Maximally informative pairwise interactions in networks

PubMed Central

Fitzgerald, Jeffrey D.; Sharpee, Tatyana O.

2010-01-01

Several types of biological networks have recently been shown to be accurately described by a maximum entropy model with pairwise interactions, also known as the Ising model. Here we present an approach for finding the optimal mappings between input signals and network states that allow the network to convey the maximal information about input signals drawn from a given distribution. This mapping also produces a set of linear equations for calculating the optimal Ising-model coupling constants, as well as geometric properties that indicate the applicability of the pairwise Ising model. We show that the optimal pairwise interactions are on average zero for Gaussian and uniformly distributed inputs, whereas they are nonzero for inputs approximating those in natural environments. These nonzero network interactions are predicted to increase in strength as the noise in the response functions of each network node increases. This approach also suggests ways for how interactions with unmeasured parts of the network can be inferred from the parameters of response functions for the measured network nodes. PMID:19905153

Dynamical pairwise entanglement and two-point correlations in the three-ligand spin-star structure

NASA Astrophysics Data System (ADS)

Motamedifar, M.

2017-10-01

We consider the three-ligand spin-star structure through homogeneous Heisenberg interactions (XXX-3LSSS) in the framework of dynamical pairwise entanglement. It is shown that the time evolution of the central qubit ;one-particle; state (COPS) brings about the generation of quantum W states at periodical time instants. On the contrary, W states cannot be generated from the time evolution of a ligand ;one-particle; state (LOPS). We also investigate the dynamical behavior of two-point quantum correlations as well as the expectation values of the different spin-components for each element in the XXX-3LSSS. It is found that when a W state is generated, the same value of the concurrence between any two arbitrary qubits arises from the xx and yy two-point quantum correlations. On the opposite, zz quantum correlation between any two qubits vanishes at these time instants.

Scalable Creation of Long-Lived Multipartite Entanglement.

PubMed

Kaufmann, H; Ruster, T; Schmiegelow, C T; Luda, M A; Kaushal, V; Schulz, J; von Lindenfels, D; Schmidt-Kaler, F; Poschinger, U G

2017-10-13

We demonstrate the deterministic generation of multipartite entanglement based on scalable methods. Four qubits are encoded in ^{40}Ca^{+}, stored in a microstructured segmented Paul trap. These qubits are sequentially entangled by laser-driven pairwise gate operations. Between these, the qubit register is dynamically reconfigured via ion shuttling operations, where ion crystals are separated and merged, and ions are moved in and out of a fixed laser interaction zone. A sequence consisting of three pairwise entangling gates yields a four-ion Greenberger-Horne-Zeilinger state |ψ⟩=(1/sqrt[2])(|0000⟩+|1111⟩), and full quantum state tomography reveals a state fidelity of 94.4(3)%. We analyze the decoherence of this state and employ dynamic decoupling on the spatially distributed constituents to maintain 69(5)% coherence at a storage time of 1.1 sec.

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Zengfu

2018-04-01

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

Automatic classification of protein structures relying on similarities between alignments

PubMed Central

2012-01-01

Background Identification of protein structural cores requires isolation of sets of proteins all sharing a same subset of structural motifs. In the context of an ever growing number of available 3D protein structures, standard and automatic clustering algorithms require adaptations so as to allow for efficient identification of such sets of proteins. Results When considering a pair of 3D structures, they are stated as similar or not according to the local similarities of their matching substructures in a structural alignment. This binary relation can be represented in a graph of similarities where a node represents a 3D protein structure and an edge states that two 3D protein structures are similar. Therefore, classifying proteins into structural families can be viewed as a graph clustering task. Unfortunately, because such a graph encodes only pairwise similarity information, clustering algorithms may include in the same cluster a subset of 3D structures that do not share a common substructure. In order to overcome this drawback we first define a ternary similarity on a triple of 3D structures as a constraint to be satisfied by the graph of similarities. Such a ternary constraint takes into account similarities between pairwise alignments, so as to ensure that the three involved protein structures do have some common substructure. We propose hereunder a modification algorithm that eliminates edges from the original graph of similarities and gives a reduced graph in which no ternary constraints are violated. Our approach is then first to build a graph of similarities, then to reduce the graph according to the modification algorithm, and finally to apply to the reduced graph a standard graph clustering algorithm. Such method was used for classifying ASTRAL-40 non-redundant protein domains, identifying significant pairwise similarities with Yakusa, a program devised for rapid 3D structure alignments. Conclusions We show that filtering similarities prior to standard graph based clustering process by applying ternary similarity constraints i) improves the separation of proteins of different classes and consequently ii) improves the classification quality of standard graph based clustering algorithms according to the reference classification SCOP. PMID:22974051

PTM Along Track Algorithm to Maintain Spacing During Same Direction Pair-Wise Trajectory Management Operations

NASA Technical Reports Server (NTRS)

Carreno, Victor A.

2015-01-01

Pair-wise Trajectory Management (PTM) is a cockpit based delegated responsibility separation standard. When an air traffic service provider gives a PTM clearance to an aircraft and the flight crew accepts the clearance, the flight crew will maintain spacing and separation from a designated aircraft. A PTM along track algorithm will receive state information from the designated aircraft and from the own ship to produce speed guidance for the flight crew to maintain spacing and separation

A multivariate extension of mutual information for growing neural networks.

PubMed

Ball, Kenneth R; Grant, Christopher; Mundy, William R; Shafer, Timothy J

2017-11-01

Recordings of neural network activity in vitro are increasingly being used to assess the development of neural network activity and the effects of drugs, chemicals and disease states on neural network function. The high-content nature of the data derived from such recordings can be used to infer effects of compounds or disease states on a variety of important neural functions, including network synchrony. Historically, synchrony of networks in vitro has been assessed either by determination of correlation coefficients (e.g. Pearson's correlation), by statistics estimated from cross-correlation histograms between pairs of active electrodes, and/or by pairwise mutual information and related measures. The present study examines the application of Normalized Multiinformation (NMI) as a scalar measure of shared information content in a multivariate network that is robust with respect to changes in network size. Theoretical simulations are designed to investigate NMI as a measure of complexity and synchrony in a developing network relative to several alternative approaches. The NMI approach is applied to these simulations and also to data collected during exposure of in vitro neural networks to neuroactive compounds during the first 12 days in vitro, and compared to other common measures, including correlation coefficients and mean firing rates of neurons. NMI is shown to be more sensitive to developmental effects than first order synchronous and nonsynchronous measures of network complexity. Finally, NMI is a scalar measure of global (rather than pairwise) mutual information in a multivariate network, and hence relies on less assumptions for cross-network comparisons than historical approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

SVM-dependent pairwise HMM: an application to protein pairwise alignments.

PubMed

Orlando, Gabriele; Raimondi, Daniele; Khan, Taushif; Lenaerts, Tom; Vranken, Wim F

2017-12-15

Methods able to provide reliable protein alignments are crucial for many bioinformatics applications. In the last years many different algorithms have been developed and various kinds of information, from sequence conservation to secondary structure, have been used to improve the alignment performances. This is especially relevant for proteins with highly divergent sequences. However, recent works suggest that different features may have different importance in diverse protein classes and it would be an advantage to have more customizable approaches, capable to deal with different alignment definitions. Here we present Rigapollo, a highly flexible pairwise alignment method based on a pairwise HMM-SVM that can use any type of information to build alignments. Rigapollo lets the user decide the optimal features to align their protein class of interest. It outperforms current state of the art methods on two well-known benchmark datasets when aligning highly divergent sequences. A Python implementation of the algorithm is available at http://ibsquare.be/rigapollo. wim.vranken@vub.be. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The structure of pairwise correlation in mouse primary visual cortex reveals functional organization in the absence of an orientation map.

