure in single-cell sequencing data remains a challenge. Existing algorithms are either not able to uncover the clustering structures in the data or lose global information such as groups of clusters that are close to each other. We present a robust statistical model, scvis, to capture and visualize the low-dimensional structures in single-cell gene expression data. Simulation results demonstrate that low-dimensional representations learned by scvis preserve both the local and global neighbor structures in the data. In addition, scvis is robust to the number of data points and learns a probabilistic parametric mapping function to add new data points to an existing embedding. We then use scvis to analyze four single-cell RNA-sequencing datasets, exemplifying interpretable two-dimensional representations of the high-dimensional single-cell RNA-sequencing data.
Brown, André E X; Yemini, Eviatar I; Grundy, Laura J; Jucikas, Tadas; Schafer, William R
2013-01-08
Visible phenotypes based on locomotion and posture have played a critical role in understanding the molecular basis of behavior and development in Caenorhabditis elegans and other model organisms. However, it is not known whether these human-defined features capture the most important aspects of behavior for phenotypic comparison or whether they are sufficient to discover new behaviors. Here we show that four basic shapes, or eigenworms, previously described for wild-type worms, also capture mutant shapes, and that this representation can be used to build a dictionary of repetitive behavioral motifs in an unbiased way. By measuring the distance between each individual's behavior and the elements in the motif dictionary, we create a fingerprint that can be used to compare mutants to wild type and to each other. This analysis has revealed phenotypes not previously detected by real-time observation and has allowed clustering of mutants into related groups. Behavioral motifs provide a compact and intuitive representation of behavioral phenotypes.
Data-driven heterogeneity in mathematical learning disabilities based on the triple code model.
Peake, Christian; Jiménez, Juan E; Rodríguez, Cristina
2017-12-01
Many classifications of heterogeneity in mathematical learning disabilities (MLD) have been proposed over the past four decades, however no empirical research has been conducted until recently, and none of the classifications are derived from Triple Code Model (TCM) postulates. The TCM proposes MLD as a heterogeneous disorder, with two distinguishable profiles: a representational subtype and a verbal subtype. A sample of elementary school 3rd to 6th graders was divided into two age cohorts (3rd - 4th grades, and 5th - 6th grades). Using data-driven strategies, based on the cognitive classification variables predicted by the TCM, our sample of children with MLD clustered as expected: a group with representational deficits and a group with number-fact retrieval deficits. In the younger group, a spatial subtype also emerged, while in both cohorts a non-specific cluster was produced whose profile could not be explained by this theoretical approach. Copyright © 2017 Elsevier Ltd. All rights reserved.
Statistical and clustering analysis for disturbances: A case study of voltage dips in wind farms
Garcia-Sanchez, Tania; Gomez-Lazaro, Emilio; Muljadi, Eduard; ...
2016-01-28
This study proposes and evaluates an alternative statistical methodology to analyze a large number of voltage dips. For a given voltage dip, a set of lengths is first identified to characterize the root mean square (rms) voltage evolution along the disturbance, deduced from partial linearized time intervals and trajectories. Principal component analysis and K-means clustering processes are then applied to identify rms-voltage patterns and propose a reduced number of representative rms-voltage profiles from the linearized trajectories. This reduced group of averaged rms-voltage profiles enables the representation of a large amount of disturbances, which offers a visual and graphical representation ofmore » their evolution along the events, aspects that were not previously considered in other contributions. The complete process is evaluated on real voltage dips collected in intense field-measurement campaigns carried out in a wind farm in Spain among different years. The results are included in this paper.« less
Hydrodynamical simulations of coupled and uncoupled quintessence models - II. Galaxy clusters
NASA Astrophysics Data System (ADS)
Carlesi, Edoardo; Knebe, Alexander; Lewis, Geraint F.; Yepes, Gustavo
2014-04-01
We study the z = 0 properties of clusters (and large groups) of galaxies within the context of interacting and non-interacting quintessence cosmological models, using a series of adiabatic SPH simulations. Initially, we examine the average properties of groups and clusters, quantifying their differences in ΛCold Dark Matter (ΛCDM), uncoupled Dark Energy (uDE) and coupled Dark Energy (cDE) cosmologies. In particular, we focus upon radial profiles of the gas density, temperature and pressure, and we also investigate how the standard hydrodynamic equilibrium hypothesis holds in quintessence cosmologies. While we are able to confirm previous results about the distribution of baryons, we also find that the main discrepancy (with differences up to 20 per cent) can be seen in cluster pressure profiles. We then switch attention to individual structures, mapping each halo in quintessence cosmology to its ΛCDM counterpart. We are able to identify a series of small correlations between the coupling in the dark sector and halo spin, triaxiality and virialization ratio. When looking at spin and virialization of dark matter haloes, we find a weak (5 per cent) but systematic deviation in fifth force scenarios from ΛCDM.
A modified procedure for mixture-model clustering of regional geochemical data
Ellefsen, Karl J.; Smith, David B.; Horton, John D.
2014-01-01
A modified procedure is proposed for mixture-model clustering of regional-scale geochemical data. The key modification is the robust principal component transformation of the isometric log-ratio transforms of the element concentrations. This principal component transformation and the associated dimension reduction are applied before the data are clustered. The principal advantage of this modification is that it significantly improves the stability of the clustering. The principal disadvantage is that it requires subjective selection of the number of clusters and the number of principal components. To evaluate the efficacy of this modified procedure, it is applied to soil geochemical data that comprise 959 samples from the state of Colorado (USA) for which the concentrations of 44 elements are measured. The distributions of element concentrations that are derived from the mixture model and from the field samples are similar, indicating that the mixture model is a suitable representation of the transformed geochemical data. Each cluster and the associated distributions of the element concentrations are related to specific geologic and anthropogenic features. In this way, mixture model clustering facilitates interpretation of the regional geochemical data.
NASA Technical Reports Server (NTRS)
Maynard, Nelson C.
2004-01-01
Our analysis concerns macro and meso-scale aspects of coupling between the IMF and the magnetosphere-ionosphere system, as opposed to the microphysics of determining how electron gyrotropy is broken and merging actually occurs. We correlate observed behaviors at Cluster and at Polar with temporal variations in other regions, such as in the ionosphere as measured by SuperDARN. Addressing problems with simultaneous observations from diverse locations properly constrains our interpretations.
Technical structure of the global nanoscience and nanotechnology literature
NASA Astrophysics Data System (ADS)
Kostoff, Ronald N.; Koytcheff, Raymond G.; Lau, Clifford G. Y.
2007-10-01
Text mining was used to extract technical intelligence from the open source global nanotechnology and nanoscience research literature. An extensive nanotechnology/nanoscience-focused query was applied to the Science Citation Index/Social Science Citation Index (SCI/SSCI) databases. The nanotechnology/nanoscience research literature technical structure (taxonomy) was obtained using computational linguistics/document clustering and factor analysis. The infrastructure (prolific authors, key journals/institutions/countries, most cited authors/journals/documents) for each of the clusters generated by the document clustering algorithm was obtained using bibliometrics. Another novel addition was the use of phrase auto-correlation maps to show technical thrust areas based on phrase co-occurrence in Abstracts, and the use of phrase-phrase cross-correlation maps to show technical thrust areas based on phrase relations due to the sharing of common co-occurring phrases. The ˜400 most cited nanotechnology papers since 1991 were grouped, and their characteristics generated. Whereas the main analysis provided technical thrusts of all nanotechnology papers retrieved, analysis of the most cited papers allowed their characteristics to be displayed. Finally, most cited papers from selected time periods were extracted, along with all publications from those time periods, and the institutions and countries were compared based on their representation in the most cited documents list relative to their representation in the most publications list.
Functional Plasticity in the Absence of Structural Change.
Krasovsky, Tal; Landa, Jana; Bar, Orly; Jaana, Ahonniska-Assa; Livny, Abigail; Tsarfaty, Galia; Silberg, Tamar
2017-04-01
This work presents a case of a young woman with apraxia and a severe body scheme disorder, 10 years after a childhood frontal and occipitoparietal brain injury. Despite specific limitations, she is independent in performing all activities of daily living. A battery of tests was administered to evaluate praxis and body representations. Specifically, the Hand Laterality Test was used to compare RS's dynamic body representation to that of healthy controls (N = 14). Results demonstrated RS's severe praxis impairment, and the Hand Laterality Test revealed deficits in accuracy and latency of motor imagery, suggesting a significant impairment in dynamic body representation. However, semantic and structural body representations were intact. These results, coupled with frequent use of verbalizations as a strategy, suggest a possible ventral compensatory mechanism (top-down processing) for dorsal stream deficits, which may explain RS's remarkable recovery of activities of daily living. The link between praxis and dynamic body representation is discussed.
Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.; ...
2016-09-07
CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil–canopy processes by introducing an alternative hydrology model with amore » physically accurate representation of coupled energy and water fluxes at the soil–air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Here, marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.« less
NASA Astrophysics Data System (ADS)
Osuský, F.; Bahdanovich, R.; Farkas, G.; Haščík, J.; Tikhomirov, G. V.
2017-01-01
The paper is focused on development of the coupled neutronics-thermal hydraulics model for the Gas-cooled Fast Reactor. It is necessary to carefully investigate coupled calculations of new concepts to avoid recriticality scenarios, as it is not possible to ensure sub-critical state for a fast reactor core under core disruptive accident conditions. Above mentioned calculations are also very suitable for development of new passive or inherent safety systems that can mitigate the occurrence of the recriticality scenarios. In the paper, the most promising fuel material compositions together with a geometry model are described for the Gas-cooled fast reactor. Seven fuel pin and fuel assembly geometry is proposed as a test case for coupled calculation with three different enrichments of fissile material in the form of Pu-UC. The reflective boundary condition is used in radial directions of the test case and vacuum boundary condition is used in axial directions. During these condition, the nuclear system is in super-critical state and to achieve a stable state (which is numerical representation of operational conditions) it is necessary to decrease the reactivity of the system. The iteration scheme is proposed, where SCALE code system is used for collapsing of a macroscopic cross-section into few group representation as input for coupled code NESTLE.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.
CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil–canopy processes by introducing an alternative hydrology model with amore » physically accurate representation of coupled energy and water fluxes at the soil–air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Here, marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.« less
NASA Astrophysics Data System (ADS)
Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.; Harman, Ian N.
2016-09-01
CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil-canopy processes by introducing an alternative hydrology model with a physically accurate representation of coupled energy and water fluxes at the soil-air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Xiaolei, E-mail: virtualzx@gmail.com; Yarkony, David R., E-mail: yarkony@jhu.edu
2016-01-14
In this work, we demonstrate that for moderate sized systems, here a system with 13 atoms, global coupled potential energy surfaces defined for several electronic states over a wide energy range and for distinct regions of nuclear coordinate space characterized by distinct electron configurations, can be constructed with precise energetics and an excellent description of non-adiabatic interactions in all regions. This is accomplished using a recently reported algorithm for constructing quasi-diabatic representations, H{sup d}, of adiabatic electronic states coupled by conical intersections. In this work, the algorithm is used to construct an H{sup d} to describe the photodissociation of phenolmore » from its first and second excited electronic states. The representation treats all 33 internal degrees of freedom in an even handed manner. The ab initio adiabatic electronic structure data used to construct the fit are obtained exclusively from multireference configuration interaction with single and double excitation wave functions comprised of 88 × 10{sup 6} configuration state functions, at geometries determined by quasi-classical trajectories. Since the algorithm uses energy gradients and derivative couplings in addition to electronic energies to construct H{sup d}, data at only 7379 nuclear configurations are required to construct a representation, which describes all nuclear configurations involved in H atom photodissociation to produce the phenoxyl radical in its ground or first excited electronic state, with a mean unsigned energy error of 202.9 cm{sup −1} for electronic energies <60 000 cm{sup −1}.« less
Identification of deficiencies in seasonal rainfall simulated by CMIP5 climate models
NASA Astrophysics Data System (ADS)
Dunning, Caroline M.; Allan, Richard P.; Black, Emily
2017-11-01
An objective technique for analysing seasonality, in terms of regime, progression and timing of the wet seasons, is applied in the evaluation of CMIP5 simulations across continental Africa. Atmosphere-only and coupled integrations capture the gross observed patterns of seasonal progression and give mean onset/cessation dates within 18 days of the observational dates for 11 of the 13 regions considered. Accurate representation of seasonality over central-southern Africa and West Africa (excluding the southern coastline) adds credence for future projected changes in seasonality here. However, coupled simulations exhibit timing biases over the Horn of Africa, with the long rains 20 days late on average. Although both sets of simulations detect biannual rainfall seasonal cycles for East and Central Africa, coupled simulations fail to capture the biannual regime over the southern West African coastline. This is linked with errors in the Gulf of Guinea sea surface temperature (SST) and deficient representation of the SST/rainfall relationship.
Optical potential from first principles
Rotureau, J.; Danielewicz, P.; Hagen, G.; ...
2017-02-15
Here, we develop a method to construct a microscopic optical potential from chiral interactions for nucleon-nucleus scattering. The optical potential is constructed by combining the Green’s function approach with the coupled-cluster method. To deal with the poles of the Green’s function along the real energy axis we employ a Berggren basis in the complex energy plane combined with the Lanczos method. Using this approach, we perform a proof-of-principle calculation of the optical potential for the elastic neutron scattering on 16O. For the computation of the ground-state of 16O, we use the coupled-cluster method in the singles-and-doubles approximation, while for themore » A ±1 nuclei we use particle-attached/removed equation-of-motion method truncated at two-particle-one-hole and one-particle-two-hole excitations, respectively. We verify the convergence of the optical potential and scattering phase shifts with respect to the model-space size and the number of discretized complex continuum states. We also investigate the absorptive component of the optical potential (which reflects the opening of inelastic channels) by computing its imaginary volume integral and find an almost negligible absorptive component at low-energies. To shed light on this result, we computed excited states of 16O using equation-of-motion coupled-cluster method with singles-and- doubles excitations and we found no low-lying excited states below 10 MeV. Furthermore, most excited states have a dominant two-particle-two-hole component, making higher-order particle-hole excitations necessary to achieve a precise description of these core-excited states. We conclude that the reduced absorption at low-energies can be attributed to the lack of correlations coming from the low-order cluster truncation in the employed coupled-cluster method.« less
Alignment and integration of complex networks by hypergraph-based spectral clustering
NASA Astrophysics Data System (ADS)
Michoel, Tom; Nachtergaele, Bruno
2012-11-01
Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.
Alignment and integration of complex networks by hypergraph-based spectral clustering.
Michoel, Tom; Nachtergaele, Bruno
2012-11-01
Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.
NASA Astrophysics Data System (ADS)
Nikoobakht, Behnam; Siebert, Max; Pernpointner, Markus
2015-11-01
In this work, we readdress the photoelectron spectra of the HM(CO)5, (M=Mn, Re) carbonyl complexes by applying four-component Fock-space coupled cluster (FSCC) methods for their calculation in order to extend earlier studies based on less demanding approaches. The final-state characterisation was based on group theoretical considerations of the contributing orbitals and allowed for an unambiguous assignment. Energy level diagrams show the effect of spin-orbit (SO) coupling starting from scalar relativistic results and for the heavy representative HRe(CO)5 nonadditivity effects of SO and electron correlation can be observed requiring a consistent treatment of both contributions.
NASA Astrophysics Data System (ADS)
Curcic, M.; Chen, S. S.
2016-02-01
The atmosphere and ocean are coupled through momentum, enthalpy, and mass fluxes. Accurate representation of these fluxes in a wide range of weather and climate conditions is one of major challenges in prediction models. Their current parameterizations are based on sparse observations in low-to-moderate winds and are not suited for high wind conditions such as tropical cyclones (TCs) and winter storms. In this study, we use the Unified Wave INterface - Coupled Model (UWIN-CM), a high resolution, fully-coupled atmosphere-wave-ocean model, to better understand the role of ocean surface waves in mediating air-sea momentum and enthalpy exchange in TCs. In particular, we focus on the explicit treatment of wave growth and dissipation for calculating atmospheric and oceanic stress, and its role in upper ocean mixing and surface cooling in the wake of the storm. Wind-wave misalignment and local wave disequilibrium result in difference between atmospheric and oceanic stress being largest on the left side of the storm. We find that explicit wave calculation in the coupled model reduces momentum transfer into the ocean by more than 10% on average, resulting in reduced cooling in TC's wake and subsequent weakening of the storm. We also investigate the impacts of sea surface temperature and upper ocean parameterization on air-sea enthalpy fluxes in the fully coupled model. High-resolution UWIN-CM simulations of TCs with various intensities and structure are conducted in this study to better understand the complex TC-ocean interaction and improve the representation of air-sea coupling processes in coupled prediction models.
Measurement of entanglement entropy in the two-dimensional Potts model using wavelet analysis.
Tomita, Yusuke
2018-05-01
A method is introduced to measure the entanglement entropy using a wavelet analysis. Using this method, the two-dimensional Haar wavelet transform of a configuration of Fortuin-Kasteleyn (FK) clusters is performed. The configuration represents a direct snapshot of spin-spin correlations since spin degrees of freedom are traced out in FK representation. A snapshot of FK clusters loses image information at each coarse-graining process by the wavelet transform. It is shown that the loss of image information measures the entanglement entropy in the Potts model.
Grissa, Ibtissem; Vergnaud, Gilles; Pourcel, Christine
2009-01-01
Clustered regularly interspaced short palindromic repeats (CRISPRs) are DNA sequences composed of a succession of repeats (23- to 47-bp long) separated by unique sequences called spacers. Polymorphism can be observed in different strains of a species and may be used for genotyping. We describe protocols and bioinformatics tools that allow the identification of CRISPRs from sequenced genomes, their comparison, and their component determination (the direct repeats and the spacers). A schematic representation of the spacer organization can be produced, allowing an easy comparison between strains.
Cooperative Jahn-Teller phase transition of icosahedral molecular units
NASA Astrophysics Data System (ADS)
Nasrollahi, Seyed H.; Vvedensky, Dimitri D.
2017-02-01
Non-linear molecules undergo distortions when the orbital degeneracy of the highest occupied level is lifted by the Jahn-Teller effect. If such molecules or clusters of atoms are coupled to one another, the system may experience a cooperative Jahn-Teller effect (CJTE). In this paper, we describe a model of how the CJTE leads to the crystallization of the disordered phase. The model Hamiltonian is based on a normal mode decomposition of the clusters in order to maintain the symmetry labels. We take account of the electron-strain and the electron-phonon couplings and, by displacing the coordinates of the oscillators, obtain a term that explicitly couples the Jahn-Teller centers, enabling us to perform a mean-field analysis. The calculation of the free energy then becomes straightforward, and obtaining phase diagrams in various regimes follows from the minimization of this free energy. The results show that the character of the phase transition may change from strong to weak first order and even to second-order, depending on the coupling to the vibrational modes. Taken together, these results may serve as a paradigm for crystallization near the transition temperature, where the atoms tend to form clusters of icosahedral symmetry.
Scholarly Publishing's Gender Gap
ERIC Educational Resources Information Center
Wilson, Robin
2012-01-01
Although the percentage of female authors is still less than women's overall representation within the full-time faculty ranks, researchers found that the proportion has increased as more women have entered the professoriate. They also found that women cluster into certain subfields and are somewhat underrepresented in the prestigious position of…
Dutta, Achintya Kumar; Dar, Manzoor; Vaval, Nayana; Pal, Sourav
2014-02-27
We report a comparative single-reference and multireference coupled-cluster investigation on the structure, potential energy surface, and IR spectroscopic properties of the trans peroxo nitrate radical, one of the key intermediates in stratospheric NOX chemistry. The previous single-reference ab initio studies predicted an unbound structure for the trans peroxo nitrate radical. However, our Fock space multireference coupled-cluster calculation confirms a bound structure for the trans peroxo nitrate radical, in accordance with the experimental results reported earlier. Further, the analysis of the potential energy surface in FSMRCC method indicates a well-behaved minima, contrary to the shallow minima predicted by the single-reference coupled-cluster method. The harmonic force field analysis, of various possible isomers of peroxo nitrate also reveals that only the trans structure leads to the experimentally observed IR peak at 1840 cm(-1). The present study highlights the critical importance of nondynamic correlation in predicting the structure and properties of high-energy stratospheric NOx radicals.
NASA Astrophysics Data System (ADS)
Sørensen, L. K.; Fleig, T.; Olsen, J.