PubMed

Denman, Daniel J; Contreras, Diego

2014-10-01

Neural responses to sensory stimuli are not independent. Pairwise correlation can reduce coding efficiency, occur independent of stimulus representation, or serve as an additional channel of information, depending on the timescale of correlation and the method of decoding. Any role for correlation depends on its magnitude and structure. In sensory areas with maps, like the orientation map in primary visual cortex (V1), correlation is strongly related to the underlying functional architecture, but it is unclear whether this correlation structure is an essential feature of the system or arises from the arrangement of cells in the map. We assessed the relationship between functional architecture and pairwise correlation by measuring both synchrony and correlated spike count variability in mouse V1, which lacks an orientation map. We observed significant pairwise synchrony, which was organized by distance and relative orientation preference between cells. We also observed nonzero correlated variability in both the anesthetized (0.16) and awake states (0.18). Our results indicate that the structure of pairwise correlation is maintained in the absence of an underlying anatomical organization and may be an organizing principle of the mammalian visual system preserved by nonrandom connectivity within local networks. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Necessary condition for local distinguishability of maximally entangled states: Beyond orthogonality preservation

NASA Astrophysics Data System (ADS)

Singal, Tanmay; Rahaman, Ramij; Ghosh, Sibasish; Kar, Guruprasad

2017-10-01

The (im)possibility of local distinguishability of orthogonal multipartite quantum states still remains an intriguing question. Beyond C3⊗C3 , the problem remains unsolved even for maximally entangled states (MESs). So far, the only known condition for the local distinguishability of states is the well-known orthogonality preservation (OP). Using an upper bound on the locally accessible information for bipartite states, we derive a very simple necessary condition for any set of pairwise orthogonal MESs in Cd⊗Cd to be perfectly locally distinguishable. It is seen that particularly when the number of pairwise orthogonal MES states in Cd⊗Cd is equal to d , then this necessary condition, along with the OP condition, imposes more constraints (for said states to be perfectly locally distinguishable) than the OP condition does. When testing this condition for the local distinguishability of all sets of four generalized Bell states in C4⊗C4 , we find that it is not only necessary but also sufficient to determine their local distinguishability. This demonstrates that the aforementioned upper bound may play a significant role in the general scenario of local distinguishability of bipartite states.

Quantum Discord in Photon-Added Glauber Coherent States of GHZ-Type

NASA Astrophysics Data System (ADS)

Daoud, M.; Kaydi, W.; El Hadfi, H.

2015-11-01

We investigate the influence of photon excitations on quantum correlations in tripartite Glauber coherent states of Greenberger-Horne-Zeilinger type (GHZ-type). The pairwise correlations are measured by means of the entropy-based quantum discord. We also analyze the monogamy property of quantum discord in this class of tripartite states in terms of the strength of Glauber coherent states and the photon excitation order.

Information-geometric measures estimate neural interactions during oscillatory brain states

PubMed Central

Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami

2014-01-01

The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain. PMID:24605089

Information-geometric measures estimate neural interactions during oscillatory brain states.

PubMed

Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami

2014-01-01

The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

Living network meta-analysis compared with pairwise meta-analysis in comparative effectiveness research: empirical study.

PubMed

Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias; Salanti, Georgia

2018-02-28

To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) ("living" network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (P<0.10). Cumulative pairwise and network meta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10 comparisons only network meta-analysis provided strong evidence against the null hypothesis (P=0.002). The median time to strong evidence against the null hypothesis was 19 years with living network meta-analysis and 23 years with living pairwise meta-analysis (hazard ratio 2.78, 95% confidence interval 1.00 to 7.72, P=0.05). Studies directly comparing the treatments of interest continued to be published for eight comparisons after strong evidence had become evident in network meta-analysis. In comparative effectiveness research, prospectively planned living network meta-analyses produced strong evidence against the null hypothesis more often and earlier than conventional, pairwise meta-analyses. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Living network meta-analysis compared with pairwise meta-analysis in comparative effectiveness research: empirical study

PubMed Central

Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias

2018-01-01

Abstract Objective To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) (“living” network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Design Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Data sources Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Eligibility criteria for study selection Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (P<0.10). Outcomes and analysis Cumulative pairwise and network meta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. Results 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10 comparisons only network meta-analysis provided strong evidence against the null hypothesis (P=0.002). The median time to strong evidence against the null hypothesis was 19 years with living network meta-analysis and 23 years with living pairwise meta-analysis (hazard ratio 2.78, 95% confidence interval 1.00 to 7.72, P=0.05). Studies directly comparing the treatments of interest continued to be published for eight comparisons after strong evidence had become evident in network meta-analysis. Conclusions In comparative effectiveness research, prospectively planned living network meta-analyses produced strong evidence against the null hypothesis more often and earlier than conventional, pairwise meta-analyses. PMID:29490922

Amino acid positions subject to multiple coevolutionary constraints can be robustly identified by their eigenvector network centrality scores.

PubMed

Parente, Daniel J; Ray, J Christian J; Swint-Kruse, Liskin

2015-12-01

As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded coevolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; "central" positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise coevolution scores: instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints-detectable by divergent algorithms--that occur at key protein locations. Finally, we discuss the fact that multiple patterns coexist in evolutionary data that, together, give rise to emergent protein functions. © 2015 Wiley Periodicals, Inc.

Classification of complex information: inference of co-occurring affective states from their expressions in speech.

PubMed

Sobol-Shikler, Tal; Robinson, Peter

2010-07-01

We present a classification algorithm for inferring affective states (emotions, mental states, attitudes, and the like) from their nonverbal expressions in speech. It is based on the observations that affective states can occur simultaneously and different sets of vocal features, such as intonation and speech rate, distinguish between nonverbal expressions of different affective states. The input to the inference system was a large set of vocal features and metrics that were extracted from each utterance. The classification algorithm conducted independent pairwise comparisons between nine affective-state groups. The classifier used various subsets of metrics of the vocal features and various classification algorithms for different pairs of affective-state groups. Average classification accuracy of the 36 pairwise machines was 75 percent, using 10-fold cross validation. The comparison results were consolidated into a single ranked list of the nine affective-state groups. This list was the output of the system and represented the inferred combination of co-occurring affective states for the analyzed utterance. The inference accuracy of the combined machine was 83 percent. The system automatically characterized over 500 affective state concepts from the Mind Reading database. The inference of co-occurring affective states was validated by comparing the inferred combinations to the lexical definitions of the labels of the analyzed sentences. The distinguishing capabilities of the system were comparable to human performance.

On the streaming model for redshift-space distortions

NASA Astrophysics Data System (ADS)

Kuruvilla, Joseph; Porciani, Cristiano

2018-06-01

The streaming model describes the mapping between real and redshift space for 2-point clustering statistics. Its key element is the probability density function (PDF) of line-of-sight pairwise peculiar velocities. Following a kinetic-theory approach, we derive the fundamental equations of the streaming model for ordered and unordered pairs. In the first case, we recover the classic equation while we demonstrate that modifications are necessary for unordered pairs. We then discuss several statistical properties of the pairwise velocities for DM particles and haloes by using a suite of high-resolution N-body simulations. We test the often used Gaussian ansatz for the PDF of pairwise velocities and discuss its limitations. Finally, we introduce a mixture of Gaussians which is known in statistics as the generalised hyperbolic distribution and show that it provides an accurate fit to the PDF. Once inserted in the streaming equation, the fit yields an excellent description of redshift-space correlations at all scales that vastly outperforms the Gaussian and exponential approximations. Using a principal-component analysis, we reduce the complexity of our model for large redshift-space separations. Our results increase the robustness of studies of anisotropic galaxy clustering and are useful for extending them towards smaller scales in order to test theories of gravity and interacting dark-energy models.

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

PubMed

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Effective equilibrium states in the colored-noise model for active matter I. Pairwise forces in the Fox and unified colored noise approximations

NASA Astrophysics Data System (ADS)

Wittmann, René; Maggi, C.; Sharma, A.; Scacchi, A.; Brader, J. M.; Marini Bettolo Marconi, U.

2017-11-01

The equations of motion of active systems can be modeled in terms of Ornstein-Uhlenbeck processes (OUPs) with appropriate correlators. For further theoretical studies, these should be approximated to yield a Markovian picture for the dynamics and a simplified steady-state condition. We perform a comparative study of the unified colored noise approximation (UCNA) and the approximation scheme by Fox recently employed within this context. We review the approximations necessary to define effective interaction potentials in the low-density limit and study the conditions for which these represent the behavior observed in two-body simulations for the OUPs model and active Brownian particles. The demonstrated limitations of the theory for potentials with a negative slope or curvature can be qualitatively corrected by a new empirical modification. In general, we find that in the presence of translational white noise the Fox approach is more accurate. Finally, we examine an alternative way to define a force-balance condition in the limit of small activity.

Weak Higher-Order Interactions in Macroscopic Functional Networks of the Resting Brain.

PubMed

Huang, Xuhui; Xu, Kaibin; Chu, Congying; Jiang, Tianzi; Yu, Shan

2017-10-25

Interactions among different brain regions are usually examined through functional connectivity (FC) analysis, which is exclusively based on measuring pairwise correlations in activities. However, interactions beyond the pairwise level, that is, higher-order interactions (HOIs), are vital in understanding the behavior of many complex systems. So far, whether HOIs exist among brain regions and how they can affect the brain's activities remains largely elusive. To address these issues, here, we analyzed blood oxygenation level-dependent (BOLD) signals recorded from six typical macroscopic functional networks of the brain in 100 human subjects (46 males and 54 females) during the resting state. Through examining the binarized BOLD signals, we found that HOIs within and across individual networks were both very weak regardless of the network size, topology, degree of spatial proximity, spatial scales, and whether the global signal was regressed. To investigate the potential mechanisms underlying the weak HOIs, we analyzed the dynamics of a network model and also found that HOIs were generally weak within a wide range of key parameters provided that the overall dynamic feature of the model was similar to the empirical data and it was operating close to a linear fluctuation regime. Our results suggest that weak HOI may be a general property of brain's macroscopic functional networks, which implies the dominance of pairwise interactions in shaping brain activities at such a scale and warrants the validity of widely used pairwise-based FC approaches. SIGNIFICANCE STATEMENT To explain how activities of different brain areas are coordinated through interactions is essential to revealing the mechanisms underlying various brain functions. Traditionally, such an interaction structure is commonly studied using pairwise-based functional network analyses. It is unclear whether the interactions beyond the pairwise level (higher-order interactions or HOIs) play any role in this process. Here, we show that HOIs are generally weak in macroscopic brain networks. We also suggest a possible dynamical mechanism that may underlie this phenomenon. These results provide plausible explanation for the effectiveness of widely used pairwise-based approaches in analyzing brain networks. More importantly, it reveals a previously unknown, simple organization of the brain's macroscopic functional systems. Copyright © 2017 the authors 0270-6474/17/3710481-17$15.00/0.

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

PubMed Central

Momeni, Babak; Xie, Li; Shou, Wenying

2017-01-01

Pairwise models are commonly used to describe many-species communities. In these models, an individual receives additive fitness effects from pairwise interactions with each species in the community ('additivity assumption'). All pairwise interactions are typically represented by a single equation where parameters reflect signs and strengths of fitness effects ('universality assumption'). Here, we show that a single equation fails to qualitatively capture diverse pairwise microbial interactions. We build mechanistic reference models for two microbial species engaging in commonly-found chemical-mediated interactions, and attempt to derive pairwise models. Different equations are appropriate depending on whether a mediator is consumable or reusable, whether an interaction is mediated by one or more mediators, and sometimes even on quantitative details of the community (e.g. relative fitness of the two species, initial conditions). Our results, combined with potential violation of the additivity assumption in many-species communities, suggest that pairwise modeling will often fail to predict microbial dynamics. DOI: http://dx.doi.org/10.7554/eLife.25051.001 PMID:28350295

Adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization

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.

Hunger enhances consistent economic choices in non-human primates.

PubMed

Yamada, Hiroshi

2017-05-24

Hunger and thirst are fundamental biological processes that drive consumption behavior in humans and non-human animals. While the existing literature in neuroscience suggests that these satiety states change how consumable rewards are represented in the brain, it remains unclear as to how they change animal choice behavior and the underlying economic preferences. Here, I used combined techniques from experimental economics, psychology, and neuroscience to measure food preferences of marmoset monkeys (Callithrix jacchus), a recently developed primate model for neuroscience. Hunger states of animals were manipulated by scheduling feeding intervals, resulting in three different conditions: sated, non-sated, and hungry. During these hunger states, animals performed pairwise choices of food items, which included all possible pairwise combinations of five different food items except for same-food pairs. Results showed that hunger enhanced economic rationality, evident as a decrease of transitivity violations (item A was preferred to item B, and B to C, but C was preferred to A). Further analysis demonstrated that hungry monkeys chose more-preferred items over less-preferred items in a more deterministic manner, while the individual food preferences appeared to remain stable across hunger states. These results suggest that hunger enhances consistent choice behavior and shifts animals towards efficient outcome maximization.

O (6 ) algebraic theory of three nonrelativistic quarks bound by spin-independent interactions

NASA Astrophysics Data System (ADS)

Dmitrašinović, V.; Salom, Igor

2018-05-01

We apply the newly developed theory of permutation-symmetric O (6 ) hyperspherical harmonics to the quantum-mechanical problem of three nonrelativistic quarks confined by a spin-independent three-quark potential. We use our previously derived results to reduce the three-body Schrödinger equation to a set of coupled ordinary differential equations in the hyper-radius R with coupling coefficients expressed entirely in terms of (i) a few interaction-dependent O (6 ) expansion coefficients and (ii) O (6 ) hyperspherical harmonics matrix elements that have been evaluated in our previous paper. This system of equations allows a solution to the eigenvalue problem with homogeneous three-quark potentials, the class of which includes a number of standard Ansätze for the confining potentials, such as the Y- and Δ -string ones. We present analytic formulas for the K =2 , 3, 4, 5 shell states' eigenenergies in homogeneous three-body potentials, which we then apply to the Y and Δ strings as well as the logarithmic confining potentials. We also present numerical results for power-law pairwise potentials with the exponent ranging between -1 and +2 . In the process, we resolve the 25-year-old Taxil and Richard vs Bowler et al. controversy regarding the ordering of states in the K =3 shell, in favor of the former. Finally, we show the first clear difference between the spectra of Δ - and Y-string potentials, which appears in K ≥3 shells. Our results are generally valid, not just for confining potentials but also for many momentum-independent permutation-symmetric homogenous potentials that need not be pairwise sums of two-body terms. The potentials that can be treated in this way must be square integrable under the O (6 ) hyperangular integral, the class of which, however, does not include the Dirac δ function.