2009-08-01
Aimed at obtaining complete and highly accurate potential energy surfaces for molecules containing heavy elements, we present a new general-order coupled cluster method which can be applied in the framework of the spin-free Dirac formalism. As an initial application we present a systematic study of electron correlation and relativistic effects on the spectroscopic and electric properties of the LiCs molecule in its electronic ground state. In particular, we closely investigate the importance of excitations higher than coupled cluster doubles, spin-free and spin-dependent relativistic effects and the correlation of outer-core electrons on the equilibrium bond length, the harmonic vibrational frequency, the dissociation energy, the dipole moment and the static electric dipole polarizability. We demonstrate that our new implementation allows for highly accurate calculations not only in the bonding region but also along the complete potential curve. The quality of our results is demonstrated by a vibrational analysis where an almost complete set of vibrational levels has been calculated accurately.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peng, Bo; Govind, Niranjan; Aprà, Edoardo
In this paper we apply equation-of-motion coupled cluster (EOMCC) methods in studies of vertical ionization potentials (IP) and electron affinities (EA) for sin- gled walled carbon nanotubes. EOMCC formulations for ionization potentials and electron affinities employing excitation manifolds spanned by single and double ex- citations (IP/EA-EOMCCSD) are used to study IPs and EAs of nanotubes as a function of nanotube length. Several armchair nanotubes corresponding to C20nH20 models with n = 2 - 6 have been used in benchmark calculations. In agreement with previous studies, we demonstrate that the electronegativity of C20nH20 systems remains, to a large extent, independent ofmore » nanotube length. We also compare IP/EA- EOMCCSD results with those obtained with the coupled cluster models with single and double excitations corrected by perturbative triples, CCSD(T), and density func- tional theory (DFT) using global and range-separated hybrid exchange-correlation functionals.« less
Dutta, Achintya Kumar; Vaval, Nayana; Pal, Sourav
2015-01-28
We propose a new elegant strategy to implement third order triples correction in the light of many-body perturbation theory to the Fock space multi-reference coupled cluster method for the ionization problem. The computational scaling as well as the storage requirement is of key concerns in any many-body calculations. Our proposed approach scales as N(6) does not require the storage of triples amplitudes and gives superior agreement over all the previous attempts made. This approach is capable of calculating multiple roots in a single calculation in contrast to the inclusion of perturbative triples in the equation of motion variant of the coupled cluster theory, where each root needs to be computed in a state-specific way and requires both the left and right state vectors together. The performance of the newly implemented scheme is tested by applying to methylene, boron nitride (B2N) anion, nitrogen, water, carbon monoxide, acetylene, formaldehyde, and thymine monomer, a DNA base.
Bridging single and multireference coupled cluster theories with universal state selective formalism
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bhaskaran-Nair, Kiran; Kowalski, Karol
2013-05-28
The universal state selective (USS) multireference approach is used to construct new energy functionals which offers a unique possibility of bridging single and multireference coupled cluster theories (SR/MRCC). These functionals, which can be used to develop iterative and non-iterative approaches, utilize a special form of the trial wavefunctions, which assure additive separability (or size-consistency) of the USS energies in the non-interacting subsystem limit. When the USS formalism is combined with approximate SRCC theories, the resulting formalism can be viewed as a size-consistent version of the method of moments of coupled cluster equations (MMCC) employing a MRCC trial wavefunction. Special casesmore » of the USS formulations, which utilize single reference state specific CC (V.V. Ivanov, D.I. Lyakh, L. Adamowicz, Phys. Chem. Chem. Phys. 11, 2355 (2009)) and tailored CC (T. Kinoshita, O. Hino, R.J. Bartlett, J. Chem. Phys. 123, 074106 (2005)) expansions are also discussed.« less
Testing chameleon gravity with the Coma cluster
DOE Office of Scientific and Technical Information (OSTI.GOV)
Terukina, Ayumu; Yamamoto, Kazuhiro; Lombriser, Lucas
2014-04-01
We propose a novel method to test the gravitational interactions in the outskirts of galaxy clusters. When gravity is modified, this is typically accompanied by the introduction of an additional scalar degree of freedom, which mediates an attractive fifth force. The presence of an extra gravitational coupling, however, is tightly constrained by local measurements. In chameleon modifications of gravity, local tests can be evaded by employing a screening mechanism that suppresses the fifth force in dense environments. While the chameleon field may be screened in the interior of the cluster, its outer region can still be affected by the extramore » force, introducing a deviation between the hydrostatic and lensing mass of the cluster. Thus, the chameleon modification can be tested by combining the gas and lensing measurements of the cluster. We demonstrate the operability of our method with the Coma cluster, for which both a lensing measurement and gas observations from the X-ray surface brightness, the X-ray temperature, and the Sunyaev-Zel'dovich effect are available. Using the joint observational data set, we perform a Markov chain Monte Carlo analysis of the parameter space describing the different profiles in both the Newtonian and chameleon scenarios. We report competitive constraints on the chameleon field amplitude and its coupling strength to matter. In the case of f(R) gravity, corresponding to a specific choice of the coupling, we find an upper bound on the background field amplitude of |f{sub R0}| < 6 × 10{sup −5}, which is currently the tightest constraint on cosmological scales.« less
Magnetic resonance brain tissue segmentation based on sparse representations
NASA Astrophysics Data System (ADS)
Rueda, Andrea
2015-12-01
Segmentation or delineation of specific organs and structures in medical images is an important task in the clinical diagnosis and treatment, since it allows to characterize pathologies through imaging measures (biomarkers). In brain imaging, segmentation of main tissues or specific structures is challenging, due to the anatomic variability and complexity, and the presence of image artifacts (noise, intensity inhomogeneities, partial volume effect). In this paper, an automatic segmentation strategy is proposed, based on sparse representations and coupled dictionaries. Image intensity patterns are singly related to tissue labels at the level of small patches, gathering this information in coupled intensity/segmentation dictionaries. This dictionaries are used within a sparse representation framework to find the projection of a new intensity image onto the intensity dictionary, and the same projection can be used with the segmentation dictionary to estimate the corresponding segmentation. Preliminary results obtained with two publicly available datasets suggest that the proposal is capable of estimating adequate segmentations for gray matter (GM) and white matter (WM) tissues, with an average overlapping of 0:79 for GM and 0:71 for WM (with respect to original segmentations).
Gainotti, Guido; Ciaraffa, Francesca; Silveri, Maria Caterina; Marra, Camillo
2009-11-01
According to the "sensory-motor model of semantic knowledge," different categories of knowledge differ for the weight that different "sources of knowledge" have in their representation. Our study aimed to evaluate this model, checking if subjective evaluations given by normal subjects confirm the different weight that various sources of knowledge have in the representation of different biological and artifact categories and of unique entities, such as famous people or monuments. Results showed that the visual properties are considered as the main source of knowledge for all the living and nonliving categories (as well as for unique entities), but that the clustering of these "sources of knowledge" is different for biological and artifacts categories. Visual data are, indeed, mainly associated with other perceptual (auditory, olfactory, gustatory, and tactual) attributes in the mental representation of living beings and unique entities, whereas they are associated with action-related properties and tactile information in the case of artifacts.
How well do CMIP5 models simulate the low-level jet in western Colombia?
NASA Astrophysics Data System (ADS)
Sierra, Juan P.; Arias, Paola A.; Vieira, Sara C.; Agudelo, Jhoana
2017-11-01
The Choco jet is an important atmospheric feature of Colombian and northern South America hydro-climatology. This work assesses the ability of 26 coupled and 11 uncoupled (AMIP) global climate models (GCMs) included in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) archive to simulate the climatological basic features (annual cycle, spatial distribution and vertical structure) of this jet. Using factor and cluster analysis, we objectively classify models in Best, Worst, and Intermediate groups. Despite the coarse resolution of the GCMs, this study demonstrates that nearly all models can represent the existence of the Choco low-level jet. AMIP and Best models present a more realistic simulation of jet. Worst models exhibit biases such as an anomalous southward location of the Choco jet during the whole year and a shallower jet. The model skill to represent this jet comes from their ability to reproduce some of its main causes, such as the temperature and pressure differences between particular regions in the eastern Pacific and western Colombian lands, which are non-local features. Conversely, Worst models considerably underestimate temperature and pressure differences between these key regions. We identify a close relationship between the location of the Choco jet and the Inter-tropical Convergence Zone (ITCZ), and CMIP5 models are able to represent such relationship. Errors in Worst models are related with bias in the location of the ITCZ over the eastern tropical Pacific Ocean, as well as the representation of the topography and the horizontal resolution.
NASA Astrophysics Data System (ADS)
Li, Hui; Sriver, Ryan L.
2018-01-01
High-resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC-climate studies. Active air-sea coupling in a coupled model framework is essential to capturing TC-ocean interactions, which can influence TC-climate connections on interannual to decadal time scales. Here we investigate how the choices of ocean coupling can affect the directly simulated TCs using high-resolution configurations of the Community Earth System Model (CESM). We performed a suite of high-resolution, multidecadal, global-scale CESM simulations in which the atmosphere (˜0.25° grid spacing) is configured with three different levels of ocean coupling: prescribed climatological sea surface temperature (SST) (ATM), mixed layer ocean (SLAB), and dynamic ocean (CPL). We find that different levels of ocean coupling can influence simulated TC frequency, geographical distributions, and storm intensity. ATM simulates more storms and higher overall storm intensity than the coupled simulations. It also simulates higher TC track density over the eastern Pacific and the North Atlantic, while TC tracks are relatively sparse within CPL and SLAB for these regions. Storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large-scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air-sea interactions. Results help to improve our understanding about the representation of TCs in high-resolution coupled Earth system models, with important implications for TC-climate applications.
Computational Studies of Magnetically Doped Semiconductor Nanoclusters
NASA Astrophysics Data System (ADS)
Gutsev, Lavrenty Gennady
Spin-polarized unrestricted density functional theory is used to calculate the molecular properties of magnetic semiconductor quantum dots doped with 3d-metal atoms. We calculate total energies of the low spin antiferromagnetically coupled states using a spin-flipping algorithm leading to the broken-symmetry states. Given the novel nature of the materials studied, we simulate experimental observables such as hyperfine couplings, ionization/ energies, electron affinities, first and second order polarizabilities, band gaps and exchange coupling constants. Specifically, we begin our investigation with pure clusters of (CdSe )16 and demonstrate the dependence of molecular observables on geometrical structures. We also show that the many isomers of this cluster are energetically quite closely spaced, and thus it would be necessary to employ a battery of tests to experimentally distinguish them. Next, we discuss Mn-doping into the cage (CdSe)9 cluster as well as the zinc-blende stacking type cluster (CdSe)36. We show that the local exchange coupling mechanism is ligand-mediated superexchange and simulate the isotropic hyperfine constants. Finally, we discuss a novel study where (CdSe)9 is doped with Mn or Fe up to a full replacement of all the Cd's and discuss the transition points for the magnetic behavior and specifically the greatly differing band-gap shifts. We also outline an unexpected pattern in the polarizability of the material as metals are added and compare our results with the results from theoretical studies of the bulk material.
Charlet, J; Darmoni, S J
2015-08-13
To summarize the best papers in the field of Knowledge Representation and Management (KRM). A comprehensive review of medical informatics literature was performed to select some of the most interesting papers of KRM published in 2014. Four articles were selected, two focused on annotation and information retrieval using an ontology. The two others focused mainly on ontologies, one dealing with the usage of a temporal ontology in order to analyze the content of narrative document, one describing a methodology for building multilingual ontologies. Semantic models began to show their efficiency, coupled with annotation tools.
Wave failure at strong coupling in intracellular C a2 + signaling system with clustered channels
NASA Astrophysics Data System (ADS)
Li, Xiang; Wu, Yuning; Gao, Xuejuan; Cai, Meichun; Shuai, Jianwei
2018-01-01
As an important intracellular signal, C a2 + ions control diverse cellular functions. In this paper, we discuss the C a2 + signaling with a two-dimensional model in which the inositol 1,4,5-trisphosphate (I P3 ) receptor channels are distributed in clusters on the endoplasmic reticulum membrane. The wave failure at large C a2 + diffusion coupling is discussed in detail in the model. We show that with varying model parameters the wave failure is a robust behavior with either deterministic or stochastic channel dynamics. We suggest that the wave failure should be a general behavior in inhomogeneous diffusing systems with clustered excitable regions and may occur in biological C a2 + signaling systems.
Infrared fixed point of SU(2) gauge theory with six flavors
NASA Astrophysics Data System (ADS)
Leino, Viljami; Rummukainen, Kari; Suorsa, Joni; Tuominen, Kimmo; Tähtinen, Sara
2018-06-01
We compute the running of the coupling in SU(2) gauge theory with six fermions in the fundamental representation of the gauge group. We find strong evidence that this theory has an infrared stable fixed point at strong coupling and measure also the anomalous dimension of the fermion mass operator at the fixed point. This theory therefore likely lies close to the boundary of the conformal window and will display novel infrared dynamics if coupled with the electroweak sector of the Standard Model.
Measuring the representational space of music with fMRI: a case study with Sting.
Levitin, Daniel J; Grafton, Scott T
2016-12-01
Functional brain imaging has revealed much about the neuroanatomical substrates of higher cognition, including music, language, learning, and memory. The technique lends itself to studying of groups of individuals. In contrast, the nature of expert performance is typically studied through the examination of exceptional individuals using behavioral case studies and retrospective biography. Here, we combined fMRI and the study of an individual who is a world-class expert musician and composer in order to better understand the neural underpinnings of his music perception and cognition, in particular, his mental representations for music. We used state of the art multivoxel pattern analysis (MVPA) and representational dissimilarity analysis (RDA) in a fixed set of brain regions to test three exploratory hypotheses with the musician Sting: (1) Composing would recruit neutral structures that are both unique and distinguishable from other creative acts, such as composing prose or visual art; (2) listening and imagining music would recruit similar neural regions, indicating that musical memory shares anatomical substrates with music listening; (3) the MVPA and RDA results would help us to map the representational space for music, revealing which musical pieces and genres are perceived to be similar in the musician's mental models for music. Our hypotheses were confirmed. The act of composing, and even of imagining elements of the composed piece separately, such as melody and rhythm, activated a similar cluster of brain regions, and were distinct from prose and visual art. Listened and imagined music showed high similarity, and in addition, notable similarity/dissimilarity patterns emerged among the various pieces used as stimuli: Muzak and Top 100/Pop songs were far from all other musical styles in Mahalanobis distance (Euclidean representational space), whereas jazz, R&B, tango and rock were comparatively close. Closer inspection revealed principaled explanations for the similarity clusters found, based on key, tempo, motif, and orchestration.
Online Low-Rank Representation Learning for Joint Multi-subspace Recovery and Clustering.
Li, Bo; Liu, Risheng; Cao, Junjie; Zhang, Jie; Lai, Yu-Kun; Liua, Xiuping
2017-10-06
Benefiting from global rank constraints, the lowrank representation (LRR) method has been shown to be an effective solution to subspace learning. However, the global mechanism also means that the LRR model is not suitable for handling large-scale data or dynamic data. For large-scale data, the LRR method suffers from high time complexity, and for dynamic data, it has to recompute a complex rank minimization for the entire data set whenever new samples are dynamically added, making it prohibitively expensive. Existing attempts to online LRR either take a stochastic approach or build the representation purely based on a small sample set and treat new input as out-of-sample data. The former often requires multiple runs for good performance and thus takes longer time to run, and the latter formulates online LRR as an out-ofsample classification problem and is less robust to noise. In this paper, a novel online low-rank representation subspace learning method is proposed for both large-scale and dynamic data. The proposed algorithm is composed of two stages: static learning and dynamic updating. In the first stage, the subspace structure is learned from a small number of data samples. In the second stage, the intrinsic principal components of the entire data set are computed incrementally by utilizing the learned subspace structure, and the low-rank representation matrix can also be incrementally solved by an efficient online singular value decomposition (SVD) algorithm. The time complexity is reduced dramatically for large-scale data, and repeated computation is avoided for dynamic problems. We further perform theoretical analysis comparing the proposed online algorithm with the batch LRR method. Finally, experimental results on typical tasks of subspace recovery and subspace clustering show that the proposed algorithm performs comparably or better than batch methods including the batch LRR, and significantly outperforms state-of-the-art online methods.
An almost trivial gauge theory in the limit of infinite gauge coupling constant.
NASA Astrophysics Data System (ADS)
Kaptanoglu, S.
A local SU(2) gauge theory with one multiplet of scalars in the adjoint representation is considered. In the limit of infinite gauge coupling constant Yang-Mills fields become auxiliary and the action possesses a larger invariance than the usual gauge invariance; hence, the system develops a richer structure of constraints. The constraint analysis is carried out.
Neural representations of kinematic laws of motion: evidence for action-perception coupling.
Dayan, Eran; Casile, Antonino; Levit-Binnun, Nava; Giese, Martin A; Hendler, Talma; Flash, Tamar
2007-12-18
Behavioral and modeling studies have established that curved and drawing human hand movements obey the 2/3 power law, which dictates a strong coupling between movement curvature and velocity. Human motion perception seems to reflect this constraint. The functional MRI study reported here demonstrates that the brain's response to this law of motion is much stronger and more widespread than to other types of motion. Compliance with this law is reflected in the activation of a large network of brain areas subserving motor production, visual motion processing, and action observation functions. Hence, these results strongly support the notion of similar neural coding for motion perception and production. These findings suggest that cortical motion representations are optimally tuned to the kinematic and geometrical invariants characterizing biological actions.
Representational Similarity of Body Parts in Human Occipitotemporal Cortex.
Bracci, Stefania; Caramazza, Alfonso; Peelen, Marius V
2015-09-23
Regions in human lateral and ventral occipitotemporal cortices (OTC) respond selectively to pictures of the human body and its parts. What are the organizational principles underlying body part responses in these regions? Here we used representational similarity analysis (RSA) of fMRI data to test multiple possible organizational principles: shape similarity, physical proximity, cortical homunculus proximity, and semantic similarity. Participants viewed pictures of whole persons, chairs, and eight body parts (hands, arms, legs, feet, chests, waists, upper faces, and lower faces). The similarity of multivoxel activity patterns for all body part pairs was established in whole person-selective OTC regions. The resulting neural similarity matrices were then compared with similarity matrices capturing the hypothesized organizational principles. Results showed that the semantic similarity model best captured the neural similarity of body parts in lateral and ventral OTC, which followed an organization in three clusters: (1) body parts used as action effectors (hands, feet, arms, and legs), (2) noneffector body parts (chests and waists), and (3) face parts (upper and lower faces). Whole-brain RSA revealed, in addition to OTC, regions in parietal and frontal cortex in which neural similarity was related to semantic similarity. In contrast, neural similarity in occipital cortex was best predicted by shape similarity models. We suggest that the semantic organization of body parts in high-level visual cortex relates to the different functions associated with the three body part clusters, reflecting the unique processing and connectivity demands associated with the different types of information (e.g., action, social) different body parts (e.g., limbs, faces) convey. Significance statement: While the organization of body part representations in motor and somatosensory cortices has been well characterized, the principles underlying body part representations in visual cortex have not yet been explored. In the present fMRI study we used multivoxel pattern analysis and representational similarity analysis to characterize the organization of body maps in human occipitotemporal cortex (OTC). Results indicate that visual and shape dimensions do not fully account for the organization of body part representations in OTC. Instead, the representational structure of body maps in OTC appears strongly related to functional-semantic properties of body parts. We suggest that this organization reflects the unique processing and connectivity demands associated with the different types of information different body parts convey. Copyright © 2015 the authors 0270-6474/15/3512977-09$15.00/0.
Finite-Time and Fixed-Time Cluster Synchronization With or Without Pinning Control.
Liu, Xiwei; Chen, Tianping
2018-01-01
In this paper, the finite-time and fixed-time cluster synchronization problem for complex networks with or without pinning control are discussed. Finite-time (or fixed-time) synchronization has been a hot topic in recent years, which means that the network can achieve synchronization in finite-time, and the settling time depends on the initial values for finite-time synchronization (or the settling time is bounded by a constant for any initial values for fixed-time synchronization). To realize the finite-time and fixed-time cluster synchronization, some simple distributed protocols with or without pinning control are designed and the effectiveness is rigorously proved. Several sufficient criteria are also obtained to clarify the effects of coupling terms for finite-time and fixed-time cluster synchronization. Especially, when the cluster number is one, the cluster synchronization becomes the complete synchronization problem; when the network has only one node, the coupling term between nodes will disappear, and the synchronization problem becomes the simplest master-slave case, which also includes the stability problem for nonlinear systems like neural networks. All these cases are also discussed. Finally, numerical simulations are presented to demonstrate the correctness of obtained theoretical results.
Microcavities coupled to multilevel atoms
NASA Astrophysics Data System (ADS)
Schmid, Sandra Isabelle; Evers, Jörg
2011-11-01
A three-level atom in the Λ configuration coupled to a microcavity is studied. The two transitions of the atom are assumed to couple to different counterpropagating mode pairs in the cavity. We analyze the dynamics both in the strong-coupling and the bad-cavity limits. We find that, compared to a two-level setup, the third atomic state and the additional control field modes crucially modify the system dynamics and enable more advanced control schemes. All results are explained using appropriate dressed-state and eigenmode representations. As potential applications, we discuss optical switching and turnstile operations and detection of particles close to the resonator surface.
Human Object-Similarity Judgments Reflect and Transcend the Primate-IT Object Representation
Mur, Marieke; Meys, Mirjam; Bodurka, Jerzy; Goebel, Rainer; Bandettini, Peter A.; Kriegeskorte, Nikolaus
2013-01-01
Primate inferior temporal (IT) cortex is thought to contain a high-level representation of objects at the interface between vision and semantics. This suggests that the perceived similarity of real-world objects might be predicted from the IT representation. Here we show that objects that elicit similar activity patterns in human IT (hIT) tend to be judged as similar by humans. The IT representation explained the human judgments better than early visual cortex, other ventral-stream regions, and a range of computational models. Human similarity judgments exhibited category clusters that reflected several categorical divisions that are prevalent in the IT representation of both human and monkey, including the animate/inanimate and the face/body division. Human judgments also reflected the within-category representation of IT. However, the judgments transcended the IT representation in that they introduced additional categorical divisions. In particular, human judgments emphasized human-related additional divisions between human and non-human animals and between man-made and natural objects. hIT was more similar to monkey IT than to human judgments. One interpretation is that IT has evolved visual-feature detectors that distinguish between animates and inanimates and between faces and bodies because these divisions are fundamental to survival and reproduction for all primate species, and that other brain systems serve to more flexibly introduce species-dependent and evolutionarily more recent divisions. PMID:23525516
McMahon, James M; Pouget, Enrique R; Tortu, Stephanie
2007-06-01
Hepatitis C virus (HCV) is the most common bloodborne pathogen in the United States and is a leading cause of liver-related morbidity and mortality. Although it is known that HCV is most commonly transmitted among injection drug users, the role of sexual transmission in the spread of HCV remains controversial because of inconsistent findings across studies involving heterosexual couples. A novel multilevel modeling technique designed to overcome the limitations of previous research was performed to assess multiple risk factors for HCV while partitioning the source of risk at the individual and couple level. The analysis was performed on risk exposure and HCV screening data obtained from 265 drug-using couples in East Harlem, New York City. In multivariable analysis, significant individual risk factors for HCV included a history of injection drug use, tattooing, and older age. At the couple level, HCV infection tended to cluster within couples, and this interdependence was accounted for by couples' drug-injection behavior. Individual and couple-level sexual behavior was not associated with HCV infection. Our results are consistent with prior research indicating that sexual contact plays little role in HCV transmission. Rather, couples' injection behavior appears to account for the clustering of HCV within heterosexual dyads.
Unaware Processing of Tools in the Neural System for Object-Directed Action Representation.
Tettamanti, Marco; Conca, Francesca; Falini, Andrea; Perani, Daniela
2017-11-01
The hypothesis that the brain constitutively encodes observed manipulable objects for the actions they afford is still debated. Yet, crucial evidence demonstrating that, even in the absence of perceptual awareness, the mere visual appearance of a manipulable object triggers a visuomotor coding in the action representation system including the premotor cortex, has hitherto not been provided. In this fMRI study, we instantiated reliable unaware visual perception conditions by means of continuous flash suppression, and we tested in 24 healthy human participants (13 females) whether the visuomotor object-directed action representation system that includes left-hemispheric premotor, parietal, and posterior temporal cortices is activated even under subliminal perceptual conditions. We found consistent activation in the target visuomotor cortices, both with and without perceptual awareness, specifically for pictures of manipulable versus non-manipulable objects. By means of a multivariate searchlight analysis, we also found that the brain activation patterns in this visuomotor network enabled the decoding of manipulable versus non-manipulable object picture processing, both with and without awareness. These findings demonstrate the intimate neural coupling between visual perception and motor representation that underlies manipulable object processing: manipulable object stimuli specifically engage the visuomotor object-directed action representation system, in a constitutive manner that is independent from perceptual awareness. This perceptuo-motor coupling endows the brain with an efficient mechanism for monitoring and planning reactions to external stimuli in the absence of awareness. SIGNIFICANCE STATEMENT Our brain constantly encodes the visual information that hits the retina, leading to a stimulus-specific activation of sensory and semantic representations, even for objects that we do not consciously perceive. Do these unconscious representations encompass the motor programming of actions that could be accomplished congruently with the objects' functions? In this fMRI study, we instantiated unaware visual perception conditions, by dynamically suppressing the visibility of manipulable object pictures with mondrian masks. Despite escaping conscious perception, manipulable objects activated an object-directed action representation system that includes left-hemispheric premotor, parietal, and posterior temporal cortices. This demonstrates that visuomotor encoding occurs independently of conscious object perception. Copyright © 2017 the authors 0270-6474/17/3710712-13$15.00/0.
NASA Astrophysics Data System (ADS)
Takahashi, A.; Hashimoto, M.; Hu, J. C.; Fukahata, Y.
2017-12-01
Taiwan Island is composed of many geological structures. The main tectonic feature is the collision of the Luzon volcanic arc with the Eurasian continent, which propagates westward and generates complicated crustal deformation. One way to model crustal deformation is to divide Taiwan island into man rigid blocks that moves relatively each other along the boundaries (deformation zones) of the blocks. Since earthquakes tend to occur in the deformation zones, identification of such tectonic boundaries is important. So far, many tectonic boundaries have been proposed on the basis of geology, geomorphology, seismology and geodesy. However, which is the most significant boundary depends on disciplines and there is no way to objectively classify them. Here, we introduce an objective method to identify significant tectonic boundaries with a hierarchical representation proposed by Simpson et al. [2012].We apply a hierarchical agglomerative clustering algorithm to dense GNSS horizontal velocity data in Taiwan. One of the significant merits of the hierarchical representation of the clustering results is that we can consistently explore crustal structures from larger to smaller scales. This is because a higher hierarchy corresponds to a larger crustal structure, and a lower hierarchy corresponds to a smaller crustal structure. Relative motion between clusters can be obtained from this analysis.The first major boundary is identified along the eastern margin of the Longitudinal Valley, which corresponds to the separation of the Philippine Sea plate and the Eurasian continental margin. The second major boundary appears along the Chaochou fault and the Chishan fault in southwestern Taiwan. The third major boundary appears along the eastern margin of the coastal plane. The identified major clusters can be divided into several smaller blocks without losing consistency with geological boundaries. For example, the Fengshun fault, concealed beneath thick sediment layers, is identified. Furthermore, obtained relative motion between clusters demands a reverse fault or a left lateral fault in the off shore of the coastal range.Our clustering based block modeling is consistent with tectonics of Taiwan, implying that observed crustal deformation in Taiwan can be attributed to motion or deformation of shallow structures.
Pattern selection and super-patterns in the bounded confidence model
Ben-Naim, E.; Scheel, A.
2015-10-26
We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes ofmore » the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. Furthermore, the spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.« less
Pattern selection and super-patterns in the bounded confidence model
NASA Astrophysics Data System (ADS)
Ben-Naim, E.; Scheel, A.
2015-10-01
We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.
Using Unsupervised Learning to Unlock the Potential of Hydrologic Similarity
NASA Astrophysics Data System (ADS)
Chaney, N.; Newman, A. J.
2017-12-01
By clustering environmental data into representative hydrologic response units (HRUs), hydrologic similarity aims to harness the covariance between a system's physical environment and its hydrologic response to create reduced-order models. This is the primary approach through which sub-grid hydrologic processes are represented in large-scale models (e.g., Earth System Models). Although the possibilities of hydrologic similarity are extensive, its practical implementations have been limited to 1-d bins of oversimplistic metrics of hydrologic response (e.g., topographic index)—this is a missed opportunity. In this presentation we will show how unsupervised learning is unlocking the potential of hydrologic similarity; clustering methods enable generalized frameworks to effectively and efficiently harness the petabytes of global environmental data to robustly characterize sub-grid heterogeneity in large-scale models. To illustrate the potential that unsupervised learning has towards advancing hydrologic similarity, we introduce a hierarchical clustering algorithm (HCA) that clusters very high resolution (30-100 meters) elevation, soil, climate, and land cover data to assemble a domain's representative HRUs. These HRUs are then used to parameterize the sub-grid heterogeneity in land surface models; for this study we use the GFDL LM4 model—the land component of the GFDL Earth System Model. To explore HCA and its impacts on the hydrologic system we use a ¼ grid cell in southeastern California as a test site. HCA is used to construct an ensemble of 9 different HRU configurations—each configuration has a different number of HRUs; for each ensemble member LM4 is run between 2002 and 2014 with a 26 year spinup. The analysis of the ensemble of model simulations show that: 1) clustering the high-dimensional environmental data space leads to a robust representation of the role of the physical environment in the coupled water, energy, and carbon cycles at a relatively low number of HRUs; 2) the reduced-order model with around 300 HRUs effectively reproduces the fully distributed model simulation (30 meters) with less than 1/1000 of computational expense; 3) assigning each grid cell of the fully distributed grid to an HRU via HCA enables novel visualization methods for large-scale models—this has significant implications for how these models are applied and evaluated. We will conclude by outlining the potential that this work has within operational prediction systems including numerical weather prediction, Earth System models, and Early Warning systems.
Two generalizations of Kohonen clustering
NASA Technical Reports Server (NTRS)
Bezdek, James C.; Pal, Nikhil R.; Tsao, Eric C. K.
1993-01-01
The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.
Dumuid, Dorothea; Olds, T; Lewis, L K; Martin-Fernández, J A; Barreira, T; Broyles, S; Chaput, J-P; Fogelholm, M; Hu, G; Kuriyan, R; Kurpad, A; Lambert, E V; Maia, J; Matsudo, V; Onywera, V O; Sarmiento, O L; Standage, M; Tremblay, M S; Tudor-Locke, C; Zhao, P; Katzmarzyk, P; Gillison, F; Maher, C
2018-02-01
The relationship between children's adiposity and lifestyle behaviour patterns is an area of growing interest. The objectives of this study are to identify clusters of children based on lifestyle behaviours and compare children's adiposity among clusters. Cross-sectional data from the International Study of Childhood Obesity, Lifestyle and the Environment were used. the participants were children (9-11 years) from 12 nations (n = 5710). 24-h accelerometry and self-reported diet and screen time were clustering input variables. Objectively measured adiposity indicators were waist-to-height ratio, percent body fat and body mass index z-scores. sex-stratified analyses were performed on the global sample and repeated on a site-wise basis. Cluster analysis (using isometric log ratios for compositional data) was used to identify common lifestyle behaviour patterns. Site representation and adiposity were compared across clusters using linear models. Four clusters emerged: (1) Junk Food Screenies, (2) Actives, (3) Sitters and (4) All-Rounders. Countries were represented differently among clusters. Chinese children were over-represented in Sitters and Colombian children in Actives. Adiposity varied across clusters, being highest in Sitters and lowest in Actives. Children from different sites clustered into groups of similar lifestyle behaviours. Cluster membership was linked with differing adiposity. Findings support the implementation of activity interventions in all countries, targeting both physical activity and sedentary time. © 2016 World Obesity Federation.
Frickenhaus, Stephan; Kannan, Srinivasaraghavan; Zacharias, Martin
2009-02-01
A direct conformational clustering and mapping approach for peptide conformations based on backbone dihedral angles has been developed and applied to compare conformational sampling of Met-enkephalin using two molecular dynamics (MD) methods. Efficient clustering in dihedrals has been achieved by evaluating all combinations resulting from independent clustering of each dihedral angle distribution, thus resolving all conformational substates. In contrast, Cartesian clustering was unable to accurately distinguish between all substates. Projection of clusters on dihedral principal component (PCA) subspaces did not result in efficient separation of highly populated clusters. However, representation in a nonlinear metric by Sammon mapping was able to separate well the 48 highest populated clusters in just two dimensions. In addition, this approach also allowed us to visualize the transition frequencies between clusters efficiently. Significantly, higher transition frequencies between more distinct conformational substates were found for a recently developed biasing-potential replica exchange MD simulation method allowing faster sampling of possible substates compared to conventional MD simulations. Although the number of theoretically possible clusters grows exponentially with peptide length, in practice, the number of clusters is only limited by the sampling size (typically much smaller), and therefore the method is well suited also for large systems. The approach could be useful to rapidly and accurately evaluate conformational sampling during MD simulations, to compare different sampling strategies and eventually to detect kinetic bottlenecks in folding pathways.
From globally coupled maps to complex-systems biology
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp
Studies of globally coupled maps, introduced as a network of chaotic dynamics, are briefly reviewed with an emphasis on novel concepts therein, which are universal in high-dimensional dynamical systems. They include clustering of synchronized oscillations, hierarchical clustering, chimera of synchronization and desynchronization, partition complexity, prevalence of Milnor attractors, chaotic itinerancy, and collective chaos. The degrees of freedom necessary for high dimensionality are proposed to equal the number in which the combinatorial exceeds the exponential. Future analysis of high-dimensional dynamical systems with regard to complex-systems biology is briefly discussed.
Correlation buildup during recrystallization in three-dimensional dusty plasma clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schella, André; Mulsow, Matthias; Melzer, André
2014-05-15
The recrystallization process of finite three-dimensional dust clouds after laser heating is studied experimentally. The time-dependent Coulomb coupling parameter is presented, showing that the recrystallization starts with an exponential cooling phase where cooling is slower than damping by the neutral gas friction. At later times, the coupling parameter oscillates into equilibrium. It is found that a large fraction of cluster states after recrystallization experiments is in metastable states. The temporal evolution of the correlation buildup shows that correlation occurs on even slower time scale than cooling.
Visual Field Map Clusters in Macaque Extrastriate Visual Cortex
Kolster, Hauke; Mandeville, Joseph B.; Arsenault, John T.; Ekstrom, Leeland B.; Wald, Lawrence L.; Vanduffel, Wim
2009-01-01
The macaque visual cortex contains more than 30 different functional visual areas, yet surprisingly little is known about the underlying organizational principles that structure its components into a complete ‘visual’ unit. A recent model of visual cortical organization in humans suggests that visual field maps are organized as clusters. Clusters minimize axonal connections between individual field maps that represent common visual percepts, with different clusters thought to carry out different functions. Experimental support for this hypothesis, however, is lacking in macaques, leaving open the question of whether it is unique to humans or a more general model for primate vision. Here we show, using high-resolution BOLD fMRI data in the awake monkey at 7 Tesla, that area MT/V5 and its neighbors are organized as a cluster with a common foveal representation and a circular eccentricity map. This novel view on the functional topography of area MT/V5 and satellites indicates that field map clusters are evolutionarily preserved and may be a fundamental organizational principle of the old world primate visual cortex. PMID:19474330
Local matrix learning in clustering and applications for manifold visualization.
Arnonkijpanich, Banchar; Hasenfuss, Alexander; Hammer, Barbara
2010-05-01
Electronic data sets are increasing rapidly with respect to both, size of the data sets and data resolution, i.e. dimensionality, such that adequate data inspection and data visualization have become central issues of data mining. In this article, we present an extension of classical clustering schemes by local matrix adaptation, which allows a better representation of data by means of clusters with an arbitrary spherical shape. Unlike previous proposals, the method is derived from a global cost function. The focus of this article is to demonstrate the applicability of this matrix clustering scheme to low-dimensional data embedding for data inspection. The proposed method is based on matrix learning for neural gas and manifold charting. This provides an explicit mapping of a given high-dimensional data space to low dimensionality. We demonstrate the usefulness of this method for data inspection and manifold visualization. 2009 Elsevier Ltd. All rights reserved.
3D morphology-based clustering and simulation of human pyramidal cell dendritic spines.
Luengo-Sanchez, Sergio; Fernaud-Espinosa, Isabel; Bielza, Concha; Benavides-Piccione, Ruth; Larrañaga, Pedro; DeFelipe, Javier
2018-06-13
The dendritic spines of pyramidal neurons are the targets of most excitatory synapses in the cerebral cortex. They have a wide variety of morphologies, and their morphology appears to be critical from the functional point of view. To further characterize dendritic spine geometry, we used in this paper over 7,000 individually 3D reconstructed dendritic spines from human cortical pyramidal neurons to group dendritic spines using model-based clustering. This approach uncovered six separate groups of human dendritic spines. To better understand the differences between these groups, the discriminative characteristics of each group were identified as a set of rules. Model-based clustering was also useful for simulating accurate 3D virtual representations of spines that matched the morphological definitions of each cluster. This mathematical approach could provide a useful tool for theoretical predictions on the functional features of human pyramidal neurons based on the morphology of dendritic spines.
Ontology-based topic clustering for online discussion data
NASA Astrophysics Data System (ADS)
Wang, Yongheng; Cao, Kening; Zhang, Xiaoming
2013-03-01
With the rapid development of online communities, mining and extracting quality knowledge from online discussions becomes very important for the industrial and marketing sector, as well as for e-commerce applications and government. Most of the existing techniques model a discussion as a social network of users represented by a user-based graph without considering the content of the discussion. In this paper we propose a new multilayered mode to analysis online discussions. The user-based and message-based representation is combined in this model. A novel frequent concept sets based clustering method is used to cluster the original online discussion network into topic space. Domain ontology is used to improve the clustering accuracy. Parallel methods are also used to make the algorithms scalable to very large data sets. Our experimental study shows that the model and algorithms are effective when analyzing large scale online discussion data.
[The destiny of cryopreserved embryos].
Karpel, L; Achour-Frydman, N; Frydman, R; Flis-Trèves, M
2007-12-01
To know the psychological motivations of couples who keep their embryos so long (five years and more) and do not make a decision about them. We studied 84 couples refrained from making a decision on their cryopreserved embryos for at least five years. They were invited to fill out a questionnaire focusing on three points: the reasons of the indecision, their own representation of the cryopreserved embryos and their choice for the future: donation to another couple, to research, pregnancy or no solution for the moment. Mean (S.D.) women's and men's age were respectively, 38.8 (2.5)- and 41.3 (2.5)-years old. On average, three (1-9) embryos are preserved since 7.5 (5-12) years. Most of couples are parents. Four major reasons explain their attitudes: feeling of being too aged (25%), fear of a multiple pregnancy (45%), disagreement between members of couple (20%) and fear of failure (42.5%). Multiple choices were given to the future of the embryos: 25% wanted a pregnancy, 8% wanted to give them to infertile couples, 20% to research and 27.5% did not find any solution. Twenty percent were hesitating. The representation of those embryos is more symbolic than material. Most of the time, they see them like a potential child, a hope for the future or a brother or sister of their alive children. Those embryos are symbolized. They are a proof of fertility, a hope for another child. So, whatever the legal statement, couples will be in a dilemma because it is never easy for an infertile person to renounce to embryos, and the hope for children.
NASA Astrophysics Data System (ADS)
Ding, Xiao-Li; Nieto, Juan J.
2017-11-01
In this paper, we consider the analytical solutions of coupling fractional partial differential equations (FPDEs) with Dirichlet boundary conditions on a finite domain. Firstly, the method of successive approximations is used to obtain the analytical solutions of coupling multi-term time fractional ordinary differential equations. Then, the technique of spectral representation of the fractional Laplacian operator is used to convert the coupling FPDEs to the coupling multi-term time fractional ordinary differential equations. By applying the obtained analytical solutions to the resulting multi-term time fractional ordinary differential equations, the desired analytical solutions of the coupling FPDEs are given. Our results are applied to derive the analytical solutions of some special cases to demonstrate their applicability.
Light clusters and pasta phases in warm and dense nuclear matter
NASA Astrophysics Data System (ADS)
Avancini, Sidney S.; Ferreira, Márcio; Pais, Helena; Providência, Constança; Röpke, Gerd
2017-04-01
The pasta phases are calculated for warm stellar matter in a framework of relativistic mean-field models, including the possibility of light cluster formation. Results from three different semiclassical approaches are compared with a quantum statistical calculation. Light clusters are considered as point-like particles, and their abundances are determined from the minimization of the free energy. The couplings of the light clusters to mesons are determined from experimental chemical equilibrium constants and many-body quantum statistical calculations. The effect of these light clusters on the chemical potentials is also discussed. It is shown that, by including heavy clusters, light clusters are present up to larger nucleonic densities, although with smaller mass fractions.
NASA Astrophysics Data System (ADS)
Jing, Miao; Heße, Falk; Kumar, Rohini; Wang, Wenqing; Fischer, Thomas; Walther, Marc; Zink, Matthias; Zech, Alraune; Samaniego, Luis; Kolditz, Olaf; Attinger, Sabine
2018-06-01
Most large-scale hydrologic models fall short in reproducing groundwater head dynamics and simulating transport process due to their oversimplified representation of groundwater flow. In this study, we aim to extend the applicability of the mesoscale Hydrologic Model (mHM v5.7) to subsurface hydrology by coupling it with the porous media simulator OpenGeoSys (OGS). The two models are one-way coupled through model interfaces GIS2FEM and RIV2FEM, by which the grid-based fluxes of groundwater recharge and the river-groundwater exchange generated by mHM are converted to fixed-flux boundary conditions of the groundwater model OGS. Specifically, the grid-based vertical reservoirs in mHM are completely preserved for the estimation of land-surface fluxes, while OGS acts as a plug-in to the original mHM modeling framework for groundwater flow and transport modeling. The applicability of the coupled model (mHM-OGS v1.0) is evaluated by a case study in the central European mesoscale river basin - Nägelstedt. Different time steps, i.e., daily in mHM and monthly in OGS, are used to account for fast surface flow and slow groundwater flow. Model calibration is conducted following a two-step procedure using discharge for mHM and long-term mean of groundwater head measurements for OGS. Based on the model summary statistics, namely the Nash-Sutcliffe model efficiency (NSE), the mean absolute error (MAE), and the interquartile range error (QRE), the coupled model is able to satisfactorily represent the dynamics of discharge and groundwater heads at several locations across the study basin. Our exemplary calculations show that the one-way coupled model can take advantage of the spatially explicit modeling capabilities of surface and groundwater hydrologic models and provide an adequate representation of the spatiotemporal behaviors of groundwater storage and heads, thus making it a valuable tool for addressing water resources and management problems.