CUFID-query: accurate network querying through random walk based network flow estimation.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive performance evaluation based on biological networks with known functional modules, we show that CUFID-query outperforms the existing state-of-the-art algorithms in terms of prediction accuracy and biological significance of the predictions.

Probabilistic Cloning of Three Real States with Optimal Success Probabilities

NASA Astrophysics Data System (ADS)

Rui, Pin-shu

2017-06-01

We investigate the probabilistic quantum cloning (PQC) of three real states with average probability distribution. To get the analytic forms of the optimal success probabilities we assume that the three states have only two pairwise inner products. Based on the optimal success probabilities, we derive the explicit form of 1 →2 PQC for cloning three real states. The unitary operation needed in the PQC process is worked out too. The optimal success probabilities are also generalized to the M→ N PQC case.

Distribution of geometric quantum discord in photon-added coherent states

NASA Astrophysics Data System (ADS)

Daoud, M.; Kaydi, W.; El Hadfi, H.

2015-12-01

In this paper, we examine the influence of photon excitation on the monogamy property of quantum discord in tripartite coherent states of Greenberger-Horne-Zeilinger (GHZ) type. The Hilbert-Schmidt norm is used as quantifier of pairwise quantum correlations. The geometric quantum discord in all bipartite subsystems are explicitly given. We show that the geometric discord is monogamous for any photon excitation order.

Collective translational and rotational Monte Carlo cluster move for general pairwise interaction

NASA Astrophysics Data System (ADS)

Růžička, Štěpán; Allen, Michael P.

2014-09-01

Virtual move Monte Carlo is a cluster algorithm which was originally developed for strongly attractive colloidal, molecular, or atomistic systems in order to both approximate the collective dynamics and avoid sampling of unphysical kinetic traps. In this paper, we present the algorithm in the form, which selects the moving cluster through a wider class of virtual states and which is applicable to general pairwise interactions, including hard-core repulsion. The newly proposed way of selecting the cluster increases the acceptance probability by up to several orders of magnitude, especially for rotational moves. The results have their applications in simulations of systems interacting via anisotropic potentials both to enhance the sampling of the phase space and to approximate the dynamics.

Statistical Mechanics of the US Supreme Court

NASA Astrophysics Data System (ADS)

Lee, Edward D.; Broedersz, Chase P.; Bialek, William

2015-07-01

We build simple models for the distribution of voting patterns in a group, using the Supreme Court of the United States as an example. The maximum entropy model consistent with the observed pairwise correlations among justices' votes, an Ising spin glass, agrees quantitatively with the data. While all correlations (perhaps surprisingly) are positive, the effective pairwise interactions in the spin glass model have both signs, recovering the intuition that ideologically opposite justices negatively influence each another. Despite the competing interactions, a strong tendency toward unanimity emerges from the model, organizing the voting patterns in a relatively simple "energy landscape." Besides unanimity, other energy minima in this landscape, or maxima in probability, correspond to prototypical voting states, such as the ideological split or a tightly correlated, conservative core. The model correctly predicts the correlation of justices with the majority and gives us a measure of their influence on the majority decision. These results suggest that simple models, grounded in statistical physics, can capture essential features of collective decision making quantitatively, even in a complex political context.

Statistical mechanics of letters in words

PubMed Central

Stephens, Greg J.; Bialek, William

2013-01-01

We consider words as a network of interacting letters, and approximate the probability distribution of states taken on by this network. Despite the intuition that the rules of English spelling are highly combinatorial and arbitrary, we find that maximum entropy models consistent with pairwise correlations among letters provide a surprisingly good approximation to the full statistics of words, capturing ~92% of the multi-information in four-letter words and even “discovering” words that were not represented in the data. These maximum entropy models incorporate letter interactions through a set of pairwise potentials and thus define an energy landscape on the space of possible words. Guided by the large letter redundancy we seek a lower-dimensional encoding of the letter distribution and show that distinctions between local minima in the landscape account for ~68% of the four-letter entropy. We suggest that these states provide an effective vocabulary which is matched to the frequency of word use and much smaller than the full lexicon. PMID:20866490

Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

PubMed

She, Qingshan; Ma, Yuliang; Meng, Ming; Luo, Zhizeng

2015-01-01

Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve this problem, a multiclass posterior probability solution for twin SVM is proposed by the ranking continuous output and pairwise coupling in this paper. First, two-class posterior probability model is constructed to approximate the posterior probability by the ranking continuous output techniques and Platt's estimating method. Secondly, a solution of multiclass probabilistic outputs for twin SVM is provided by combining every pair of class probabilities according to the method of pairwise coupling. Finally, the proposed method is compared with multiclass SVM and twin SVM via voting, and multiclass posterior probability SVM using different coupling approaches. The efficacy on the classification accuracy and time complexity of the proposed method has been demonstrated by both the UCI benchmark datasets and real world EEG data from BCI Competition IV Dataset 2a, respectively.

Searching for collective behavior in a large network of sensory neurons.

PubMed

Tkačik, Gašper; Marre, Olivier; Amodei, Dario; Schneidman, Elad; Bialek, William; Berry, Michael J

2014-01-01

Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system; for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such "K-pairwise" models--being systematic extensions of the previously used pairwise Ising models--provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1) estimating its entropy, which constrains the population's capacity to represent visual information; 2) classifying activity patterns into a small set of metastable collective modes; 3) showing that the neural codeword ensembles are extremely inhomogenous; 4) demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction.

Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game

NASA Astrophysics Data System (ADS)

Zai, Dawei; Li, Jonathan; Guo, Yulan; Cheng, Ming; Huang, Pengdi; Cao, Xiaofei; Wang, Cheng

2017-12-01

It is challenging to automatically register TLS point clouds with noise, outliers and varying overlap. In this paper, we propose a new method for pairwise registration of TLS point clouds. We first generate covariance matrix descriptors with an adaptive neighborhood size from point clouds to find candidate correspondences, we then construct a non-cooperative game to isolate mutual compatible correspondences, which are considered as true positives. The method was tested on three models acquired by two different TLS systems. Experimental results demonstrate that our proposed adaptive covariance (ACOV) descriptor is invariant to rigid transformation and robust to noise and varying resolutions. The average registration errors achieved on three models are 0.46 cm, 0.32 cm and 1.73 cm, respectively. The computational times cost on these models are about 288 s, 184 s and 903 s, respectively. Besides, our registration framework using ACOV descriptors and a game theoretic method is superior to the state-of-the-art methods in terms of both registration error and computational time. The experiment on a large outdoor scene further demonstrates the feasibility and effectiveness of our proposed pairwise registration framework.

Con-Text: Text Detection for Fine-grained Object Classification.

PubMed

Karaoglu, Sezer; Tao, Ran; van Gemert, Jan C; Gevers, Theo

2017-05-24

This work focuses on fine-grained object classification using recognized scene text in natural images. While the state-of-the-art relies on visual cues only, this paper is the first work which proposes to combine textual and visual cues. Another novelty is the textual cue extraction. Unlike the state-of-the-art text detection methods, we focus more on the background instead of text regions. Once text regions are detected, they are further processed by two methods to perform text recognition i.e. ABBYY commercial OCR engine and a state-of-the-art character recognition algorithm. Then, to perform textual cue encoding, bi- and trigrams are formed between the recognized characters by considering the proposed spatial pairwise constraints. Finally, extracted visual and textual cues are combined for fine-grained classification. The proposed method is validated on four publicly available datasets: ICDAR03, ICDAR13, Con-Text and Flickr-logo. We improve the state-of-the-art end-to-end character recognition by a large margin of 15% on ICDAR03. We show that textual cues are useful in addition to visual cues for fine-grained classification. We show that textual cues are also useful for logo retrieval. Adding textual cues outperforms visual- and textual-only in fine-grained classification (70.7% to 60.3%) and logo retrieval (57.4% to 54.8%).

Extrinsic Calibration of Camera Networks Based on Pedestrians

PubMed Central

Guan, Junzhi; Deboeverie, Francis; Slembrouck, Maarten; Van Haerenborgh, Dirk; Van Cauwelaert, Dimitri; Veelaert, Peter; Philips, Wilfried

2016-01-01

In this paper, we propose a novel extrinsic calibration method for camera networks by analyzing tracks of pedestrians. First of all, we extract the center lines of walking persons by detecting their heads and feet in the camera images. We propose an easy and accurate method to estimate the 3D positions of the head and feet w.r.t. a local camera coordinate system from these center lines. We also propose a RANSAC-based orthogonal Procrustes approach to compute relative extrinsic parameters connecting the coordinate systems of cameras in a pairwise fashion. Finally, we refine the extrinsic calibration matrices using a method that minimizes the reprojection error. While existing state-of-the-art calibration methods explore epipolar geometry and use image positions directly, the proposed method first computes 3D positions per camera and then fuses the data. This results in simpler computations and a more flexible and accurate calibration method. Another advantage of our method is that it can also handle the case of persons walking along straight lines, which cannot be handled by most of the existing state-of-the-art calibration methods since all head and feet positions are co-planar. This situation often happens in real life. PMID:27171080

On the sufficiency of pairwise interactions in maximum entropy models of networks

NASA Astrophysics Data System (ADS)

Nemenman, Ilya; Merchan, Lina

Biological information processing networks consist of many components, which are coupled by an even larger number of complex multivariate interactions. However, analyses of data sets from fields as diverse as neuroscience, molecular biology, and behavior have reported that observed statistics of states of some biological networks can be approximated well by maximum entropy models with only pairwise interactions among the components. Based on simulations of random Ising spin networks with p-spin (p > 2) interactions, here we argue that this reduction in complexity can be thought of as a natural property of some densely interacting networks in certain regimes, and not necessarily as a special property of living systems. This work was supported in part by James S. McDonnell Foundation Grant No. 220020321.

Joint annotation of chromatin state and chromatin conformation reveals relationships among domain types and identifies domains of cell-type-specific expression

PubMed Central

Libbrecht, Maxwell W.; Ay, Ferhat; Hoffman, Michael M.; Gilbert, David M.; Bilmes, Jeffrey A.; Noble, William Stafford

2015-01-01

The genomic neighborhood of a gene influences its activity, a behavior that is attributable in part to domain-scale regulation. Previous genomic studies have identified many types of regulatory domains. However, due to the difficulty of integrating genomics data sets, the relationships among these domain types are poorly understood. Semi-automated genome annotation (SAGA) algorithms facilitate human interpretation of heterogeneous collections of genomics data by simultaneously partitioning the human genome and assigning labels to the resulting genomic segments. However, existing SAGA methods cannot integrate inherently pairwise chromatin conformation data. We developed a new computational method, called graph-based regularization (GBR), for expressing a pairwise prior that encourages certain pairs of genomic loci to receive the same label in a genome annotation. We used GBR to exploit chromatin conformation information during genome annotation by encouraging positions that are close in 3D to occupy the same type of domain. Using this approach, we produced a model of chromatin domains in eight human cell types, thereby revealing the relationships among known domain types. Through this model, we identified clusters of tightly regulated genes expressed in only a small number of cell types, which we term “specific expression domains.” We found that domain boundaries marked by promoters and CTCF motifs are consistent between cell types even when domain activity changes. Finally, we showed that GBR can be used to transfer information from well-studied cell types to less well-characterized cell types during genome annotation, making it possible to produce high-quality annotations of the hundreds of cell types with limited available data. PMID:25677182

Joint annotation of chromatin state and chromatin conformation reveals relationships among domain types and identifies domains of cell-type-specific expression.

PubMed

Libbrecht, Maxwell W; Ay, Ferhat; Hoffman, Michael M; Gilbert, David M; Bilmes, Jeffrey A; Noble, William Stafford

2015-04-01

The genomic neighborhood of a gene influences its activity, a behavior that is attributable in part to domain-scale regulation. Previous genomic studies have identified many types of regulatory domains. However, due to the difficulty of integrating genomics data sets, the relationships among these domain types are poorly understood. Semi-automated genome annotation (SAGA) algorithms facilitate human interpretation of heterogeneous collections of genomics data by simultaneously partitioning the human genome and assigning labels to the resulting genomic segments. However, existing SAGA methods cannot integrate inherently pairwise chromatin conformation data. We developed a new computational method, called graph-based regularization (GBR), for expressing a pairwise prior that encourages certain pairs of genomic loci to receive the same label in a genome annotation. We used GBR to exploit chromatin conformation information during genome annotation by encouraging positions that are close in 3D to occupy the same type of domain. Using this approach, we produced a model of chromatin domains in eight human cell types, thereby revealing the relationships among known domain types. Through this model, we identified clusters of tightly regulated genes expressed in only a small number of cell types, which we term "specific expression domains." We found that domain boundaries marked by promoters and CTCF motifs are consistent between cell types even when domain activity changes. Finally, we showed that GBR can be used to transfer information from well-studied cell types to less well-characterized cell types during genome annotation, making it possible to produce high-quality annotations of the hundreds of cell types with limited available data. © 2015 Libbrecht et al.; Published by Cold Spring Harbor Laboratory Press.

Unexpected Relationships and Inbreeding in HapMap Phase III Populations

PubMed Central

Stevens, Eric L.; Baugher, Joseph D.; Shirley, Matthew D.; Frelin, Laurence P.; Pevsner, Jonathan

2012-01-01

Correct annotation of the genetic relationships between samples is essential for population genomic studies, which could be biased by errors or omissions. To this end, we used identity-by-state (IBS) and identity-by-descent (IBD) methods to assess genetic relatedness of individuals within HapMap phase III data. We analyzed data from 1,397 individuals across 11 ethnic populations. Our results support previous studies (Pemberton et al., 2010; Kyriazopoulou-Panagiotopoulou et al., 2011) assessing unknown relatedness present within this population. Additionally, we present evidence for 1,657 novel pairwise relationships across 9 populations. Surprisingly, significant Cotterman's coefficients of relatedness K1 (IBD1) values were detected between pairs of known parents. Furthermore, significant K2 (IBD2) values were detected in 32 previously annotated parent-child relationships. Consistent with a hypothesis of inbreeding, regions of homozygosity (ROH) were identified in the offspring of related parents, of which a subset overlapped those reported in previous studies (Gibson et al. 2010; Johnson et al. 2011). In total, we inferred 28 inbred individuals with ROH that overlapped areas of relatedness between the parents and/or IBD2 sharing at a different genomic locus between a child and a parent. Finally, 8 previously annotated parent-child relationships had unexpected K0 (IBD0) values (resulting from a chromosomal abnormality or genotype error), and 10 previously annotated second-degree relationships along with 38 other novel pairwise relationships had unexpected IBD2 (indicating two separate paths of recent ancestry). These newly described types of relatedness may impact the outcome of previous studies and should inform the design of future studies relying on the HapMap Phase III resource. PMID:23185369