Dalteg, Tomas; Sandberg, Jonas; Malm, Dan; Sandgren, Anna; Benzein, Eva
2017-11-01
To explore illness beliefs in couples where one spouse has atrial fibrillation. Beliefs are the lenses through which we view the world, guiding our behaviour and constructing our lives. Couples evolve an ecology of beliefs from their interaction whereby their actions and choices arise from their beliefs. Atrial fibrillation is a common cardiac arrhythmia that has implications for both patients and partners. A couple's illness beliefs play an important role in convalescence and illness management, and no previous studies have explored illness beliefs in couples living with atrial fibrillation. A qualitative hermeneutic design. Data collection constituted in-depth interviews with nine couples (patient and partner together). Hermeneutic philosophy as described by Gadamer was used to interpret and to understand illness beliefs in couples living with atrial fibrillation. The findings revealed both core illness beliefs and secondary illness beliefs. From the core illness belief 'The heart is a representation of life', two secondary illness beliefs were derived: atrial fibrillation is a threat to life and atrial fibrillation can and must be explained. From the core illness belief 'Change is an integral part of life', two secondary illness beliefs were derived: atrial fibrillation is a disruption in our lives and atrial fibrillation will not interfere with our lives. Finally, from the core illness belief 'Adaptation is fundamental in life', two secondary illness beliefs were derived: atrial fibrillation entails adjustment in daily life and atrial fibrillation entails confidence in and adherence to professional care. Couples' interaction has developed mutual illness beliefs regarding atrial fibrillation that guide them in their daily lives and influence their decisions. The adoption of a family-centred perspective in cardiovascular care settings is warranted. © 2017 John Wiley & Sons Ltd.
Hichri, Echrak; Abriel, Hugues; Kucera, Jan P
2018-02-15
It has been proposed that ephaptic conduction, relying on interactions between the sodium (Na + ) current and the extracellular potential in intercalated discs, might contribute to cardiac conduction when gap junctional coupling is reduced, but this mechanism is still controversial. In intercalated discs, Na + channels form clusters near gap junction plaques, but the functional significance of these clusters has never been evaluated. In HEK cells expressing cardiac Na + channels, we show that restricting the extracellular space modulates the Na + current, as predicted by corresponding simulations accounting for ephaptic effects. In a high-resolution model of the intercalated disc, clusters of Na + channels that face each other across the intercellular cleft facilitate ephaptic impulse transmission when gap junctional coupling is reduced. Thus, our simulations reveal a functional role for the clustering of Na + channels in intercalated discs, and suggest that rearrangement of these clusters in disease may influence cardiac conduction. It has been proposed that ephaptic interactions in intercalated discs, mediated by extracellular potentials, contribute to cardiac impulse propagation when gap junctional coupling is reduced. However, experiments demonstrating ephaptic effects on the cardiac Na + current (I Na ) are scarce. Furthermore, Na + channels form clusters around gap junction plaques, but the electrophysiological significance of these clusters has never been investigated. In patch clamp experiments with HEK cells stably expressing human Na v 1.5 channels, we examined how restricting the extracellular space modulates I Na elicited by an activation protocol. In parallel, we developed a high-resolution computer model of the intercalated disc to investigate how the distribution of Na + channels influences ephaptic interactions. Approaching the HEK cells to a non-conducting obstacle always increased peak I Na at step potentials near the threshold of I Na activation and decreased peak I Na at step potentials far above threshold (7 cells, P = 0.0156, Wilcoxon signed rank test). These effects were consistent with corresponding control simulations with a uniform Na + channel distribution. In the intercalated disc computer model, redistributing the Na + channels into a central cluster of the disc potentiated ephaptic effects. Moreover, ephaptic impulse transmission from one cell to another was facilitated by clusters of Na + channels facing each other across the intercellular cleft when gap junctional coupling was reduced. In conclusion, our proof-of-principle experiments demonstrate that confining the extracellular space modulates cardiac I Na , and our simulations reveal the functional role of the aggregation of Na + channels in the perinexus. These findings highlight novel concepts in the physiology of cardiac excitation. © 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.
Dynamic updating of hippocampal object representations reflects new conceptual knowledge
Mack, Michael L.; Love, Bradley C.; Preston, Alison R.
2016-01-01
Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal. PMID:27803320
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jursenas, Rytis, E-mail: Rytis.Jursenas@tfai.vu.l; Merkelis, Gintaras
2011-01-15
General expressions for the second-order effective atomic Hamiltonian are derived for open-subshell atoms in jj-coupling. The expansion terms are presented as N-body (N=0,1,2,3) effective operators given in the second quantization representation in coupled tensorial form. Two alternative coupled tensorial forms for each expansion term have been developed. To reduce the number of expressions of the effective Hamiltonian, the reduced matrix elements of antisymmetric two-particle wavefunctions are involved in the consideration. The general expressions presented allow the determination of the spin-angular part of expansion terms when studying correlation effects dealing with a number of problems in atomic structure calculations.
Acculturation Stress, Drinking, and Intimate Partner Violence among Hispanic Couples in the U.S
ERIC Educational Resources Information Center
Caetano, Raul; Ramisetty-Mikler, Suhasini; Caetano Vaeth, Patrice A.; Harris, T. Robert
2007-01-01
This article examines the cross-sectional association between acculturation, acculturation stress, drinking, and intimate partner violence (IPV) among Hispanic couples in the U.S. The data being analyzed come from a multi-cluster random household sample of couples interviewed as part of the second wave of a 5-year national longitudinal study. The…
Residence-time framework for modeling multicomponent reactive transport in stream hyporheic zones
NASA Astrophysics Data System (ADS)
Painter, S. L.; Coon, E. T.; Brooks, S. C.
2017-12-01
Process-based models for transport and transformation of nutrients and contaminants in streams require tractable representations of solute exchange between the stream channel and biogeochemically active hyporheic zones. Residence-time based formulations provide an alternative to detailed three-dimensional simulations and have had good success in representing hyporheic exchange of non-reacting solutes. We extend the residence-time formulation for hyporheic transport to accommodate general multicomponent reactive transport. To that end, the integro-differential form of previous residence time models is replaced by an equivalent formulation based on a one-dimensional advection dispersion equation along the channel coupled at each channel location to a one-dimensional transport model in Lagrangian travel-time form. With the channel discretized for numerical solution, the associated Lagrangian model becomes a subgrid model representing an ensemble of streamlines that are diverted into the hyporheic zone before returning to the channel. In contrast to the previous integro-differential forms of the residence-time based models, the hyporheic flowpaths have semi-explicit spatial representation (parameterized by travel time), thus allowing coupling to general biogeochemical models. The approach has been implemented as a stream-corridor subgrid model in the open-source integrated surface/subsurface modeling software ATS. We use bedform-driven flow coupled to a biogeochemical model with explicit microbial biomass dynamics as an example to show that the subgrid representation is able to represent redox zonation in sediments and resulting effects on metal biogeochemical dynamics in a tractable manner that can be scaled to reach scales.
NASA Astrophysics Data System (ADS)
Tao, Guohua
2017-07-01
A general theoretical framework is derived for the recently developed multi-state trajectory (MST) approach from the time dependent Schrödinger equation, resulting in equations of motion for coupled nuclear-electronic dynamics equivalent to Hamilton dynamics or Heisenberg equation based on a new multistate Meyer-Miller (MM) model. The derived MST formalism incorporates both diabatic and adiabatic representations as limiting cases and reduces to Ehrenfest or Born-Oppenheimer dynamics in the mean-field or the single-state limits, respectively. In the general multistate formalism, nuclear dynamics is represented in terms of a set of individual state-specific trajectories, while in the active state trajectory (AST) approximation, only one single nuclear trajectory on the active state is propagated with its augmented images running on all other states. The AST approximation combines the advantages of consistent nuclear-coupled electronic dynamics in the MM model and the single nuclear trajectory in the trajectory surface hopping (TSH) treatment and therefore may provide a potential alternative to both Ehrenfest and TSH methods. The resulting algorithm features in a consistent description of coupled electronic-nuclear dynamics and excellent numerical stability. The implementation of the MST approach to several benchmark systems involving multiple nonadiabatic transitions and conical intersection shows reasonably good agreement with exact quantum calculations, and the results in both representations are similar in accuracy. The AST treatment also reproduces the exact results reasonably, sometimes even quantitatively well, with a better performance in the adiabatic representation.
Qualitative mechanism models and the rationalization of procedures
NASA Technical Reports Server (NTRS)
Farley, Arthur M.
1989-01-01
A qualitative, cluster-based approach to the representation of hydraulic systems is described and its potential for generating and explaining procedures is demonstrated. Many ideas are formalized and implemented as part of an interactive, computer-based system. The system allows for designing, displaying, and reasoning about hydraulic systems. The interactive system has an interface consisting of three windows: a design/control window, a cluster window, and a diagnosis/plan window. A qualitative mechanism model for the ORS (Orbital Refueling System) is presented to coordinate with ongoing research on this system being conducted at NASA Ames Research Center.
Efficient coupling of high intensity short laser pulses into snow clusters
NASA Astrophysics Data System (ADS)
Palchan, T.; Pecker, S.; Henis, Z.; Eisenmann, S.; Zigler, A.
2007-01-01
Measurements of energy absorption of high intensity laser pulses in snow clusters are reported. Targets consisting of sapphire coated with snow nanoparticles were found to absorb more than 95% of the incident light compared to 50% absorption in flat sapphire targets.
Transport properties of dilute α -Fe (X ) solid solutions (X = C, N, O)
NASA Astrophysics Data System (ADS)
Schuler, Thomas; Nastar, Maylise
2016-06-01
We extend the self-consistent mean field (SCMF) method to the calculation of the Onsager matrix of Fe-based interstitial solid solutions. Both interstitial jumps and substitutional atom-vacancy exchanges are accounted for. A general procedure is introduced to split the Onsager matrix of a dilute solid solution into intrinsic cluster Onsager matrices, and extract from them flux-coupling ratios, mobilities, and association-dissociation rates for each cluster. The formalism is applied to vacancy-interstitial solute pairs in α -Fe (V X pairs, X = C, N, O), with ab initio based thermodynamic and kinetic parameters. Convergence of the cluster mobility contribution gives a controlled estimation of the cluster definition distance, taking into account both its thermodynamic and kinetic properties. Then, the flux-coupling behavior of each V X pair is discussed, and qualitative understanding is achieved from the comparison between various contributions to the Onsager matrix. Also, the effect of low-activation energy second-nearest-neighbor interstitial solute jumps around a vacancy on these results is addressed.
Kozai, Toshiya; Yang, Huiran; Ishikuro, Daiki; Seyama, Kaho; Kumagai, Yusuke; Abe, Tadashi; Yamada, Hiroshi; Uchihashi, Takayuki
2018-01-01
Dynamin is a mechanochemical GTPase essential for membrane fission during clathrin-mediated endocytosis. Dynamin forms helical complexes at the neck of clathrin-coated pits and their structural changes coupled with GTP hydrolysis drive membrane fission. Dynamin and its binding protein amphiphysin cooperatively regulate membrane remodeling during the fission, but its precise mechanism remains elusive. In this study, we analyzed structural changes of dynamin-amphiphysin complexes during the membrane fission using electron microscopy (EM) and high-speed atomic force microscopy (HS-AFM). Interestingly, HS-AFM analyses show that the dynamin-amphiphysin helices are rearranged to form clusters upon GTP hydrolysis and membrane constriction occurs at protein-uncoated regions flanking the clusters. We also show a novel function of amphiphysin in size control of the clusters to enhance biogenesis of endocytic vesicles. Our approaches using combination of EM and HS-AFM clearly demonstrate new mechanistic insights into the dynamics of dynamin-amphiphysin complexes during membrane fission. PMID:29357276
Cluster Synchronization of Diffusively Coupled Nonlinear Systems: A Contraction-Based Approach
NASA Astrophysics Data System (ADS)
Aminzare, Zahra; Dey, Biswadip; Davison, Elizabeth N.; Leonard, Naomi Ehrich
2018-04-01
Finding the conditions that foster synchronization in networked nonlinear systems is critical to understanding a wide range of biological and mechanical systems. However, the conditions proved in the literature for synchronization in nonlinear systems with linear coupling, such as has been used to model neuronal networks, are in general not strict enough to accurately determine the system behavior. We leverage contraction theory to derive new sufficient conditions for cluster synchronization in terms of the network structure, for a network where the intrinsic nonlinear dynamics of each node may differ. Our result requires that network connections satisfy a cluster-input-equivalence condition, and we explore the influence of this requirement on network dynamics. For application to networks of nodes with FitzHugh-Nagumo dynamics, we show that our new sufficient condition is tighter than those found in previous analyses that used smooth or nonsmooth Lyapunov functions. Improving the analytical conditions for when cluster synchronization will occur based on network configuration is a significant step toward facilitating understanding and control of complex networked systems.
Beyond Exemplars and Prototypes as Memory Representations of Natural Concepts: A Clustering Approach
ERIC Educational Resources Information Center
Verbeemen, Timothy; Vanpaemel, Wolf; Pattyn, Sven; Storms, Gert; Verguts, Tom
2007-01-01
Categorization in well-known natural concepts is studied using a special version of the Varying Abstraction Framework (Vanpaemel, W., & Storms, G. (2006). A varying abstraction framework for categorization. Manuscript submitted for publication; Vanpaemel, W., Storms, G., & Ons, B. (2005). A varying abstraction model for categorization. In B. Bara,…
Neural Representations Used by Brain Regions Underlying Speech Production
ERIC Educational Resources Information Center
Segawa, Jennifer Anne
2013-01-01
Speech utterances are phoneme sequences but may not always be represented as such in the brain. For instance, electropalatography evidence indicates that as speaking rate increases, gestures within syllables are manipulated separately but those within consonant clusters act as one motor unit. Moreover, speech error data suggest that a syllable's…
Minati, Ludovico
2014-12-01
In this paper, experimental evidence of multiple synchronization phenomena in a large (n = 30) ring of chaotic oscillators is presented. Each node consists of an elementary circuit, generating spikes of irregular amplitude and comprising one bipolar junction transistor, one capacitor, two inductors, and one biasing resistor. The nodes are mutually coupled to their neighbours via additional variable resistors. As coupling resistance is decreased, phase synchronization followed by complete synchronization is observed, and onset of synchronization is associated with partial synchronization, i.e., emergence of communities (clusters). While component tolerances affect community structure, the general synchronization properties are maintained across three prototypes and in numerical simulations. The clusters are destroyed by adding long distance connections with distant notes, but are otherwise relatively stable with respect to structural connectivity changes. The study provides evidence that several fundamental synchronization phenomena can be reliably observed in a network of elementary single-transistor oscillators, demonstrating their generative potential and opening way to potential applications of this undemanding setup in experimental modelling of the relationship between network structure, synchronization, and dynamical properties.
Baudin, Pablo; Bykov, Dmytro; Liakh, Dmitry I.; ...
2017-02-22
Here, the recently developed Local Framework for calculating Excitation energies (LoFEx) is extended to the coupled cluster singles and doubles (CCSD) model. In the new scheme, a standard CCSD excitation energy calculation is carried out within a reduced excitation orbital space (XOS), which is composed of localised molecular orbitals and natural transition orbitals determined from time-dependent Hartree–Fock theory. The presented algorithm uses a series of reduced second-order approximate coupled cluster singles and doubles (CC2) calculations to optimise the XOS in a black-box manner. This ensures that the requested CCSD excitation energies have been determined to a predefined accuracy compared tomore » a conventional CCSD calculation. We present numerical LoFEx-CCSD results for a set of medium-sized organic molecules, which illustrate the black-box nature of the approach and the computational savings obtained for transitions that are local compared to the size of the molecule. In fact, for such local transitions, the LoFEx-CCSD scheme can be applied to molecular systems where a conventional CCSD implementation is intractable.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bozkaya, Uğur, E-mail: ugrbzky@gmail.com
2016-04-14
An efficient implementation of the asymmetric triples correction for the coupled-cluster singles and doubles [ΛCCSD(T)] method [S. A. Kucharski and R. J. Bartlett, J. Chem. Phys. 108, 5243 (1998); T. D. Crawford and J. F. Stanton, Int. J. Quantum Chem. 70, 601 (1998)] with the density-fitting [DF-ΛCCSD(T)] approach is presented. The computational time for the DF-ΛCCSD(T) method is compared with that of ΛCCSD(T). Our results demonstrate that the DF-ΛCCSD(T) method provide substantially lower computational costs than ΛCCSD(T). Further application results show that the ΛCCSD(T) and DF-ΛCCSD(T) methods are very beneficial for the study of single bond breaking problems as wellmore » as noncovalent interactions and transition states. We conclude that ΛCCSD(T) and DF-ΛCCSD(T) are very promising for the study of challenging chemical systems, where the coupled-cluster singles and doubles with perturbative triples method fails.« less
Exploration of dynamical regimes of irradiated small protonated water clusters
NASA Astrophysics Data System (ADS)
Ndongmouo Taffoti, U. F.; Dinh, P. M.; Reinhard, P.-G.; Suraud, E.; Wang, Z. P.
2010-05-01
We explore from a theoretical perspective the dynamical response of small water clusters, (H2O)nH3O+ with n=1,2,3, to a short laser pulse for various frequencies, from infrared (IR) to ultra-violet (UV) and intensities (from 6×10^{13} W/cm^2 to 5×10^{14} W/cm^2). To that end, we use time-dependent local-density approximation for the electrons, coupled to molecular dynamics for the atomic cores (TDLDA-MD). The local-density approximation is augmented by a self-interaction correction (SIC) to allow for a correct description of electron emission. For IR frequencies, we see a direct coupling of the laser field to the very light H+ ions in the clusters. Resonant coupling (in the UV) and/or higher intensities lead to fast ionization with subsequent Coulomb explosion. The stability against Coulomb pressure increases with system size. Excitation to lower ionization stages induced strong ionic vibrations. The latter maintain a rather harmonic pattern in spite of the sizeable amplitudes (often 10% of the bond length).
SU(3) gauge symmetry for collective rotational states in deformed nuclei
NASA Astrophysics Data System (ADS)
Rosensteel, George; Sparks, Nick
2016-09-01
How do deformed nuclei rotate? The qualitative answer is that a velocity-dependent interaction causes a strong coupling between the angular momentum and the vortex momentum (or Kelvin circulation). To achieve a quantitative explanation, we propose a significant extension of the Bohr-Mottelson legacy model in which collective wave functions are vector-valued in an irreducible representation of SU(3). This SU(3) is not the usual Elliott choice, but rather describes internal vorticity in the rotating frame. The circulation values C of an SU(3) irreducible representation, say the (8,0) for 20Ne, are C = 0, 2, 4, 6, 8, which is the same as the angular momentum spectrum in the Elliott model; the reason is a reciprocity theorem in the symplectic model. The differential geometry of Yang-Mills theory provides a natural mathematical framework to solve the angular-vortex coupling riddle. The requisite strong coupling is a ``magnetic-like'' interaction arising from the covariant derivative and the bundle connection. The model builds on prior work about the Yang-Mills SO(3) gauge group model.
Revisiting Kawasaki dynamics in one dimension
NASA Astrophysics Data System (ADS)
Grynberg, M. D.
2010-11-01
Critical exponents of the Kawasaki dynamics in the Ising chain are re-examined numerically through the spectrum gap of evolution operators constructed both in spin and domain-wall representations. At low-temperature regimes the latter provides a rapid finite-size convergence to these exponents, which tend to z≃3.11 for instant quenches under ferromagnetic couplings, while approaching to z≃2 in the antiferro case. The spin representation complements the evaluation of dynamic exponents at higher temperature scales, where the kinetics still remains slow.
NASA Astrophysics Data System (ADS)
Garza, Alejandro J.