Dependence of Halo Bias and Kinematics on Assembly Variables

NASA Astrophysics Data System (ADS)

Xu, Xiaoju; Zheng, Zheng

2018-06-01

Using dark matter haloes identified in a large N-body simulation, we study halo assembly bias, with halo formation time, peak maximum circular velocity, concentration, and spin as the assembly variables. Instead of grouping haloes at fixed mass into different percentiles of each assembly variable, we present the joint dependence of halo bias on the values of halo mass and each assembly variable. In the plane of halo mass and one assembly variable, the joint dependence can be largely described as halo bias increasing outward from a global minimum. We find it unlikely to have a combination of halo variables to absorb all assembly bias effects. We then present the joint dependence of halo bias on two assembly variables at fixed halo mass. The gradient of halo bias does not necessarily follow the correlation direction of the two assembly variables and it varies with halo mass. Therefore in general for two correlated assembly variables one cannot be used as a proxy for the other in predicting halo assembly bias trend. Finally, halo assembly is found to affect the kinematics of haloes. Low-mass haloes formed earlier can have much higher pairwise velocity dispersion than those of massive haloes. In general, halo assembly leads to a correlation between halo bias and halo pairwise velocity distribution, with more strongly clustered haloes having higher pairwise velocity and velocity dispersion. However, the correlation is not tight, and the kinematics of haloes at fixed halo bias still depends on halo mass and assembly variables.

DockTrina: docking triangular protein trimers.

PubMed

Popov, Petr; Ritchie, David W; Grudinin, Sergei

2014-01-01

In spite of the abundance of oligomeric proteins within a cell, the structural characterization of protein-protein interactions is still a challenging task. In particular, many of these interactions involve heteromeric complexes, which are relatively difficult to determine experimentally. Hence there is growing interest in using computational techniques to model such complexes. However, assembling large heteromeric complexes computationally is a highly combinatorial problem. Nonetheless the problem can be simplified greatly by considering interactions between protein trimers. After dimers and monomers, triangular trimers (i.e. trimers with pair-wise contacts between all three pairs of proteins) are the most frequently observed quaternary structural motifs according to the three-dimensional (3D) complex database. This article presents DockTrina, a novel protein docking method for modeling the 3D structures of nonsymmetrical triangular trimers. The method takes as input pair-wise contact predictions from a rigid body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation test. Finally, it ranks the predictions using a scoring function which combines triples of pair-wise contact terms and a geometric clash penalty term. The overall approach takes less than 2 min per complex on a modern desktop computer. The method is tested and validated using a benchmark set of 220 bound and seven unbound protein trimer structures. DockTrina will be made available at http://nano-d.inrialpes.fr/software/docktrina. Copyright © 2013 Wiley Periodicals, Inc.

Analysis of Geographic and Pairwise Distances among Chinese Cashmere Goat Populations

PubMed Central

Liu, Jian-Bin; Wang, Fan; Lang, Xia; Zha, Xi; Sun, Xiao-Ping; Yue, Yao-Jing; Feng, Rui-Lin; Yang, Bo-Hui; Guo, Jian

2013-01-01

This study investigated the geographic and pairwise distances of nine Chinese local Cashmere goat populations through the analysis of 20 microsatellite DNA markers. Fluorescence PCR was used to identify the markers, which were selected based on their significance as identified by the Food and Agriculture Organization of the United Nations (FAO) and the International Society for Animal Genetics (ISAG). In total, 206 alleles were detected; the average allele number was 10.30; the polymorphism information content of loci ranged from 0.5213 to 0.7582; the number of effective alleles ranged from 4.0484 to 4.6178; the observed heterozygosity was from 0.5023 to 0.5602 for the practical sample; the expected heterozygosity ranged from 0.5783 to 0.6464; and Allelic richness ranged from 4.7551 to 8.0693. These results indicated that Chinese Cashmere goat populations exhibited rich genetic diversity. Further, the Wright’s F-statistics of subpopulation within total (FST) was 0.1184; the genetic differentiation coefficient (GST) was 0.0940; and the average gene flow (Nm) was 2.0415. All pairwise FST values among the populations were highly significant (p<0.01 or p<0.001), suggesting that the populations studied should all be considered to be separate breeds. Finally, the clustering analysis divided the Chinese Cashmere goat populations into at least four clusters, with the Hexi and Yashan goat populations alone in one cluster. These results have provided useful, practical, and important information for the future of Chinese Cashmere goat breeding. PMID:25049794

Manipulation of Karyotype in Caenorhabditis elegans Reveals Multiple Inputs Driving Pairwise Chromosome Synapsis During Meiosis

PubMed Central

Roelens, Baptiste; Schvarzstein, Mara; Villeneuve, Anne M.

2015-01-01

Meiotic chromosome segregation requires pairwise association between homologs, stabilized by the synaptonemal complex (SC). Here, we investigate factors contributing to pairwise synapsis by investigating meiosis in polyploid worms. We devised a strategy, based on transient inhibition of cohesin function, to generate polyploid derivatives of virtually any Caenorhabditis elegans strain. We exploited this strategy to investigate the contribution of recombination to pairwise synapsis in tetraploid and triploid worms. In otherwise wild-type polyploids, chromosomes first sort into homolog groups, then multipartner interactions mature into exclusive pairwise associations. Pairwise synapsis associations still form in recombination-deficient tetraploids, confirming a propensity for synapsis to occur in a strictly pairwise manner. However, the transition from multipartner to pairwise association was perturbed in recombination-deficient triploids, implying a role for recombination in promoting this transition when three partners compete for synapsis. To evaluate the basis of synapsis partner preference, we generated polyploid worms heterozygous for normal sequence and rearranged chromosomes sharing the same pairing center (PC). Tetraploid worms had no detectable preference for identical partners, indicating that PC-adjacent homology drives partner choice in this context. In contrast, triploid worms exhibited a clear preference for identical partners, indicating that homology outside the PC region can influence partner choice. Together, our findings, suggest a two-phase model for C. elegans synapsis: an early phase, in which initial synapsis interactions are driven primarily by recombination-independent assessment of homology near PCs and by a propensity for pairwise SC assembly, and a later phase in which mature synaptic interactions are promoted by recombination. PMID:26500263

Methods of amorphization and investigation of the amorphous state.

PubMed

Einfal, Tomaž; Planinšek, Odon; Hrovat, Klemen

2013-09-01

The amorphous form of pharmaceutical materials represents the most energetic solid state of a material. It provides advantages in terms of dissolution rate and bioavailability. This review presents the methods of solid- -state amorphization described in literature (supercooling of liquids, milling, lyophilization, spray drying, dehydration of crystalline hydrates), with the emphasis on milling. Furthermore, we describe how amorphous state of pharmaceuticals differ depending on the method of preparation and how these differences can be screened by a variety of spectroscopic (X-ray powder diffraction, solid state nuclear magnetic resonance, atomic pairwise distribution, infrared spectroscopy, terahertz spectroscopy) and calorimetry methods.