Perhaps the most important approximations to the electronic structure problem in quantum chemistry are those based on coupled cluster and density functional theories. Coupled cluster theory has been called the ``gold standard'' of quantum chemistry due to the high accuracy that it achieves for weakly correlated systems. Kohn-Sham density functionals based on semilocal approximations are, without a doubt, the most widely used methods in chemistry and material science because of their high accuracy/cost ratio. The root of the success of coupled cluster and density functionals is their ability to efficiently describe the dynamic part of the electron correlation. However, both traditional coupled cluster and density functional approximations may fail catastrophically when substantial static correlation is present. This severely limits the applicability of these methods to a plethora of important chemical and physical problems such as, e.g., the description of bond breaking, transition states, transition metal-, lanthanide- and actinide-containing compounds, and superconductivity. In an attempt to tackle this problem, nonstandard (single-reference) coupled cluster-based techniques that aim to describe static correlation have been recently developed: pair coupled cluster doubles (pCCD) and singlet-paired coupled cluster doubles (CCD0). The ability to describe static correlation in pCCD and CCD0 comes, however, at the expense of important amounts of dynamic correlation so that the high accuracy of standard coupled cluster becomes unattainable. Thus, the reliable and efficient description of static and dynamic correlation in a simultaneous manner remains an open problem for quantum chemistry and many-body theory in general. In this thesis, different ways to combine pCCD and CCD0 with density functionals in order to describe static and dynamic correlation simultaneously (and efficiently) are explored. The combination of wavefunction and density functional methods has a long history in quantum chemistry (practical implementations have appeared in the literature since the 1970s). However, this kind of techniques have not achieved widespread use due to problems such as double counting of correlation and the symmetry dilemma--the fact that wavefunction methods respect the symmetries of Hamiltonian, while modern functionals are designed to work with broken symmetry densities. Here, particular mathematical features of pCCD and CCD0 are exploited to avoid these problems in an efficient manner. The two resulting families of approximations, denoted as pCCD+DFT and CCD0+DFT, are shown to be able to describe static and dynamic correlation in standard benchmark calculations. Furthermore, it is also shown that CCD0+DFT lends itself to combination with correlation from the direct random phase approximation (dRPA). Inclusion of dRPA in the long-range via the technique of range-separation allows for the description of dispersion correlation, the remaining part of the correlation. Thus, when combined with the dRPA, CCD0+DFT can account for all three-types of electron correlation that are necessary to accurately describe molecular systems. Lastly, applications of CCD0+DFT to actinide chemistry are considered in this work. The accuracy of CCD0+DFT for predicting equilibrium geometries and vibrational frequencies of actinide molecules and ions is assessed and compared to that of well-established quantum chemical methods. For this purpose, the f0 actinyl series (UO2 2+, NpO 23+, PuO24+, the isoelectronic NUN, and Thorium (ThO, ThO2+) and Nobelium (NoO, NoO2) oxides are studied. It is shown that the CCD0+DFT description of these species agrees with available experimental data and is comparable with the results given by the highest-level calculations that are possible for such heavy compounds while being, at least, an order of magnitude lower in computational cost.
Simulation of circularly polarized luminescence spectra using coupled cluster theory
NASA Astrophysics Data System (ADS)
McAlexander, Harley R.; Crawford, T. Daniel
2015-04-01
We report the first computations of circularly polarized luminescence (CPL) rotatory strengths at the equation-of-motion coupled cluster singles and doubles (EOM-CCSD) level of theory. Using a test set of eight chiral ketones, we compare both dipole and rotatory strengths for absorption (electronic circular dichroism) and emission to the results from time-dependent density-functional theory (TD-DFT) and available experimental data for both valence and Rydberg transitions. For two of the compounds, we obtained optimized geometries of the lowest several excited states using both EOM-CCSD and TD-DFT and determined that structures and EOM-CCSD transition properties obtained with each structure were sufficiently similar that TD-DFT optimizations were acceptable for the remaining test cases. Agreement between EOM-CCSD and the Becke three-parameter exchange function and Lee-Yang-Parr correlation functional (B3LYP) corrected using the Coulomb attenuating method (CAM-B3LYP) is typically good for most of the transitions, though agreement with the uncorrected B3LYP functional is significantly worse for all reported properties. The choice of length vs. velocity representation of the electric dipole operator has little impact on the EOM-CCSD transition strengths for nearly all of the states we examined. For a pair of closely related β, γ-enones, (1R)-7-methylenebicyclo[2.2.1]heptan-2-one and (1S)-2-methylenebicyclo[2.2.1]heptan-7-one, we find that EOM-CCSD and CAM-B3LYP agree with the energetic ordering of the two possible excited-state conformations, resulting in good agreement with experimental rotatory strengths in both absorption and emission, whereas B3LYP yields a qualitatively incorrect result for the CPL signal of (1S)-2-methylenebicyclo[2.2.1]heptan-7-one. Finally, we predict that one of the compounds considered here, trans-bicyclo[3.3.0]octane-3,7-dione, is unique in that it exhibits an achiral ground state and a chiral first excited state, leading to a strong CPL signal but a weak circular dichroism signal.
Simulation of circularly polarized luminescence spectra using coupled cluster theory
DOE Office of Scientific and Technical Information (OSTI.GOV)
McAlexander, Harley R.; Crawford, T. Daniel, E-mail: crawdad@vt.edu
2015-04-21
We report the first computations of circularly polarized luminescence (CPL) rotatory strengths at the equation-of-motion coupled cluster singles and doubles (EOM-CCSD) level of theory. Using a test set of eight chiral ketones, we compare both dipole and rotatory strengths for absorption (electronic circular dichroism) and emission to the results from time-dependent density-functional theory (TD-DFT) and available experimental data for both valence and Rydberg transitions. For two of the compounds, we obtained optimized geometries of the lowest several excited states using both EOM-CCSD and TD-DFT and determined that structures and EOM-CCSD transition properties obtained with each structure were sufficiently similar thatmore » TD-DFT optimizations were acceptable for the remaining test cases. Agreement between EOM-CCSD and the Becke three-parameter exchange function and Lee-Yang-Parr correlation functional (B3LYP) corrected using the Coulomb attenuating method (CAM-B3LYP) is typically good for most of the transitions, though agreement with the uncorrected B3LYP functional is significantly worse for all reported properties. The choice of length vs. velocity representation of the electric dipole operator has little impact on the EOM-CCSD transition strengths for nearly all of the states we examined. For a pair of closely related β, γ-enones, (1R)-7-methylenebicyclo[2.2.1]heptan-2-one and (1S)-2-methylenebicyclo[2.2.1]heptan-7-one, we find that EOM-CCSD and CAM-B3LYP agree with the energetic ordering of the two possible excited-state conformations, resulting in good agreement with experimental rotatory strengths in both absorption and emission, whereas B3LYP yields a qualitatively incorrect result for the CPL signal of (1S)-2-methylenebicyclo[2.2.1]heptan-7-one. Finally, we predict that one of the compounds considered here, trans-bicyclo[3.3.0]octane-3,7-dione, is unique in that it exhibits an achiral ground state and a chiral first excited state, leading to a strong CPL signal but a weak circular dichroism signal.« less
NASA Astrophysics Data System (ADS)
Manoylov, Anton; Lebon, Bruno; Djambazov, Georgi; Pericleous, Koulis
2017-11-01
The aerospace and automotive industries are seeking advanced materials with low weight yet high strength and durability. Aluminum and magnesium-based metal matrix composites with ceramic micro- and nano-reinforcements promise the desirable properties. However, larger surface-area-to-volume ratio in micro- and especially nanoparticles gives rise to van der Waals and adhesion forces that cause the particles to agglomerate in clusters. Such clusters lead to adverse effects on final properties, no longer acting as dislocation anchors but instead becoming defects. Also, agglomeration causes the particle distribution to become uneven, leading to inconsistent properties. To break up clusters, ultrasonic processing may be used via an immersed sonotrode, or alternatively via electromagnetic vibration. This paper combines a fundamental study of acoustic cavitation in liquid aluminum with a study of the interaction forces causing particles to agglomerate, as well as mechanisms of cluster breakup. A non-linear acoustic cavitation model utilizing pressure waves produced by an immersed horn is presented, and then applied to cavitation in liquid aluminum. Physical quantities related to fluid flow and quantities specific to the cavitation solver are passed to a discrete element method particles model. The coupled system is then used for a detailed study of clusters' breakup by cavitation.
Information jet: Handling noisy big data from weakly disconnected network
NASA Astrophysics Data System (ADS)
Aurongzeb, Deeder
Sudden aggregation (information jet) of large amount of data is ubiquitous around connected social networks, driven by sudden interacting and non-interacting events, network security threat attacks, online sales channel etc. Clustering of information jet based on time series analysis and graph theory is not new but little work is done to connect them with particle jet statistics. We show pre-clustering based on context can element soft network or network of information which is critical to minimize time to calculate results from noisy big data. We show difference between, stochastic gradient boosting and time series-graph clustering. For disconnected higher dimensional information jet, we use Kallenberg representation theorem (Kallenberg, 2005, arXiv:1401.1137) to identify and eliminate jet similarities from dense or sparse graph.
Devereux, Barry J; Clarke, Alex; Marouchos, Andreas; Tyler, Lorraine K
2013-11-27
Understanding the meanings of words and objects requires the activation of underlying conceptual representations. Semantic representations are often assumed to be coded such that meaning is evoked regardless of the input modality. However, the extent to which meaning is coded in modality-independent or amodal systems remains controversial. We address this issue in a human fMRI study investigating the neural processing of concepts, presented separately as written words and pictures. Activation maps for each individual word and picture were used as input for searchlight-based multivoxel pattern analyses. Representational similarity analysis was used to identify regions correlating with low-level visual models of the words and objects and the semantic category structure common to both. Common semantic category effects for both modalities were found in a left-lateralized network, including left posterior middle temporal gyrus (LpMTG), left angular gyrus, and left intraparietal sulcus (LIPS), in addition to object- and word-specific semantic processing in ventral temporal cortex and more anterior MTG, respectively. To explore differences in representational content across regions and modalities, we developed novel data-driven analyses, based on k-means clustering of searchlight dissimilarity matrices and seeded correlation analysis. These revealed subtle differences in the representations in semantic-sensitive regions, with representations in LIPS being relatively invariant to stimulus modality and representations in LpMTG being uncorrelated across modality. These results suggest that, although both LpMTG and LIPS are involved in semantic processing, only the functional role of LIPS is the same regardless of the visual input, whereas the functional role of LpMTG differs for words and objects.
Cluster-Glass Phase in Pyrochlore X Y Antiferromagnets with Quenched Disorder
NASA Astrophysics Data System (ADS)
Andrade, Eric C.; Hoyos, José A.; Rachel, Stephan; Vojta, Matthias
2018-03-01
We study the impact of quenched disorder (random exchange couplings or site dilution) on easy-plane pyrochlore antiferromagnets. In the clean system, order by disorder selects a magnetically ordered state from a classically degenerate manifold. In the presence of randomness, however, different orders can be chosen locally depending on details of the disorder configuration. Using a combination of analytical considerations and classical Monte Carlo simulations, we argue that any long-range-ordered magnetic state is destroyed beyond a critical level of randomness where the system breaks into magnetic domains due to random exchange anisotropies, becoming, therefore, a glass of spin clusters, in accordance with the available experimental data. These random anisotropies originate from off-diagonal exchange couplings in the microscopic Hamiltonian, establishing their relevance to other magnets with strong spin-orbit coupling.
The Phasor Approach to Fluorescence Lifetime Imaging Analysis
Digman, Michelle A.; Caiolfa, Valeria R.; Zamai, Moreno; Gratton, Enrico
2008-01-01
Changing the data representation from the classical time delay histogram to the phasor representation provides a global view of the fluorescence decay at each pixel of an image. In the phasor representation we can easily recognize the presence of different molecular species in a pixel or the occurrence of fluorescence resonance energy transfer. The analysis of the fluorescence lifetime imaging microscopy (FLIM) data in the phasor space is done observing clustering of pixels values in specific regions of the phasor plot rather than by fitting the fluorescence decay using exponentials. The analysis is instantaneous since is not based on calculations or nonlinear fitting. The phasor approach has the potential to simplify the way data are analyzed in FLIM, paving the way for the analysis of large data sets and, in general, making the FLIM technique accessible to the nonexpert in spectroscopy and data analysis. PMID:17981902
Nishimura, Mayu; Maurer, Daphne; Gao, Xiaoqing
2009-07-01
We explored differences in the mental representation of facial identity between 8-year-olds and adults. The 8-year-olds and adults made similarity judgments of a homogeneous set of faces (individual hair cues removed) using an "odd-man-out" paradigm. Multidimensional scaling (MDS) analyses were performed to represent perceived similarity of faces in a multidimensional space. Five dimensions accounted optimally for the judgments of both children and adults, with similar local clustering of faces. However, the fit of the MDS solutions was better for adults, in part because children's responses were more variable. More children relied predominantly on a single dimension, namely eye color, whereas adults appeared to use multiple dimensions for each judgment. The pattern of findings suggests that children's mental representation of faces has a structure similar to that of adults but that children's judgments are influenced less consistently by that overall structure.
Hydrodynamic effects on β-amyloid (16-22) peptide aggregation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chiricotto, Mara; Sterpone, Fabio, E-mail: fabio.sterpone@ibpc.fr; Melchionna, Simone
Computer simulations based on simplified representations are routinely used to explore the early steps of amyloid aggregation. However, when protein models with implicit solvent are employed, these simulations miss the effect of solvent induced correlations on the aggregation kinetics and lifetimes of metastable states. In this work, we apply the multi-scale Lattice Boltzmann Molecular Dynamics technique (LBMD) to investigate the initial aggregation phases of the amyloid Aβ{sub 16−22} peptide. LBMD includes naturally hydrodynamic interactions (HIs) via a kinetic on-lattice representation of the fluid kinetics. The peptides are represented by the flexible OPEP coarse-grained force field. First, we have tuned themore » essential parameters that control the coupling between the molecular and fluid evolutions in order to reproduce the experimental diffusivity of elementary species. The method is then deployed to investigate the effect of HIs on the aggregation of 100 and 1000 Aβ{sub 16−22} peptides. We show that HIs clearly impact the aggregation process and the fluctuations of the oligomer sizes by favouring the fusion and exchange dynamics of oligomers between aggregates. HIs also guide the growth of the leading largest cluster. For the 100 Aβ{sub 16−22} peptide system, the simulation of ∼300 ns allowed us to observe the transition from ellipsoidal assemblies to an elongated and slightly twisted aggregate involving almost the totality of the peptides. For the 1000 Aβ{sub 16−22} peptides, a system of unprecedented size at quasi-atomistic resolution, we were able to explore a branched disordered fibril-like structure that has never been described by other computer simulations, but has been observed experimentally.« less
Practices and representations of health education among primary school teachers.
Jourdan, Didier; Pommier, Jeanine; Quidu, Frédérique
2010-02-01
School is one of the key settings for health education (HE). The objectives of this study are to assess primary school teachers' self-reported teaching practices in HE and to describe their representation concerning their role in HE. A quantitative study was conducted on a sample of primary school teachers (n = 626) in two French regions in order to analyze their practices and representations in HE. A hierarchical clustering dendogram was performed on questions exploring representations of HE. Multiple linear regression analysis helped explain the motivation and self-perceived competency score. Three quarters of the teachers declare they work in HE. Only one third of them declare they work in a comprehensive HE perspective. The HE approach is often considered in terms of specific unique curriculum intervention. Two thirds of the teachers say they work alone in HE, the other third associate other partners and choose mainly school health services. Parents are rarely (12%) involved in HE initiatives. It is essentially the practice of HE, teacher training and teachers' representation of HE that condition their motivation to develop HE. Teachers can take different approaches to HE. Teachers' representation of HE plays an important role in the development of HE activities: some teachers consider that HE is the mission of the health professionals and the parents. Our expectations of teacher involvement should be realistic, should take into account the representations of their role, the difficulties they encounter, and should be sustained by specific training.
Diabatic Definition of Geometric Phase Effects.
Izmaylov, Artur F; Li, Jiaru; Joubert-Doriol, Loïc
2016-11-08
Electronic wave functions in the adiabatic representation acquire nontrivial geometric phases (GPs) when corresponding potential energy surfaces undergo conical intersection (CI). These GPs have profound effects on the nuclear quantum dynamics and cannot be eliminated in the adiabatic representation without changing the physics of the system. To define dynamical effects arising from the GP presence, the nuclear quantum dynamics of the CI containing system is compared with that of the system with artificially removed GP. We explore a new construction of the system with removed GP via a modification of the diabatic representation for the original CI containing system. Using an absolute value function of diabatic couplings, we remove the GP while preserving adiabatic potential energy surfaces and CI. We assess GP effects in dynamics of a two-dimensional linear vibronic coupling model both for ground and excited state dynamics. Results are compared with those obtained with a conventional removal of the GP by ignoring double-valued boundary conditions of the real electronic wave functions. Interestingly, GP effects appear similar in two approaches only for the low energy dynamics. In contrast with the conventional approach, the new approach does not have substantial GP effects in the ultrafast excited state dynamics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sibaev, M.; Crittenden, D. L., E-mail: deborah.crittenden@canterbury.ac.nz
In this paper, we outline a general, scalable, and black-box approach for calculating high-order strongly coupled force fields in rectilinear normal mode coordinates, based upon constructing low order expansions in curvilinear coordinates with naturally limited mode-mode coupling, and then transforming between coordinate sets analytically. The optimal balance between accuracy and efficiency is achieved by transforming from 3 mode representation quartic force fields in curvilinear normal mode coordinates to 4 mode representation sextic force fields in rectilinear normal modes. Using this reduced mode-representation strategy introduces an error of only 1 cm{sup −1} in fundamental frequencies, on average, across a sizable testmore » set of molecules. We demonstrate that if it is feasible to generate an initial semi-quartic force field in curvilinear normal mode coordinates from ab initio data, then the subsequent coordinate transformation procedure will be relatively fast with modest memory demands. This procedure facilitates solving the nuclear vibrational problem, as all required integrals can be evaluated analytically. Our coordinate transformation code is implemented within the extensible PyPES library program package, at http://sourceforge.net/projects/pypes-lib-ext/.« less
Clusters in nonsmooth oscillator networks
NASA Astrophysics Data System (ADS)
Nicks, Rachel; Chambon, Lucie; Coombes, Stephen
2018-03-01
For coupled oscillator networks with Laplacian coupling, the master stability function (MSF) has proven a particularly powerful tool for assessing the stability of the synchronous state. Using tools from group theory, this approach has recently been extended to treat more general cluster states. However, the MSF and its generalizations require the determination of a set of Floquet multipliers from variational equations obtained by linearization around a periodic orbit. Since closed form solutions for periodic orbits are invariably hard to come by, the framework is often explored using numerical techniques. Here, we show that further insight into network dynamics can be obtained by focusing on piecewise linear (PWL) oscillator models. Not only do these allow for the explicit construction of periodic orbits, their variational analysis can also be explicitly performed. The price for adopting such nonsmooth systems is that many of the notions from smooth dynamical systems, and in particular linear stability, need to be modified to take into account possible jumps in the components of Jacobians. This is naturally accommodated with the use of saltation matrices. By augmenting the variational approach for studying smooth dynamical systems with such matrices we show that, for a wide variety of networks that have been used as models of biological systems, cluster states can be explicitly investigated. By way of illustration, we analyze an integrate-and-fire network model with event-driven synaptic coupling as well as a diffusively coupled network built from planar PWL nodes, including a reduction of the popular Morris-Lecar neuron model. We use these examples to emphasize that the stability of network cluster states can depend as much on the choice of single node dynamics as it does on the form of network structural connectivity. Importantly, the procedure that we present here, for understanding cluster synchronization in networks, is valid for a wide variety of systems in biology, physics, and engineering that can be described by PWL oscillators.
NASA Astrophysics Data System (ADS)
Huang, Jing; Zhou, Yanzi; Xie, Daiqian
2018-04-01
We report a new full-dimensional ab initio potential energy surface for the Ar-HF van der Waals complex at the level of coupled-cluster singles and doubles with noniterative inclusion of connected triples levels [CCSD(T)] using augmented correlation-consistent quintuple-zeta basis set (aV5Z) plus bond functions. Full counterpoise correction was employed to correct the basis-set superposition error. The hypersurface was fitted using artificial neural network method with a root mean square error of 0.1085 cm-1 for more than 8000 ab initio points. The complex was found to prefer a linear Ar-H-F equilibrium structure. The three-dimensional discrete variable representation method and the Lanczos propagation algorithm were then employed to calculate the rovibrational states without separating inter- and intra- molecular nuclear motions. The calculated vibrational energies of Ar-HF differ from the experiment values within about 1 cm-1 on the first four HF vibrational states, and the predicted pure rotational energies on (0000) and (1000) vibrational states are deviated from the observed value by about 1%, which shows the accuracy of our new PES.
The eNanoMapper database for nanomaterial safety information
Chomenidis, Charalampos; Doganis, Philip; Fadeel, Bengt; Grafström, Roland; Hardy, Barry; Hastings, Janna; Hegi, Markus; Jeliazkov, Vedrin; Kochev, Nikolay; Kohonen, Pekka; Munteanu, Cristian R; Sarimveis, Haralambos; Smeets, Bart; Sopasakis, Pantelis; Tsiliki, Georgia; Vorgrimmler, David; Willighagen, Egon
2015-01-01
Summary Background: The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs). Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs. Results: The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API), and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms. Conclusion: We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the “representational state transfer” (REST) API enables building user friendly interfaces and graphical summaries of the data, and how these resources facilitate the modelling of reproducible quantitative structure–activity relationships for nanomaterials (NanoQSAR). PMID:26425413
The eNanoMapper database for nanomaterial safety information.
Jeliazkova, Nina; Chomenidis, Charalampos; Doganis, Philip; Fadeel, Bengt; Grafström, Roland; Hardy, Barry; Hastings, Janna; Hegi, Markus; Jeliazkov, Vedrin; Kochev, Nikolay; Kohonen, Pekka; Munteanu, Cristian R; Sarimveis, Haralambos; Smeets, Bart; Sopasakis, Pantelis; Tsiliki, Georgia; Vorgrimmler, David; Willighagen, Egon
2015-01-01
The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs). Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs. The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API), and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms. We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the "representational state transfer" (REST) API enables building user friendly interfaces and graphical summaries of the data, and how these resources facilitate the modelling of reproducible quantitative structure-activity relationships for nanomaterials (NanoQSAR).