Structure based alignment and clustering of proteins (STRALCP)

DOEpatents

Zemla, Adam T.; Zhou, Carol E.; Smith, Jason R.; Lam, Marisa W.

2013-06-18

Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.

A descriptive model of resting-state networks using Markov chains.

PubMed

Xie, H; Pal, R; Mitra, S

2016-08-01

Resting-state functional connectivity (RSFC) studies considering pairwise linear correlations have attracted great interests while the underlying functional network structure still remains poorly understood. To further our understanding of RSFC, this paper presents an analysis of the resting-state networks (RSNs) based on the steady-state distributions and provides a novel angle to investigate the RSFC of multiple functional nodes. This paper evaluates the consistency of two networks based on the Hellinger distance between the steady-state distributions of the inferred Markov chain models. The results show that generated steady-state distributions of default mode network have higher consistency across subjects than random nodes from various RSNs.

Nonclassical features of trimodal excited coherent Greenberger - Horne - Zeilinger(GHZ) - type state

NASA Astrophysics Data System (ADS)

Merlin, J.; Ahmed, A. B. M.; Mohammed, S. Naina

2017-06-01

We examine the influence of photon excitation on each mode of the Glauber coherent GHZ type tripartite state. Concurrence is adopted as entanglement measure between bipartite entangled state. The pairwise concurrence is calculated and used as a quantifier of intermodal entanglement. The entanglement distribution among three modes is investigated using tangle as a measure and the residual entanglement is also calculated. The effect of the photon addition process on the quadrature squeezing is investigated. The higher order squeezing capacity of the photon addition process is also shown.

Synergetic and Redundant Information Flow Detected by Unnormalized Granger Causality: Application to Resting State fMRI.

PubMed

Stramaglia, Sebastiano; Angelini, Leonardo; Wu, Guorong; Cortes, Jesus M; Faes, Luca; Marinazzo, Daniele

2016-12-01

We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. The presence of redundancy and/or synergy in multivariate time series data renders difficulty to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality, one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently, we introduce a pairwise index of synergy which is zero when two independent sources additively influence the future state of the system, differently from previous definitions of synergy. We report the application of the proposed approach to resting state functional magnetic resonance imaging data from the Human Connectome Project showing that redundant pairs of regions arise mainly due to space contiguity and interhemispheric symmetry, while synergy occurs mainly between nonhomologous pairs of regions in opposite hemispheres. Redundancy and synergy, in healthy resting brains, display characteristic patterns, revealed by the proposed approach. The pairwise synergy index, here introduced, maps the informational character of the system at hand into a weighted complex network: the same approach can be applied to other complex systems whose normal state corresponds to a balance between redundant and synergetic circuits.

Building dynamic population graph for accurate correspondence detection.

PubMed

Du, Shaoyi; Guo, Yanrong; Sanroma, Gerard; Ni, Dong; Wu, Guorong; Shen, Dinggang

2015-12-01

In medical imaging studies, there is an increasing trend for discovering the intrinsic anatomical difference across individual subjects in a dataset, such as hand images for skeletal bone age estimation. Pair-wise matching is often used to detect correspondences between each individual subject and a pre-selected model image with manually-placed landmarks. However, the large anatomical variability across individual subjects can easily compromise such pair-wise matching step. In this paper, we present a new framework to simultaneously detect correspondences among a population of individual subjects, by propagating all manually-placed landmarks from a small set of model images through a dynamically constructed image graph. Specifically, we first establish graph links between models and individual subjects according to pair-wise shape similarity (called as forward step). Next, we detect correspondences for the individual subjects with direct links to any of model images, which is achieved by a new multi-model correspondence detection approach based on our recently-published sparse point matching method. To correct those inaccurate correspondences, we further apply an error detection mechanism to automatically detect wrong correspondences and then update the image graph accordingly (called as backward step). After that, all subject images with detected correspondences are included into the set of model images, and the above two steps of graph expansion and error correction are repeated until accurate correspondences for all subject images are established. Evaluations on real hand X-ray images demonstrate that our proposed method using a dynamic graph construction approach can achieve much higher accuracy and robustness, when compared with the state-of-the-art pair-wise correspondence detection methods as well as a similar method but using static population graph. Copyright © 2015 Elsevier B.V. All rights reserved.

Breaking the computational barriers of pairwise genome comparison.

PubMed

Torreno, Oscar; Trelles, Oswaldo

2015-08-11

Conventional pairwise sequence comparison software algorithms are being used to process much larger datasets than they were originally designed for. This can result in processing bottlenecks that limit software capabilities or prevent full use of the available hardware resources. Overcoming the barriers that limit the efficient computational analysis of large biological sequence datasets by retrofitting existing algorithms or by creating new applications represents a major challenge for the bioinformatics community. We have developed C libraries for pairwise sequence comparison within diverse architectures, ranging from commodity systems to high performance and cloud computing environments. Exhaustive tests were performed using different datasets of closely- and distantly-related sequences that span from small viral genomes to large mammalian chromosomes. The tests demonstrated that our solution is capable of generating high quality results with a linear-time response and controlled memory consumption, being comparable or faster than the current state-of-the-art methods. We have addressed the problem of pairwise and all-versus-all comparison of large sequences in general, greatly increasing the limits on input data size. The approach described here is based on a modular out-of-core strategy that uses secondary storage to avoid reaching memory limits during the identification of High-scoring Segment Pairs (HSPs) between the sequences under comparison. Software engineering concepts were applied to avoid intermediate result re-calculation, to minimise the performance impact of input/output (I/O) operations and to modularise the process, thus enhancing application flexibility and extendibility. Our computationally-efficient approach allows tasks such as the massive comparison of complete genomes, evolutionary event detection, the identification of conserved synteny blocks and inter-genome distance calculations to be performed more effectively.

Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons

PubMed Central

Setareh, Hesam; Deger, Moritz; Petersen, Carl C. H.; Gerstner, Wulfram

2017-01-01

Experimental measurements of pairwise connection probability of pyramidal neurons together with the distribution of synaptic weights have been used to construct randomly connected model networks. However, several experimental studies suggest that both wiring and synaptic weight structure between neurons show statistics that differ from random networks. Here we study a network containing a subset of neurons which we call weight-hub neurons, that are characterized by strong inward synapses. We propose a connectivity structure for excitatory neurons that contain assemblies of densely connected weight-hub neurons, while the pairwise connection probability and synaptic weight distribution remain consistent with experimental data. Simulations of such a network with generalized integrate-and-fire neurons display regular and irregular slow oscillations akin to experimentally observed up/down state transitions in the activity of cortical neurons with a broad distribution of pairwise spike correlations. Moreover, stimulation of a model network in the presence or absence of assembly structure exhibits responses similar to light-evoked responses of cortical layers in optogenetically modified animals. We conclude that a high connection probability into and within assemblies of excitatory weight-hub neurons, as it likely is present in some but not all cortical layers, changes the dynamics of a layer of cortical microcircuitry significantly. PMID:28690508

A tensorial approach to access cognitive workload related to mental arithmetic from EEG functional connectivity estimates.