Electron capture cross sections by O+ from atomic He
NASA Astrophysics Data System (ADS)
Joseph, Dwayne C.; Saha, Bidhan C.
2009-11-01
The adiabatic representation is used in both the quantal and semi classical molecular orbital close coupling methods (MOCC) to evaluate charge exchange cross sections. Our results show good agreement with experimental cross sections
Accelerating the coupled-cluster singles and doubles method using the chain-of-sphere approximation
NASA Astrophysics Data System (ADS)
Dutta, Achintya Kumar; Neese, Frank; Izsák, Róbert
2018-06-01
In this paper, we present a chain-of-sphere implementation of the external exchange term, the computational bottleneck of coupled-cluster calculations at the singles and doubles level. This implementation is compared to standard molecular orbital, atomic orbital and resolution of identity implementations of the same term within the ORCA package and turns out to be the most efficient one for larger molecules, with a better accuracy than the resolution-of-identity approximation. Furthermore, it becomes possible to perform a canonical CC calculation on a tetramer of nucleobases in 17 days, 20 hours.
Kowalski, Karol; Valiev, Marat
2007-01-01
High-level ab-initio equation-of-motion coupled-cluster methods with singles, doubles, and noniterative triples are used, in conjunction with the combined quantum mechanical molecular mechanics approach, to investigate the structure of low-lying excited states of the guanine base in DNA and solvated environments. Our results indicate that while the excitation energy of the first excited state is barely changed compared to its gas-phase counterpart, the excitation energy of the second excited state is blue-shifted by 0.24 eV.
A Massively Parallel Tensor Contraction Framework for Coupled-Cluster Computations
2014-08-02
CCSDT The CCSD model [41], where T = T1 + T2 (i.e. n = 2 in Equation 2), is one of the most widely used coupled-cluster methods as it provides a good...derived from response theory. Extending this to CCSDT [30, 35], where T = T1 + T2 + T3 ( n = 3), gives an even more accurate method (often capable of...CCSD and CCSDT have leading-order costs of O(n2on 4 v) and O( n 3 on 5 v), where no and nv are the number of occupied and virtual orbitals, respectively
DOE Office of Scientific and Technical Information (OSTI.GOV)
Parrish, Robert M.; Sherrill, C. David, E-mail: sherrill@gatech.edu; Hohenstein, Edward G.
2014-05-14
We apply orbital-weighted least-squares tensor hypercontraction decomposition of the electron repulsion integrals to accelerate the coupled cluster singles and doubles (CCSD) method. Using accurate and flexible low-rank factorizations of the electron repulsion integral tensor, we are able to reduce the scaling of the most vexing particle-particle ladder term in CCSD from O(N{sup 6}) to O(N{sup 5}), with remarkably low error. Combined with a T{sub 1}-transformed Hamiltonian, this leads to substantial practical accelerations against an optimized density-fitted CCSD implementation.
Coupled-cluster treatment of molecular strong-field ionization
NASA Astrophysics Data System (ADS)
Jagau, Thomas-C.
2018-05-01
Ionization rates and Stark shifts of H2, CO, O2, H2O, and CH4 in static electric fields have been computed with coupled-cluster methods in a basis set of atom-centered Gaussian functions with a complex-scaled exponent. Consideration of electron correlation is found to be of great importance even for a qualitatively correct description of the dependence of ionization rates and Stark shifts on the strength and orientation of the external field. The analysis of the second moments of the molecular charge distribution suggests a simple criterion for distinguishing tunnel and barrier suppression ionization in polyatomic molecules.
NASA Astrophysics Data System (ADS)
Khomyakov, Dmitry G.; Timerghazin, Qadir K.
2017-07-01
Methyl thionitrite CH3SNO is an important model of S-nitrosated cysteine aminoacid residue (CysNO), a ubiquitous biological S-nitrosothiol (RSNO) involved in numerous physiological processes. As such, CH3SNO can provide insights into the intrinsic properties of the —SNO group in CysNO, in particular, its weak and labile S—N bond. Here, we report an ab initio computational investigation of the structure and properties of CH3SNO using a composite Feller-Peterson-Dixon scheme based on the explicitly correlated coupled cluster with single, double, and perturbative triple excitations calculations extrapolated to the complete basis set limit, CCSD(T)-F12/CBS, with a number of additive corrections for the effects of quadruple excitations, core-valence correlation, scalar-relativistic and spin-orbit effects, as well as harmonic zero-point vibrational energy with an anharmonicity correction. These calculations suggest that the S—N bond in CH3SNO is significantly elongated (1.814 Å) and has low stretching frequency and dissociation energy values, νS—N = 387 cm-1 and D0 = 32.4 kcal/mol. At the same time, the S—N bond has a sizable rotation barrier, △E0≠ = 12.7 kcal/mol, so CH3SNO exists as a cis- or trans-conformer, the latter slightly higher in energy, △E0 = 1.2 kcal/mol. The S—N bond properties are consistent with the antagonistic nature of CH3SNO, whose resonance representation requires two chemically opposite (antagonistic) resonance structures, CH3—S+=N—O- and CH3—S-/NO+, which can be probed using external electric fields and quantified using the natural resonance theory approach (NRT). The calculated S—N bond properties slowly converge with the level of correlation treatment, with the recently developed distinguished cluster with single and double excitations approximation (DCSD-F12) performing significantly better than the coupled cluster with single and double excitations (CCSD-F12), although still inferior to the CCSD(T)-F12 method that includes perturbative triple excitations. Double-hybrid density functional theory (DFT) calculations with mPW2PLYPD/def2-TZVPPD reproduce well the geometry, vibrational frequencies, and the S—N bond rotational barrier in CH3SNO, while hybrid DFT calculations with PBE0/def2-TZVPPD give a better S—N bond dissociation energy.
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data
Hallac, David; Vare, Sagar; Boyd, Stephen; Leskovec, Jure
2018-01-01
Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. PMID:29770257
Generalized quantum kinetic expansion: Higher-order corrections to multichromophoric Förster theory
NASA Astrophysics Data System (ADS)
Wu, Jianlan; Gong, Zhihao; Tang, Zhoufei
2015-08-01
For a general two-cluster energy transfer network, a new methodology of the generalized quantum kinetic expansion (GQKE) method is developed, which predicts an exact time-convolution equation for the cluster population evolution under the initial condition of the local cluster equilibrium state. The cluster-to-cluster rate kernel is expanded over the inter-cluster couplings. The lowest second-order GQKE rate recovers the multichromophoric Förster theory (MCFT) rate. The higher-order corrections to the MCFT rate are systematically included using the continued fraction resummation form, resulting in the resummed GQKE method. The reliability of the GQKE methodology is verified in two model systems, revealing the relevance of higher-order corrections.
Ahlqvist-Björkroth, Sari; Korja, Riikka; Junttila, Niina; Savonlahti, Elina; Pajulo, Marjukka; Räihä, Hannele; Aromaa, Minna
2016-07-01
Marital distress, parental depression, and weak quality of parental representations are all known risk factors for parent-child relationships. However, the relation between marital distress, depressive symptoms, and parents' prenatal representation is uncertain, especially regarding fathers. The present study aimed to explore how mothers' and fathers' prenatal experience of marital distress and depressive symptoms affects the organization of their prenatal representations in late pregnancy. Participants were 153 pregnant couples from a Finnish follow-up study called "Steps to the Healthy Development and Well-being of Children" (H. Lagström et al., ). Marital distress (Revised Dyadic Adjustment Scale; D.M. Busby, C. Christensen, D. Crane, & J. Larson, 1995) and depressive symptoms (Edinburgh Postnatal Depression Scale) were assessed at 20 gestational weeks, and prenatal representations (Working Model of the Child Interview; D. Benoit, K.C.H. Parker, & C.H. Zeanah, 1997; C.H. Zeanah, D. Benoit, M. Barton, & L. Hirshberg, 1996) were assessed between 29 and 32 gestational weeks. The mothers' risks of distorted representations increased significantly when they had at least minor depressive symptoms. Marital distress was associated with the fathers' prenatal representations, although the association was weak; fathers within the marital distress group had less balanced representations. Coexisting marital distress and depressive symptoms were only associated with the mothers' representations; lack of marital distress and depressive symptoms increased the likelihood for mothers to have balanced representations. The results imply that marital distress and depressive symptoms are differently related to the organizations of mothers' and fathers' prenatal representations. © 2016 Michigan Association for Infant Mental Health.
NASA Astrophysics Data System (ADS)
Seppke, Benjamin; Dreschler-Fischer, Leonie; Wilms, Christian
2016-08-01
The extraction of road signatures from remote sensing images as a promising indicator for urbanization is a classical segmentation problem. However, some segmentation algorithms often lead to non-sufficient results. One way to overcome this problem is the usage of superpixels, that represent a locally coherent cluster of connected pixels. Superpixels allow flexible, highly adaptive segmentation approaches due to the possibility of merging as well as splitting and form new basic image entities. On the other hand, superpixels require an appropriate representation containing all relevant information about topology and geometry to maximize their advantages.In this work, we present a combined geometric and topological representation based on a special graph representation, the so-called RS-graph. Moreover, we present the use of the RS-graph by means of a case study: the extraction of partially occluded road networks in rural areas from open source (spectral) remote sensing images by tracking. In addition, multiprocessing and GPU-based parallelization is used to speed up the construction of the representation and the application.
Communication: Multiple-property-based diabatization for open-shell van der Waals molecules
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karman, Tijs; Avoird, Ad van der; Groenenboom, Gerrit C., E-mail: gerritg@theochem.ru.nl
2016-03-28
We derive a new multiple-property-based diabatization algorithm. The transformation between adiabatic and diabatic representations is determined by requiring a set of properties in both representations to be related by a similarity transformation. This set of properties is determined in the adiabatic representation by rigorous electronic structure calculations. In the diabatic representation, the same properties are determined using model diabatic states defined as products of undistorted monomer wave functions. This diabatic model is generally applicable to van der Waals molecules in arbitrary electronic states. Application to locating seams of conical intersections and collisional transfer of electronic excitation energy is demonstrated formore » O{sub 2} − O{sub 2} in low-lying excited states. Property-based diabatization for this test system included all components of the electric quadrupole tensor, orbital angular momentum, and spin-orbit coupling.« less
Irwin, Gareth; Kerwin, David G; Williams, Genevieve; Van Emmerik, Richard E A; Newell, Karl M; Hamill, Joseph
2018-06-18
A case study visualisation approach to examining the coordination and variability of multiple interacting segments is presented using a whole-body gymnastic skill as the task example. One elite male gymnast performed 10 trials of 10 longswings whilst three-dimensional locations of joint centres were tracked using a motion analysis system. Segment angles were used to define coupling between the arms and trunk, trunk and thighs and thighs and shanks. Rectified continuous relative phase profiles for each interacting couple for 80 longswings were produced. Graphical representations of coordination couplings are presented that include the traditional single coupling, followed by the relational dynamics of two couplings and finally three couplings simultaneously plotted. This method highlights the power of visualisation of movement dynamics and identifies properties of the global interacting segmental couplings that a more formal analysis may not reveal. Visualisation precedes and informs the appropriate qualitative and quantitative analysis of the dynamics.
Zhou, Xichun; Turchi, Craig; Wang, Denong
2009-01-01
We reported here a novel, ready-to-use bioarray platform and methodology for construction of sensitive carbohydrate cluster microarrays. This technology utilizes a 3-dimensional (3-D) poly(amidoamine) starburst dendrimer monolayer assembled on glass surface, which is functionalized with terminal aminooxy and hydrazide groups for site-specific coupling of carbohydrates. A wide range of saccharides, including monosaccharides, oligosaccharides and polysaccharides of diverse structures, are applicable for the 3-D bioarray platform without prior chemical derivatization. The process of carbohydrate coupling is effectively accelerated by microwave radiation energy. The carbohydrate concentration required for microarray fabrication is substantially reduced using this technology. Importantly, this bioarray platform presents sugar chains in defined orientation and cluster configurations. It is, thus, uniquely useful for exploration of the structural and conformational diversities of glyco-epitope and their functional properties. PMID:19791771
Comparing Effects of Cluster-Coupled Patterns on Opinion Dynamics
NASA Astrophysics Data System (ADS)
Liu, Yun; Si, Xia-Meng; Zhang, Yan-Chao
2012-07-01
Community structure is another important feature besides small-world and scale-free property of complex networks. Communities can be coupled through specific fixed links between nodes, or occasional encounter behavior. We introduce a model for opinion evolution with multiple cluster-coupled patterns, in which the interconnectivity denotes the coupled degree of communities by fixed links, and encounter frequency controls the coupled degree of communities by encounter behaviors. Considering the complicated cognitive system of people, the CODA (continuous opinions and discrete actions) update rules are used to mimic how people update their decisions after interacting with someone. It is shown that, large interconnectivity and encounter frequency both can promote consensus, reduce competition between communities and propagate some opinion successfully across the whole population. Encounter frequency is better than interconnectivity at facilitating the consensus of decisions. When the degree of social cohesion is same, small interconnectivity has better effects on lessening the competence between communities than small encounter frequency does, while large encounter frequency can make the greater degree of agreement across the whole populations than large interconnectivity can.
Clustering of GPS velocities in the Mojave Block, southeastern California
Savage, James C.; Simpson, Robert W.
2013-01-01
We find subdivisions within the Mojave Block using cluster analysis to identify groupings in the velocities observed at GPS stations there. The clusters are represented on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. The most significant representation as judged by the gap test involves 4 clusters within the Mojave Block. The fault systems bounding the clusters from east to west are 1) the faults defining the eastern boundary of the Northeast Mojave Domain extended southward to connect to the Hector Mine rupture, 2) the Calico-Paradise fault system, 3) the Landers-Blackwater fault system, and 4) the Helendale-Lockhart fault system. This division of the Mojave Block is very similar to that proposed by Meade and Hager. However, no cluster boundary coincides with the Garlock Fault, the northern boundary of the Mojave Block. Rather, the clusters appear to continue without interruption from the Mojave Block north into the southern Walker Lane Belt, similar to the continuity across the Garlock Fault of the shear zone along the Blackwater-Little Lake fault system observed by Peltzer et al. Mapped traces of individual faults in the Mojave Block terminate within the block and do not continue across the Garlock Fault [Dokka and Travis, ].
Clustering-based Feature Learning on Variable Stars
NASA Astrophysics Data System (ADS)
Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos
2016-04-01
The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.
Chemical reaction vector embeddings: towards predicting drug metabolism in the human gut microbiome.
Mallory, Emily K; Acharya, Ambika; Rensi, Stefano E; Turnbaugh, Peter J; Bright, Roselie A; Altman, Russ B
2018-01-01
Bacteria in the human gut have the ability to activate, inactivate, and reactivate drugs with both intended and unintended effects. For example, the drug digoxin is reduced to the inactive metabolite dihydrodigoxin by the gut Actinobacterium E. lenta, and patients colonized with high levels of drug metabolizing strains may have limited response to the drug. Understanding the complete space of drugs that are metabolized by the human gut microbiome is critical for predicting bacteria-drug relationships and their effects on individual patient response. Discovery and validation of drug metabolism via bacterial enzymes has yielded >50 drugs after nearly a century of experimental research. However, there are limited computational tools for screening drugs for potential metabolism by the gut microbiome. We developed a pipeline for comparing and characterizing chemical transformations using continuous vector representations of molecular structure learned using unsupervised representation learning. We applied this pipeline to chemical reaction data from MetaCyc to characterize the utility of vector representations for chemical reaction transformations. After clustering molecular and reaction vectors, we performed enrichment analyses and queries to characterize the space. We detected enriched enzyme names, Gene Ontology terms, and Enzyme Consortium (EC) classes within reaction clusters. In addition, we queried reactions against drug-metabolite transformations known to be metabolized by the human gut microbiome. The top results for these known drug transformations contained similar substructure modifications to the original drug pair. This work enables high throughput screening of drugs and their resulting metabolites against chemical reactions common to gut bacteria.
Version 4.0 of code Java for 3D simulation of the CCA model
NASA Astrophysics Data System (ADS)
Fan, Linyu; Liao, Jianwei; Zuo, Junsen; Zhang, Kebo; Li, Chao; Xiong, Hailing
2018-07-01
This paper presents a new version Java code for the three-dimensional simulation of Cluster-Cluster Aggregation (CCA) model to replace the previous version. Many redundant traverses of clusters-list in the program were totally avoided, so that the consumed simulation time is significantly reduced. In order to show the aggregation process in a more intuitive way, we have labeled different clusters with varied colors. Besides, a new function is added for outputting the particle's coordinates of aggregates in file to benefit coupling our model with other models.
Pendulum Motion in Main Parachute Clusters
NASA Technical Reports Server (NTRS)
Ray, Eric S.; Machin, Ricardo A.
2015-01-01
The coupled dynamics of a cluster of parachutes to a payload are notoriously difficult to predict. Often the payload is designed to be insensitive to the range of attitude and rates that might occur, but spacecraft generally do not have the mass and volume budgeted for this robust of a design. The National Aeronautics and Space Administration (NASA) Orion Capsule Parachute Assembly System (CPAS) implements a cluster of three mains for landing. During testing of the Engineering Development Unit (EDU) design, it was discovered that with a cluster of two mains (a fault tolerance required for human rating) the capsule coupled to the parachute cluster could get into a limit cycle pendulum motion which would exceed the spacecraft landing capability. This pendulum phenomenon could not be predicted with the existing models and simulations. A three phased effort has been undertaken to understand the consequence of the pendulum motion observed, and explore potential design changes that would mitigate this phenomenon. This paper will review the early analysis that was performed of the pendulum motion observed during EDU testing, summarize the analysis ongoing to understand the root cause of the pendulum phenomenon, and discuss the modeling and testing that is being pursued to identify design changes that would mitigate the risk.
Homayoon, Zahra
2014-09-28
A new, full (nine)-dimensional potential energy surface and dipole moment surface to describe the NO(+)(H2O) cluster is reported. The PES is based on fitting of roughly 32,000 CCSD(T)-F12/aug-cc-pVTZ electronic energies. The surface is a linear least-squares fit using a permutationally invariant basis with Morse-type variables. The PES is used in a Diffusion Monte Carlo study of the zero-point energy and wavefunction of the NO(+)(H2O) and NO(+)(D2O) complexes. Using the calculated ZPE the dissociation energies of the clusters are reported. Vibrational configuration interaction calculations of NO(+)(H2O) and NO(+)(D2O) using the MULTIMODE program are performed. The fundamental, a number of overtone, and combination states of the clusters are reported. The IR spectrum of the NO(+)(H2O) cluster is calculated using 4, 5, 7, and 8 modes VSCF/CI calculations. The anharmonic, coupled vibrational calculations, and IR spectrum show very good agreement with experiment. Mode coupling of the water "antisymmetric" stretching mode with the low-frequency intermolecular modes results in intensity borrowing.
NASA Astrophysics Data System (ADS)
Homayoon, Zahra
2014-09-01
A new, full (nine)-dimensional potential energy surface and dipole moment surface to describe the NO+(H2O) cluster is reported. The PES is based on fitting of roughly 32 000 CCSD(T)-F12/aug-cc-pVTZ electronic energies. The surface is a linear least-squares fit using a permutationally invariant basis with Morse-type variables. The PES is used in a Diffusion Monte Carlo study of the zero-point energy and wavefunction of the NO+(H2O) and NO+(D2O) complexes. Using the calculated ZPE the dissociation energies of the clusters are reported. Vibrational configuration interaction calculations of NO+(H2O) and NO+(D2O) using the MULTIMODE program are performed. The fundamental, a number of overtone, and combination states of the clusters are reported. The IR spectrum of the NO+(H2O) cluster is calculated using 4, 5, 7, and 8 modes VSCF/CI calculations. The anharmonic, coupled vibrational calculations, and IR spectrum show very good agreement with experiment. Mode coupling of the water "antisymmetric" stretching mode with the low-frequency intermolecular modes results in intensity borrowing.
Cluster Formation of Anchored Proteins Induced by Membrane-Mediated Interaction
Li, Shuangyang; Zhang, Xianren; Wang, Wenchuan
2010-01-01
Abstract Computer simulations were used to study the cluster formation of anchored proteins in a membrane. The rate and extent of clustering was found to be dependent upon the hydrophobic length of the anchored proteins embedded in the membrane. The cluster formation mechanism of anchored proteins in our work was ascribed to the different local perturbations on the upper and lower monolayers of the membrane and the intermonolayer coupling. Simulation results demonstrated that only when the penetration depth of anchored proteins was larger than half the membrane thickness, could the structure of the lower monolayer be significantly deformed. Additionally, studies on the local structures of membranes indicated weak perturbation of bilayer thickness for a shallowly inserted protein, while there was significant perturbation for a more deeply inserted protein. The origin of membrane-mediated protein-protein interaction is therefore due to the local perturbation of the membrane thickness, and the entropy loss—both of which are caused by the conformation restriction on the lipid chains and the enhanced intermonolayer coupling for a deeply inserted protein. Finally, in this study we addressed the difference of cluster formation mechanisms between anchored proteins and transmembrane proteins. PMID:20513399
A framework for graph-based synthesis, analysis, and visualization of HPC cluster job data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mayo, Jackson R.; Kegelmeyer, W. Philip, Jr.; Wong, Matthew H.
The monitoring and system analysis of high performance computing (HPC) clusters is of increasing importance to the HPC community. Analysis of HPC job data can be used to characterize system usage and diagnose and examine failure modes and their effects. This analysis is not straightforward, however, due to the complex relationships that exist between jobs. These relationships are based on a number of factors, including shared compute nodes between jobs, proximity of jobs in time, etc. Graph-based techniques represent an approach that is particularly well suited to this problem, and provide an effective technique for discovering important relationships in jobmore » queuing and execution data. The efficacy of these techniques is rooted in the use of a semantic graph as a knowledge representation tool. In a semantic graph job data, represented in a combination of numerical and textual forms, can be flexibly processed into edges, with corresponding weights, expressing relationships between jobs, nodes, users, and other relevant entities. This graph-based representation permits formal manipulation by a number of analysis algorithms. This report presents a methodology and software implementation that leverages semantic graph-based techniques for the system-level monitoring and analysis of HPC clusters based on job queuing and execution data. Ontology development and graph synthesis is discussed with respect to the domain of HPC job data. The framework developed automates the synthesis of graphs from a database of job information. It also provides a front end, enabling visualization of the synthesized graphs. Additionally, an analysis engine is incorporated that provides performance analysis, graph-based clustering, and failure prediction capabilities for HPC systems.« less
Ab initio Bogoliubov coupled cluster theory for open-shell nuclei
Signoracci, Angelo J.; Duguet, Thomas; Hagen, Gaute; ...
2015-06-29
Background: Ab initio many-body methods have been developed over the past 10 yr to address closed-shell nuclei up to mass A≈130 on the basis of realistic two- and three-nucleon interactions. A current frontier relates to the extension of those many-body methods to the description of open-shell nuclei. Several routes to address open-shell nuclei are currently under investigation, including ideas that exploit spontaneous symmetry breaking. Purpose: Singly open-shell nuclei can be efficiently described via the sole breaking of U(1) gauge symmetry associated with particle-number conservation as a way to account for their superfluid character. While this route was recently followed withinmore » the framework of self-consistent Green's function theory, the goal of the present work is to formulate a similar extension within the framework of coupled cluster theory. Methods: We formulate and apply Bogoliubov coupled cluster (BCC) theory, which consists of representing the exact ground-state wave function of the system as the exponential of a quasiparticle excitation cluster operator acting on a Bogoliubov reference state. Equations for the ground-state energy and the cluster amplitudes are derived at the singles and doubles level (BCCSD) both algebraically and diagrammatically. The formalism includes three-nucleon forces at the normal-ordered two-body level. The first BCC code is implemented in m scheme, which will permit the treatment of doubly open-shell nuclei via the further breaking of SU(2) symmetry associated with angular momentum conservation. Results: Proof-of-principle calculations in an N max=6 spherical harmonic oscillator basis for 16,18O and 18Ne in the BCCD approximation are in good agreement with standard coupled cluster results with the same chiral two-nucleon interaction, while 20O and 20Mg display underbinding relative to experiment. The breaking of U(1) symmetry, monitored by computing the variance associated with the particle-number operator, is relatively constant for all five nuclei, in both the Hartree-Fock-Bogoliubov and BCCD approximations. Conclusions: The newly developed many-body formalism increases the potential span of ab initio calculations based on single-reference coupled cluster techniques tremendously, i.e., potentially to reach several hundred additional midmass nuclei. The new formalism offers a wealth of potential applications and further extensions dedicated to the description of ground and excited states of open-shell nuclei. Short-term goals include the implementation of three-nucleon forces at the normal-ordered two-body level. Midterm extensions include the approximate treatment of triples corrections and the development of the equation-of-motion methodology to treat both excited states and odd nuclei. Long-term extensions include exact restoration of U(1) and SU(2) symmetries.« less
Differential geometry based solvation model II: Lagrangian formulation.
Chen, Zhan; Baker, Nathan A; Wei, G W
2011-12-01
Solvation is an elementary process in nature and is of paramount importance to more sophisticated chemical, biological and biomolecular processes. The understanding of solvation is an essential prerequisite for the quantitative description and analysis of biomolecular systems. This work presents a Lagrangian formulation of our differential geometry based solvation models. The Lagrangian representation of biomolecular surfaces has a few utilities/advantages. First, it provides an essential basis for biomolecular visualization, surface electrostatic potential map and visual perception of biomolecules. Additionally, it is consistent with the conventional setting of implicit solvent theories and thus, many existing theoretical algorithms and computational software packages can be directly employed. Finally, the Lagrangian representation does not need to resort to artificially enlarged van der Waals radii as often required by the Eulerian representation in solvation analysis. The main goal of the present work is to analyze the connection, similarity and difference between the Eulerian and Lagrangian formalisms of the solvation model. Such analysis is important to the understanding of the differential geometry based solvation model. The present model extends the scaled particle theory of nonpolar solvation model with a solvent-solute interaction potential. The nonpolar solvation model is completed with a Poisson-Boltzmann (PB) theory based polar solvation model. The differential geometry theory of surfaces is employed to provide a natural description of solvent-solute interfaces. The optimization of the total free energy functional, which encompasses the polar and nonpolar contributions, leads to coupled potential driven geometric flow and PB equations. Due to the development of singularities and nonsmooth manifolds in the Lagrangian representation, the resulting potential-driven geometric flow equation is embedded into the Eulerian representation for the purpose of computation, thanks to the equivalence of the Laplace-Beltrami operator in the two representations. The coupled partial differential equations (PDEs) are solved with an iterative procedure to reach a steady state, which delivers desired solvent-solute interface and electrostatic potential for problems of interest. These quantities are utilized to evaluate the solvation free energies and protein-protein binding affinities. A number of computational methods and algorithms are described for the interconversion of Lagrangian and Eulerian representations, and for the solution of the coupled PDE system. The proposed approaches have been extensively validated. We also verify that the mean curvature flow indeed gives rise to the minimal molecular surface and the proposed variational procedure indeed offers minimal total free energy. Solvation analysis and applications are considered for a set of 17 small compounds and a set of 23 proteins. The salt effect on protein-protein binding affinity is investigated with two protein complexes by using the present model. Numerical results are compared to the experimental measurements and to those obtained by using other theoretical methods in the literature. © Springer-Verlag 2011
Differential geometry based solvation model II: Lagrangian formulation
Chen, Zhan; Baker, Nathan A.; Wei, G. W.
2010-01-01
Solvation is an elementary process in nature and is of paramount importance to more sophisticated chemical, biological and biomolecular processes. The understanding of solvation is an essential prerequisite for the quantitative description and analysis of biomolecular systems. This work presents a Lagrangian formulation of our differential geometry based solvation model. The Lagrangian representation of biomolecular surfaces has a few utilities/advantages. First, it provides an essential basis for biomolecular visualization, surface electrostatic potential map and visual perception of biomolecules. Additionally, it is consistent with the conventional setting of implicit solvent theories and thus, many existing theoretical algorithms and computational software packages can be directly employed. Finally, the Lagrangian representation does not need to resort to artificially enlarged van der Waals radii as often required by the Eulerian representation in solvation analysis. The main goal of the present work is to analyze the connection, similarity and difference between the Eulerian and Lagrangian formalisms of the solvation model. Such analysis is important to the understanding of the differential geometry based solvation model. The present model extends the scaled particle theory (SPT) of nonpolar solvation model with a solvent-solute interaction potential. The nonpolar solvation model is completed with a Poisson-Boltzmann (PB) theory based polar solvation model. The differential geometry theory of surfaces is employed to provide a natural description of solvent-solute interfaces. The minimization of the total free energy functional, which encompasses the polar and nonpolar contributions, leads to coupled potential driven geometric flow and Poisson-Boltzmann equations. Due to the development of singularities and nonsmooth manifolds in the Lagrangian representation, the resulting potential-driven geometric flow equation is embedded into the Eulerian representation for the purpose of computation, thanks to the equivalence of the Laplace-Beltrami operator in the two representations. The coupled partial differential equations (PDEs) are solved with an iterative procedure to reach a steady state, which delivers desired solvent-solute interface and electrostatic potential for problems of interest. These quantities are utilized to evaluate the solvation free energies and protein-protein binding affinities. A number of computational methods and algorithms are described for the interconversion of Lagrangian and Eulerian representations, and for the solution of the coupled PDE system. The proposed approaches have been extensively validated. We also verify that the mean curvature flow indeed gives rise to the minimal molecular surface (MMS) and the proposed variational procedure indeed offers minimal total free energy. Solvation analysis and applications are considered for a set of 17 small compounds and a set of 23 proteins. The salt effect on protein-protein binding affinity is investigated with two protein complexes by using the present model. Numerical results are compared to the experimental measurements and to those obtained by using other theoretical methods in the literature. PMID:21279359
Pilot-in-the-Loop CFD Method Development
2014-06-16
CFD analysis. Coupled simulations will be run at PSU on the COCOA -4 cluster, a high performance computing cluster. The CRUNCH CFD software has...been installed on the COCOA -4 servers and initial software tests are being conducted. Initial efforts will use the Generic Frigate Shape SFS-2 to
Ruan, Zhi; Yang, Ting; Shi, Xinyan; Kong, Yingying; Xie, Xinyou
2017-01-01
Ureaplasma spp. have gained increasing recognition as pathogens in both adult and neonatal patients with multiple clinical presentations. However, the clonality of this organism in the male population and infertile couples in China is largely unknown. In this study, 96 (53 U. parvum and 43 U. urealyticum) of 103 Ureaplasma spp. strains recovered from genital specimens from male patients and 15 pairs of infertile couples were analyzed using multilocus sequence typing (MLST)/expanded multilocus sequence typing (eMLST) schemes. A total of 39 sequence types (STs) and 53 expanded sequence types (eSTs) were identified, with three predominant STs (ST1, ST9 and ST22) and eSTs (eST16, eST41 and eST82). Moreover, phylogenetic analysis revealed two distinct clusters that were highly congruent with the taxonomic differences between the two Ureaplasma species. We found significant differences in the distributions of both clusters and sub-groups between the male and female patients (P < 0.001). Moreover, 66.7% and 40.0% of the male and female partners of the infertile couples tested positive for Ureaplasma spp. The present study also attained excellent agreement of the identification of both Ureaplasma species between paired urine and semen specimens from the male partners (k > 0.80). However, this concordance was observed only for the detection of U. urealyticum within the infertile couples. In conclusion, the distributions of the clusters and sub-groups significantly differed between the male and female patients. U. urealyticum is more likely to transmit between infertile couples and be associated with clinical manifestations by the specific epidemic clonal lineages. PMID:28859153
Ruan, Zhi; Yang, Ting; Shi, Xinyan; Kong, Yingying; Xie, Xinyou; Zhang, Jun
2017-01-01
Ureaplasma spp. have gained increasing recognition as pathogens in both adult and neonatal patients with multiple clinical presentations. However, the clonality of this organism in the male population and infertile couples in China is largely unknown. In this study, 96 (53 U. parvum and 43 U. urealyticum) of 103 Ureaplasma spp. strains recovered from genital specimens from male patients and 15 pairs of infertile couples were analyzed using multilocus sequence typing (MLST)/expanded multilocus sequence typing (eMLST) schemes. A total of 39 sequence types (STs) and 53 expanded sequence types (eSTs) were identified, with three predominant STs (ST1, ST9 and ST22) and eSTs (eST16, eST41 and eST82). Moreover, phylogenetic analysis revealed two distinct clusters that were highly congruent with the taxonomic differences between the two Ureaplasma species. We found significant differences in the distributions of both clusters and sub-groups between the male and female patients (P < 0.001). Moreover, 66.7% and 40.0% of the male and female partners of the infertile couples tested positive for Ureaplasma spp. The present study also attained excellent agreement of the identification of both Ureaplasma species between paired urine and semen specimens from the male partners (k > 0.80). However, this concordance was observed only for the detection of U. urealyticum within the infertile couples. In conclusion, the distributions of the clusters and sub-groups significantly differed between the male and female patients. U. urealyticum is more likely to transmit between infertile couples and be associated with clinical manifestations by the specific epidemic clonal lineages.
Determining requirements for patient-centred care: a participatory concept mapping study.
Ogden, Kathryn; Barr, Jennifer; Greenfield, David
2017-11-28
Recognition of a need for patient-centred care is not new, however making patient-centred care a reality remains a challenge to organisations. We need empirical studies to extend current understandings, create new representations of the complexity of patient-centred care, and guide collective action toward patient-centred health care. To achieve these ends, the research aim was to empirically determine what organisational actions are required for patient-centred care to be achieved. We used an established participatory concept mapping methodology. Cross-sector stakeholders contributed to the development of statements for patient-centred care requirements, sorting statements into groupings according to similarity, and rating each statement according to importance, feasibility, and achievement. The resultant data were analysed to produce a visual concept map representing participants' conceptualisation of patient-centred care requirements. Analysis included the development of a similarity matrix, multidimensional scaling, hierarchical cluster analysis, selection of the number of clusters and their labels, identifying overarching domains and quantitative representation of rating data. The outcome was the development of a conceptual map for the Requirements of Patient-Centred Care Systems (ROPCCS). ROPCCS incorporates 123 statements sorted into 13 clusters. Cluster labels were: shared responsibility for personalised health literacy; patient provider dynamic for care partnership; collaboration; shared power and responsibility; resources for coordination of care; recognition of humanity - skills and attributes; knowing and valuing the patient; relationship building; system review evaluation and new models; commitment to supportive structures and processes; elements to facilitate change; professional identity and capability development; and explicit education and learning. The clusters were grouped into three overarching domains, representing a cross-sectoral approach: humanity and partnership; career spanning education and training; and health systems, policy and management. Rating of statements allowed the generation of go-zone maps for further interrogation of the relative importance, feasibility, and achievement of each patient-centred care requirement and cluster. The study has empirically determined requirements for patient-centred care through the development of ROPCCS. The unique map emphasises collaborative responsibility of stakeholders to ensure that patient-centred care is comprehensively progressed. ROPCCS allows the complex requirements for patient-centred care to be understood, implemented, evaluated, measured, and shown to be occurring.
Multi-Scale Voxel Segmentation for Terrestrial Lidar Data within Marshes
NASA Astrophysics Data System (ADS)
Nguyen, C. T.; Starek, M. J.; Tissot, P.; Gibeaut, J. C.
2016-12-01
The resilience of marshes to a rising sea is dependent on their elevation response. Terrestrial laser scanning (TLS) is a detailed topographic approach for accurate, dense surface measurement with high potential for monitoring of marsh surface elevation response. The dense point cloud provides a 3D representation of the surface, which includes both terrain and non-terrain objects. Extraction of topographic information requires filtering of the data into like-groups or classes, therefore, methods must be incorporated to identify structure in the data prior to creation of an end product. A voxel representation of three-dimensional space provides quantitative visualization and analysis for pattern recognition. The objectives of this study are threefold: 1) apply a multi-scale voxel approach to effectively extract geometric features from the TLS point cloud data, 2) investigate the utility of K-means and Self Organizing Map (SOM) clustering algorithms for segmentation, and 3) utilize a variety of validity indices to measure the quality of the result. TLS data were collected at a marsh site along the central Texas Gulf Coast using a Riegl VZ 400 TLS. The site consists of both exposed and vegetated surface regions. To characterize structure of the point cloud, octree segmentation is applied to create a tree data structure of voxels containing the points. The flexibility of voxels in size and point density makes this algorithm a promising candidate to locally extract statistical and geometric features of the terrain including surface normal and curvature. The characteristics of the voxel itself such as the volume and point density are also computed and assigned to each point as are laser pulse characteristics. The features extracted from the voxelization are then used as input for clustering of the points using the K-means and SOM clustering algorithms. Optimal number of clusters are then determined based on evaluation of cluster separability criterions. Results for different combinations of the feature space vector and differences between K-means and SOM clustering will be presented. The developed method provides a novel approach for compressing TLS scene complexity in marshes, such as for vegetation biomass studies or erosion monitoring.
Structures of Aln (n= 27, 28, 29, and 30) clusters with double-tetrahedron structures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, W.; Lu, W. C.; Sun, J.
2008-01-31
Global search for lowest-energy structures of neutral aluminum clusters Al{sub n} (n = 27, 28, 29 and 30) was performed using a genetic algorithm (GA) coupled with a tight-binding (TB) method. Structural candidates obtained from our GA search were further optimized with first-principles calculations. It is found that the medium-sized aluminum clusters Al{sub 27} to Al{sub 30} favor double-tetrahedron structures.
Negrón-Oyarzo, Ignacio; Espinosa, Nelson; Aguilar, Marcelo; Fuenzalida, Marco; Aboitiz, Francisco; Fuentealba, Pablo
2018-06-18
Learning the location of relevant places in the environment is crucial for survival. Such capacity is supported by a distributed network comprising the prefrontal cortex and hippocampus, yet it is not fully understood how these structures cooperate during spatial reference memory formation. Hence, we examined neural activity in the prefrontal-hippocampal circuit in mice during acquisition of spatial reference memory. We found that interregional oscillatory coupling increased with learning, specifically in the slow-gamma frequency (20 to 40 Hz) band during spatial navigation. In addition, mice used both spatial and nonspatial strategies to navigate and solve the task, yet prefrontal neuronal spiking and oscillatory phase coupling were selectively enhanced in the spatial navigation strategy. Lastly, a representation of the behavioral goal emerged in prefrontal spiking patterns exclusively in the spatial navigation strategy. These results suggest that reference memory formation is supported by enhanced cortical connectivity and evolving prefrontal spiking representations of behavioral goals.
NASA Astrophysics Data System (ADS)
Cohen, Guy; Gull, Emanuel; Reichman, David R.; Millis, Andrew J.
2014-04-01
The nonequilibrium spectral properties of the Anderson impurity model with a chemical potential bias are investigated within a numerically exact real-time quantum Monte Carlo formalism. The two-time correlation function is computed in a form suitable for nonequilibrium dynamical mean field calculations. Additionally, the evolution of the model's spectral properties are simulated in an alternative representation, defined by a hypothetical but experimentally realizable weakly coupled auxiliary lead. The voltage splitting of the Kondo peak is confirmed and the dynamics of its formation after a coupling or gate quench are studied. This representation is shown to contain additional information about the dot's population dynamics. Further, we show that the voltage-dependent differential conductance gives a reasonable qualitative estimate of the equilibrium spectral function, but significant qualitative differences are found including incorrect trends and spurious temperature dependent effects.
Duality-symmetric supersymmetric Yang-Mills theory in three dimensions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nishino, Hitoshi; Rajpoot, Subhash
We formulate a duality-symmetric N=1 supersymmetric Yang-Mills theory in three dimensions. Our field content is (A{sub {mu}}{sup I},{lambda}{sup I},{phi}{sup I}), where the index I is for the adjoint representation of an arbitrary gauge group G. Our Hodge duality symmetry is F{sub {mu}{nu}}{sup I}=+{epsilon}{sub {mu}{nu}}{sup {rho}D}{sub {rho}{phi}}{sup I}. Because of this relationship, the presence of two physical fields A{sub {mu}}{sup I} and {phi}{sup I} within the same N=1 supermultiplet poses no problem. We can couple this multiplet to another vector multiplet (C{sub {mu}}{sup I},{chi}{sup I};B{sub {mu}{nu}}{sup I}) with 1+1 physical degrees of freedom modulo dim G. Thanks to peculiar couplings andmore » supersymmetry, the usual problem with an extra vector field in a nontrivial representation does not arise in our system.« less
Reward acts on the pFC to enhance distractor resistance of working memory representations.
Fallon, Sean James; Cools, Roshan
2014-12-01
Working memory and reward processing are often thought to be separate, unrelated processes. However, most daily activities involve integrating these two types of information, and the two processes rarely, if ever, occur in isolation. Here, we show that working memory and reward interact in a task-dependent manner and that this task-dependent interaction involves modulation of the pFC by the ventral striatum. Specifically, BOLD signal during gains relative to losses in the ventral striatum and pFC was associated not only with enhanced distractor resistance but also with impairment in the ability to update working memory representations. Furthermore, the effect of reward on working memory was accompanied by differential coupling between the ventral striatum and ignore-related regions in the pFC. Together, these data demonstrate that reward-related signals modulate the balance between cognitive stability and cognitive flexibility by altering functional coupling between the ventral striatum and the pFC.
Minimal composite Higgs models at the LHC
NASA Astrophysics Data System (ADS)
Carena, Marcela; Da Rold, Leandro; Pontón, Eduardo
2014-06-01
We consider composite Higgs models where the Higgs is a pseudo-Nambu Goldstone boson arising from the spontaneous breaking of an approximate global symmetry by some underlying strong dynamics. We focus on the SO(5) → SO(4) symmetry breaking pattern, assuming the "partial compositeness" paradigm. We study the consequences on Higgs physics of the fermionic representations produced by the strong dynamics, that mix with the Standard Model (SM) degrees of freedom. We consider models based on the lowest-dimensional representations of SO(5) that allow for the custodial protection of the coupling, i.e. the 5, 10 and 14. We find a generic suppression of the gluon fusion process, while the Higgs branching fractions can be enhanced or suppressed compared to the SM. Interestingly, a precise measurement of the Higgs boson couplings can distinguish between different realizations in the fermionic sector, thus providing crucial information about the nature of the UV dynamics.
Study for prediction of rotor/wake/fuselage interference, part 1
NASA Technical Reports Server (NTRS)
Clark, D. R.; Maskew, B.
1985-01-01
A method was developed which allows the fully coupled calculation of fuselage and rotor airloads for typical helicopter configurations in forward flight. To do this, an iterative solution is carried out based on a conventional panel representation of the fuselage and a blade element representation of the rotor where fuselage and rotor singularity strengths are determined simultaneously at each step and the rotor wake is allowed to relax (deform) in response to changes in rotor wake loading and fuselage presence. On completion of the iteration, rotor loading and inflow, fuselage singularity strength (and, hence, pressure and velocity distributions) and rotor wake are all consistent. The results of a fully coupled calculation of the flow around representative helicopter configurations are presented. The effect of fuselage components on the rotor flow field and the overall wake structure is detailed and the aerodynamic interference between the different parts of the aircraft is discussed.
Building Cognition: The Construction of Computational Representations for Scientific Discovery.
Chandrasekharan, Sanjay; Nersessian, Nancy J
2015-11-01
Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that led to a remarkable discovery in basic bioscience. Accounting for such discoveries requires a distributed cognition (DC) analysis, as DC focuses on the roles played by external representations in cognitive processes. However, DC analyses by and large have not examined scientific discovery, and they mostly focus on memory offloading, particularly how the use of existing external representations changes the nature of cognitive tasks. In contrast, we study discovery processes and argue that discoveries emerge from the processes of building the computational representation. The building process integrates manipulations in imagination and in the representation, creating a coupled cognitive system of model and modeler, where the model is incorporated into the modeler's imagination. This account extends DC significantly, and we present some of the theoretical and application implications of this extended account. Copyright © 2014 Cognitive Science Society, Inc.
Lagrangian analysis by clustering. An example in the Nordic Seas.
NASA Astrophysics Data System (ADS)
Koszalka, Inga; Lacasce, Joseph H.
2010-05-01
We propose a new method for obtaining average velocities and eddy diffusivities from Lagrangian data. Rather than grouping the drifter-derived velocities in uniform geographical bins, as is commonly done, we group a specified number of nearest-neighbor velocities. This is done via a clustering algorithm operating on the instantaneous positions of the drifters. Thus it is the data distribution itself which determines the positions of the averages and the areal extent of the clusters. A major advantage is that because the number of members is essentially the same for all clusters, the statistical accuracy is more uniform than with geographical bins. We illustrate the technique using synthetic data from a stochastic model, employing a realistic mean flow. The latter is an accurate representation of the surface currents in the Nordic Seas and is strongly inhomogeneous in space. We use the clustering algorithm to extract the mean velocities and diffusivities (both of which are known from the stochastic model). We also compare the results to those obtained with fixed geographical bins. Clustering is more successful at capturing spatial variability of the mean flow and also improves convergence in the eddy diffusivity estimates. We discuss both the future prospects and shortcomings of the new method.
Water quality analysis of the Rapur area, Andhra Pradesh, South India using multivariate techniques
NASA Astrophysics Data System (ADS)
Nagaraju, A.; Sreedhar, Y.; Thejaswi, A.; Sayadi, Mohammad Hossein
2017-10-01
The groundwater samples from Rapur area were collected from different sites to evaluate the major ion chemistry. The large number of data can lead to difficulties in the integration, interpretation, and representation of the results. Two multivariate statistical methods, hierarchical cluster analysis (HCA) and factor analysis (FA), were applied to evaluate their usefulness to classify and identify geochemical processes controlling groundwater geochemistry. Four statistically significant clusters were obtained from 30 sampling stations. This has resulted two important clusters viz., cluster 1 (pH, Si, CO3, Mg, SO4, Ca, K, HCO3, alkalinity, Na, Na + K, Cl, and hardness) and cluster 2 (EC and TDS) which are released to the study area from different sources. The application of different multivariate statistical techniques, such as principal component analysis (PCA), assists in the interpretation of complex data matrices for a better understanding of water quality of a study area. From PCA, it is clear that the first factor (factor 1), accounted for 36.2% of the total variance, was high positive loading in EC, Mg, Cl, TDS, and hardness. Based on the PCA scores, four significant cluster groups of sampling locations were detected on the basis of similarity of their water quality.
Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes
Jurek, Anna; Nugent, Chris; Bi, Yaxin; Wu, Shengli
2014-01-01
Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks. PMID:25014095
Clustering-based ensemble learning for activity recognition in smart homes.
Jurek, Anna; Nugent, Chris; Bi, Yaxin; Wu, Shengli
2014-07-10
Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.
Spatiotemporal coding of inputs for a system of globally coupled phase oscillators
NASA Astrophysics Data System (ADS)
Wordsworth, John; Ashwin, Peter
2008-12-01
We investigate the spatiotemporal coding of low amplitude inputs to a simple system of globally coupled phase oscillators with coupling function g(ϕ)=-sin(ϕ+α)+rsin(2ϕ+β) that has robust heteroclinic cycles (slow switching between cluster states). The inputs correspond to detuning of the oscillators. It was recently noted that globally coupled phase oscillators can encode their frequencies in the form of spatiotemporal codes of a sequence of cluster states [P. Ashwin, G. Orosz, J. Wordsworth, and S. Townley, SIAM J. Appl. Dyn. Syst. 6, 728 (2007)]. Concentrating on the case of N=5 oscillators we show in detail how the spatiotemporal coding can be used to resolve all of the information that relates the individual inputs to each other, providing that a long enough time series is considered. We investigate robustness to the addition of noise and find a remarkable stability, especially of the temporal coding, to the addition of noise even for noise of a comparable magnitude to the inputs.
ERIC Educational Resources Information Center
Lynch, Michael F.; Willett, Peter
1987-01-01
Discusses research into chemical information and document retrieval systems at the University of Sheffield. Highlights include the use of cluster analysis methods for document retrieval and drug design, representation and searching of files of generic chemical structures, and the application of parallel computer hardware to information retrieval.…
The Role of Consonant/Vowel Organization in Perceptual Discrimination
ERIC Educational Resources Information Center
Chetail, Fabienne; Drabs, Virginie; Content, Alain
2014-01-01
According to a recent hypothesis, the CV pattern (i.e., the arrangement of consonant and vowel letters) constrains the mental representation of letter strings, with each vowel or vowel cluster being the core of a unit. Six experiments with the same/different task were conducted to test whether this structure is extracted prelexically. In the…
Intergroup Stereotypes of Working Class Blacks and Whites: Implications for Stereotype Threat.
ERIC Educational Resources Information Center
Niemann, Yolanda Flores; O'Connor, Elizabeth; McClorie, Randall
1998-01-01
Examined stereotypes of urban blacks and whites at a flea market with 68 black respondents, and at another flea market with 20 white respondents. Cluster-analysis results show that blacks have a relatively complex, multidimensional representation of themselves and of whites, while whites seem to have a more simplistic and negative view of blacks.…
The Meaning of English Words across Cultures, with a Focus on Cameroon and Hong Kong
ERIC Educational Resources Information Center
Bobda, Augustin Simo
2009-01-01
A word, even when considered monosemic, generally has a cluster of meanings, depending on the mental representation of the referent by the speaker/writer or listener/reader. The variation is even more noticeable across cultures. This paper investigates the different ways in which cultural knowledge helps in the interpretation of English lexical…
Pansharpening via coupled triple factorization dictionary learning
Skau, Erik; Wohlberg, Brendt; Krim, Hamid; ...
2016-03-01
Data fusion is the operation of integrating data from different modalities to construct a single consistent representation. Here, this paper proposes variations of coupled dictionary learning through an additional factorization. One variation of this model is applicable to the pansharpening data fusion problem. Real world pansharpening data was applied to train and test our proposed formulation. The results demonstrate that the data fusion model can successfully be applied to the pan-sharpening problem.
Coronal Mass Ejection Data Clustering and Visualization of Decision Trees
NASA Astrophysics Data System (ADS)
Ma, Ruizhe; Angryk, Rafal A.; Riley, Pete; Filali Boubrahimi, Soukaina
2018-05-01
Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.
NASA Astrophysics Data System (ADS)
Rahman, Md. Habibur; Matin, M. A.; Salma, Umma
2017-12-01
The precipitation patterns of seventeen locations in Bangladesh from 1961 to 2014 were studied using a cluster analysis and metric multidimensional scaling. In doing so, the current research applies four major hierarchical clustering methods to precipitation in conjunction with different dissimilarity measures and metric multidimensional scaling. A variety of clustering algorithms were used to provide multiple clustering dendrograms for a mixture of distance measures. The dendrogram of pre-monsoon rainfall for the seventeen locations formed five clusters. The pre-monsoon precipitation data for the areas of Srimangal and Sylhet were located in two clusters across the combination of five dissimilarity measures and four hierarchical clustering algorithms. The single linkage algorithm with Euclidian and Manhattan distances, the average linkage algorithm with the Minkowski distance, and Ward's linkage algorithm provided similar results with regard to monsoon precipitation. The results of the post-monsoon and winter precipitation data are shown in different types of dendrograms with disparate combinations of sub-clusters. The schematic geometrical representations of the precipitation data using metric multidimensional scaling showed that the post-monsoon rainfall of Cox's Bazar was located far from those of the other locations. The results of a box-and-whisker plot, different clustering techniques, and metric multidimensional scaling indicated that the precipitation behaviour of Srimangal and Sylhet during the pre-monsoon season, Cox's Bazar and Sylhet during the monsoon season, Maijdi Court and Cox's Bazar during the post-monsoon season, and Cox's Bazar and Khulna during the winter differed from those at other locations in Bangladesh.
Lloyd-Jones, Toby J; Roberts, Mark V; Leek, E Charles; Fouquet, Nathalie C; Truchanowicz, Ewa G
2012-01-01
Little is known about the timing of activating memory for objects and their associated perceptual properties, such as colour, and yet this is important for theories of human cognition. We investigated the time course associated with early cognitive processes related to the activation of object shape and object shape+colour representations respectively, during memory retrieval as assessed by repetition priming in an event-related potential (ERP) study. The main findings were as follows: (1) we identified a unique early modulation of mean ERP amplitude during the N1 that was associated with the activation of object shape independently of colour; (2) we also found a subsequent early P2 modulation of mean amplitude over the same electrode clusters associated with the activation of object shape+colour representations; (3) these findings were apparent across both familiar (i.e., correctly coloured - yellow banana) and novel (i.e., incorrectly coloured - blue strawberry) objects; and (4) neither of the modulations of mean ERP amplitude were evident during the P3. Together the findings delineate the timing of object shape and colour memory systems and support the notion that perceptual representations of object shape mediate the retrieval of temporary shape+colour representations for familiar and novel objects.
Lloyd-Jones, Toby J.; Roberts, Mark V.; Leek, E. Charles; Fouquet, Nathalie C.; Truchanowicz, Ewa G.
2012-01-01
Little is known about the timing of activating memory for objects and their associated perceptual properties, such as colour, and yet this is important for theories of human cognition. We investigated the time course associated with early cognitive processes related to the activation of object shape and object shape+colour representations respectively, during memory retrieval as assessed by repetition priming in an event-related potential (ERP) study. The main findings were as follows: (1) we identified a unique early modulation of mean ERP amplitude during the N1 that was associated with the activation of object shape independently of colour; (2) we also found a subsequent early P2 modulation of mean amplitude over the same electrode clusters associated with the activation of object shape+colour representations; (3) these findings were apparent across both familiar (i.e., correctly coloured – yellow banana) and novel (i.e., incorrectly coloured - blue strawberry) objects; and (4) neither of the modulations of mean ERP amplitude were evident during the P3. Together the findings delineate the timing of object shape and colour memory systems and support the notion that perceptual representations of object shape mediate the retrieval of temporary shape+colour representations for familiar and novel objects. PMID:23155393
Group-sparse representation with dictionary learning for medical image denoising and fusion.
Li, Shutao; Yin, Haitao; Fang, Leyuan
2012-12-01
Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.
NASA Astrophysics Data System (ADS)
Satra, P.; Carsky, J.
2018-04-01
Our research is looking at the travel behaviour from a macroscopic view, taking one municipality as a basic unit. The travel behaviour of one municipality as a whole is becoming one piece of a data in the research of travel behaviour of a larger area, perhaps a country. A data pre-processing is used to cluster the municipalities in groups, which show similarities in their travel behaviour. Such groups can be then researched for reasons of their prevailing pattern of travel behaviour without any distortion caused by municipalities with a different pattern. This paper deals with actual settings of the clustering process, which is based on Bayesian statistics, particularly the mixture model. An optimization of the settings parameters based on correlation of pointer model parameters and relative number of data in clusters is helpful, however not fully reliable method. Thus, method for graphic representation of clusters needs to be developed in order to check their quality. A training of the setting parameters in 2D has proven to be a beneficial method, because it allows visual control of the produced clusters. The clustering better be applied on separate groups of municipalities, where competition of only identical transport modes can be found.
Wang, Chenglin; Tang, Yunchao; Zou, Xiangjun; Luo, Lufeng; Chen, Xiong
2017-01-01
Recognition and matching of litchi fruits are critical steps for litchi harvesting robots to successfully grasp litchi. However, due to the randomness of litchi growth, such as clustered growth with uncertain number of fruits and random occlusion by leaves, branches and other fruits, the recognition and matching of the fruit become a challenge. Therefore, this study firstly defined mature litchi fruit as three clustered categories. Then an approach for recognition and matching of clustered mature litchi fruit was developed based on litchi color images acquired by binocular charge-coupled device (CCD) color cameras. The approach mainly included three steps: (1) calibration of binocular color cameras and litchi image acquisition; (2) segmentation of litchi fruits using four kinds of supervised classifiers, and recognition of the pre-defined categories of clustered litchi fruit using a pixel threshold method; and (3) matching the recognized clustered fruit using a geometric center-based matching method. The experimental results showed that the proposed recognition method could be robust against the influences of varying illumination and occlusion conditions, and precisely recognize clustered litchi fruit. In the tested 432 clustered litchi fruits, the highest and lowest average recognition rates were 94.17% and 92.00% under sunny back-lighting and partial occlusion, and sunny front-lighting and non-occlusion conditions, respectively. From 50 pairs of tested images, the highest and lowest matching success rates were 97.37% and 91.96% under sunny back-lighting and non-occlusion, and sunny front-lighting and partial occlusion conditions, respectively. PMID:29112177
Ab initio multireference study of the BN molecule
NASA Technical Reports Server (NTRS)
Martin, J. M. L.; Lee, Timothy J.; Scuseria, Gustavo E.; Taylor, Peter R.
1992-01-01
The lowest 1Sigma(+) and 3Pi states of the BN molecule are studied using multireference configuration interaction (MRCI) and averaged coupled-pair functional (ACPF) methods and large atomic natural orbital (ANO) basis sets, as well as several coupled cluster methods. Our calculations strongly support a 3Pi ground state, but the a1Sigma(+) state lies only 381 +/- 100/cm higher. The a1Sigma(+) state wave function exhibits strong multireference character and, consequently, the predictions of the perturbationally-based single-reference CCSD(T) coupled cluster method are not as reliable in this case as the multireference results. The theoretical predictions for the spectroscopic constants of BN are in good agreement with experiment for the Chi3Pi state, but strongly suggest a misassignment of the fundamental vibrational frequency for the a1Sigma(+) state.
Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions.
Hyafil, Alexandre; Giraud, Anne-Lise; Fontolan, Lorenzo; Gutkin, Boris
2015-11-01
Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions. Copyright © 2015 Elsevier Ltd. All rights reserved.
Scaling and correlations in three bus-transport networks of China
NASA Astrophysics Data System (ADS)
Xu, Xinping; Hu, Junhui; Liu, Feng; Liu, Lianshou
2007-01-01
We report the statistical properties of three bus-transport networks (BTN) in three different cities of China. These networks are composed of a set of bus lines and stations serviced by these. Network properties, including the degree distribution, clustering and average path length are studied in different definitions of network topology. We explore scaling laws and correlations that may govern intrinsic features of such networks. Besides, we create a weighted network representation for BTN with lines mapped to nodes and number of common stations to weights between lines. In such a representation, the distributions of degree, strength and weight are investigated. A linear behavior between strength and degree s(k)∼k is also observed.
Dynamic interactions between visual working memory and saccade target selection
Schneegans, Sebastian; Spencer, John P.; Schöner, Gregor; Hwang, Seongmin; Hollingworth, Andrew
2014-01-01
Recent psychophysical experiments have shown that working memory for visual surface features interacts with saccadic motor planning, even in tasks where the saccade target is unambiguously specified by spatial cues. Specifically, a match between a memorized color and the color of either the designated target or a distractor stimulus influences saccade target selection, saccade amplitudes, and latencies in a systematic fashion. To elucidate these effects, we present a dynamic neural field model in combination with new experimental data. The model captures the neural processes underlying visual perception, working memory, and saccade planning relevant to the psychophysical experiment. It consists of a low-level visual sensory representation that interacts with two separate pathways: a spatial pathway implementing spatial attention and saccade generation, and a surface feature pathway implementing color working memory and feature attention. Due to bidirectional coupling between visual working memory and feature attention in the model, the working memory content can indirectly exert an effect on perceptual processing in the low-level sensory representation. This in turn biases saccadic movement planning in the spatial pathway, allowing the model to quantitatively reproduce the observed interaction effects. The continuous coupling between representations in the model also implies that modulation should be bidirectional, and model simulations provide specific predictions for complementary effects of saccade target selection on visual working memory. These predictions were empirically confirmed in a new experiment: Memory for a sample color was biased toward the color of a task-irrelevant saccade target object, demonstrating the bidirectional coupling between visual working memory and perceptual processing. PMID:25228628
Steady-state, lumped-parameter model for capacitor-run, single-phase induction motors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Umans, S.D.
1996-01-01
This paper documents a technique for deriving a steady-state, lumped-parameter model for capacitor-run, single-phase induction motors. The objective of this model is to predict motor performance parameters such as torque, loss distribution, and efficiency as a function of applied voltage and motor speed as well as the temperatures of the stator windings and of the rotor. The model includes representations of both the main and auxiliary windings (including arbitrary external impedances) and also the effects of core and rotational losses. The technique can be easily implemented and the resultant model can be used in a wide variety of analyses tomore » investigate motor performance as a function of load, speed, and winding and rotor temperatures. The technique is based upon a coupled-circuit representation of the induction motor. A notable feature of the model is the technique used for representing core loss. In equivalent-circuit representations of transformers and induction motors, core loss is typically represented by a core-loss resistance in shunt with the magnetizing inductance. In order to maintain the coupled-circuit viewpoint adopted in this paper, this technique was modified slightly; core loss is represented by a set of core-loss resistances connected to the ``secondaries`` of a set of windings which perfectly couple to the air-gap flux of the motor. An example of the technique is presented based upon a 3.5 kW, single-phase, capacitor-run motor and the validity of the technique is demonstrated by comparing predicted and measured motor performance.« less
A coupled-oscillator model of olfactory bulb gamma oscillations
2017-01-01
The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity. PMID:29140973
NASA Astrophysics Data System (ADS)
Jungclaus, J. H.; Fischer, N.; Haak, H.; Lohmann, K.; Marotzke, J.; Matei, D.; Mikolajewicz, U.; Notz, D.; von Storch, J. S.
2013-06-01
MPI-ESM is a new version of the global Earth system model developed at the Max Planck Institute for Meteorology. This paper describes the ocean state and circulation as well as basic aspects of variability in simulations contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The performance of the ocean/sea-ice model MPIOM, coupled to a new version of the atmosphere model ECHAM6 and modules for land surface and ocean biogeochemistry, is assessed for two model versions with different grid resolution in the ocean. The low-resolution configuration has a nominal resolution of 1.5°, whereas the higher resolution version features a quasiuniform, eddy-permitting global resolution of 0.4°. The paper focuses on important oceanic features, such as surface temperature and salinity, water mass distribution, large-scale circulation, and heat and freshwater transports. In general, these integral quantities are simulated well in comparison with observational estimates, and improvements in comparison with the predecessor system are documented; for example, for tropical variability and sea ice representation. Introducing an eddy-permitting grid configuration in the ocean leads to improvements, in particular, in the representation of interior water mass properties in the Atlantic and in the representation of important ocean currents, such as the Agulhas and Equatorial current systems. In general, however, there are more similarities than differences between the two grid configurations, and several shortcomings, known from earlier versions of the coupled model, prevail.
Asymptotic freedom in certain S O (N ) and S U (N ) models
NASA Astrophysics Data System (ADS)
Einhorn, Martin B.; Jones, D. R. Timothy
2017-09-01
We calculate the β -functions for S O (N ) and S U (N ) gauge theories coupled to adjoint and fundamental scalar representations, correcting longstanding, previous results. We explore the constraints on N resulting from requiring asymptotic freedom for all couplings. When we take into account the actual allowed behavior of the gauge coupling, the minimum value of N in both cases turns out to be larger than realized in earlier treatments. We also show that in the large N limit, both models have large regions of parameter space corresponding to total asymptotic freedom.