PubMed

Dimitriadis, S I; Sun, Yu; Kwok, K; Laskaris, N A; Bezerianos, A

2013-01-01

The association of functional connectivity patterns with particular cognitive tasks has long been a topic of interest in neuroscience, e.g., studies of functional connectivity have demonstrated its potential use for decoding various brain states. However, the high-dimensionality of the pairwise functional connectivity limits its usefulness in some real-time applications. In the present study, the methodology of tensor subspace analysis (TSA) is used to reduce the initial high-dimensionality of the pairwise coupling in the original functional connectivity network to a space of condensed descriptive power, which would significantly decrease the computational cost and facilitate the differentiation of brain states. We assess the feasibility of the proposed method on EEG recordings when the subject was performing mental arithmetic task which differ only in the difficulty level (easy: 1-digit addition v.s. 3-digit additions). Two different cortical connective networks were detected, and by comparing the functional connectivity networks in different work states, it was found that the task-difficulty is best reflected in the connectivity structure of sub-graphs extending over parietooccipital sites. Incorporating this data-driven information within original TSA methodology, we succeeded in predicting the difficulty level from connectivity patterns in an efficient way that can be implemented so as to work in real-time.

Functional connectivity in resting state as a phonemic fluency ability measure.

PubMed

Miró-Padilla, Anna; Bueichekú, Elisenda; Ventura-Campos, Noelia; Palomar-García, María-Ángeles; Ávila, César

2017-03-01

There is some evidence that functional connectivity (FC) measures obtained at rest may reflect individual differences in cognitive capabilities. We tested this possibility by using the FAS test as a measure of phonemic fluency. Seed regions of the main brain areas involved in this task were extracted from meta-analysis results (Wagner et al., 2014) and used for pairwise resting-state FC analysis. Ninety-three undergraduates completed the FAS test outside the scanner. A correlation analysis was conducted between the F-A-S scores (behavioral testing) and the pairwise FC pattern of verbal fluency regions of interest. Results showed that the higher FC between the thalamus and the cerebellum, and the lower FCs between the left inferior frontal gyrus and the right insula and between the supplementary motor area and the right insula were associated with better performance on the FAS test. Regression analyses revealed that the first two FCs contributed independently to this better phonemic fluency, reflecting a more general attentional factor (FC between thalamus and cerebellum) and a more specific fluency factor (FC between the left inferior frontal gyrus and the right insula). The results support the Spontaneous Trait Reactivation hypothesis, which explains how resting-state derived measures may reflect individual differences in cognitive abilities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Information processing in micro and meso-scale neural circuits during normal and disease states

NASA Astrophysics Data System (ADS)

Luongo, Francisco

Neural computation can occur at multiple spatial and temporal timescales. The sum total of all of these processes is to guide optimal behaviors within the context of the constraints imposed by the physical world. How the circuits of the brain achieves this goal represents a central question in systems neuroscience. Here I explore the many ways in which the circuits of the brain can process information at both the micro and meso scale. Understanding the way information is represented and processed in the brain could shed light on the neuropathology underlying complex neuropsychiatric diseases such as autism and schizophrenia. Chapter 2 establishes an experimental paradigm for assaying patterns of microcircuit activity and examines the role of dopaminergic modulation on prefrontal microcircuits. We find that dopamine type 2 (D2) receptor activation results in an increase in spontaneous activity while dopamine type 1 (D1) activation does not. Chapter 3 of this dissertation presents a study that illustrates how cholingergic activation normally produces what has been suggested as a neural substrate of attention; pairwise decorrelation in microcircuit activity. This study also shows that in two etiologicall distinct mouse models of autism, FMR1 knockout mice and Valproic Acid exposed mice, this ability to decorrelate in the presence of cholinergic activation is lost. This represents a putative microcircuit level biomarker of autism. Chapter 4 examines the structure/function relationship within the prefrontal microcircuit. Spontaneous activity in prefrontal microcircuits is shown to be organized according to a small world architecture. Interestingly, this architecture is important for one concrete function of neuronal microcircuits; the ability to produce temporally stereotyped patterns of activation. In the final chapter, we identify subnetworks in chronic intracranial electrocorticographic (ECoG) recordings using pairwise electrode coherence and dimensionality reduction techniques. We show that we can further reduce the dimensionality of these networks by identifying 'key-interactions' that are informative of the overall subnetwork state at any given point in time. This study highlights that redundancy in ECoG data can be exploited to identify low-dimensional representation of brain-wide subnetworks. Taken together, these studies represent the development of multiple technological and analytical techniques aimed at understanding how information is processed and modulated at emergent circuit and network levels as well as understanding their dysfunction in a neuropsychiatric disease state.

Correlations and Werner states in finite spin linear arrays

NASA Astrophysics Data System (ADS)

Wells, P. R.; Chaves, C. M.; d'Albuquerque e Castro, J.; Koiller, Belita

2013-10-01

Pairwise quantum correlations in the ground state of an N-spins antiferromagnetic Heisenberg chain are investigated. By varying the exchange coupling between two neighboring sites, it is possible to reversibly drive spins from entangled to disentangled states. For even N, the two-spin density matrix is written in the form of a Werner state, allowing identification of its single parameter with the usual spin-spin correlation function. The N = 4 chain is identified as a promising system for practical demonstrations of non-classical correlations and the realization of Werner states in familiar condensed matter systems. Fabrication and measurement ingredients are within current capabilities.

GDSCalc: A Web-Based Application for Evaluating Discrete Graph Dynamical Systems

PubMed Central

Elmeligy Abdelhamid, Sherif H.; Kuhlman, Chris J.; Marathe, Madhav V.; Mortveit, Henning S.; Ravi, S. S.

2015-01-01

Discrete dynamical systems are used to model various realistic systems in network science, from social unrest in human populations to regulation in biological networks. A common approach is to model the agents of a system as vertices of a graph, and the pairwise interactions between agents as edges. Agents are in one of a finite set of states at each discrete time step and are assigned functions that describe how their states change based on neighborhood relations. Full characterization of state transitions of one system can give insights into fundamental behaviors of other dynamical systems. In this paper, we describe a discrete graph dynamical systems (GDSs) application called GDSCalc for computing and characterizing system dynamics. It is an open access system that is used through a web interface. We provide an overview of GDS theory. This theory is the basis of the web application; i.e., an understanding of GDS provides an understanding of the software features, while abstracting away implementation details. We present a set of illustrative examples to demonstrate its use in education and research. Finally, we compare GDSCalc with other discrete dynamical system software tools. Our perspective is that no single software tool will perform all computations that may be required by all users; tools typically have particular features that are more suitable for some tasks. We situate GDSCalc within this space of software tools. PMID:26263006

GDSCalc: A Web-Based Application for Evaluating Discrete Graph Dynamical Systems.

PubMed

Elmeligy Abdelhamid, Sherif H; Kuhlman, Chris J; Marathe, Madhav V; Mortveit, Henning S; Ravi, S S

2015-01-01

Discrete dynamical systems are used to model various realistic systems in network science, from social unrest in human populations to regulation in biological networks. A common approach is to model the agents of a system as vertices of a graph, and the pairwise interactions between agents as edges. Agents are in one of a finite set of states at each discrete time step and are assigned functions that describe how their states change based on neighborhood relations. Full characterization of state transitions of one system can give insights into fundamental behaviors of other dynamical systems. In this paper, we describe a discrete graph dynamical systems (GDSs) application called GDSCalc for computing and characterizing system dynamics. It is an open access system that is used through a web interface. We provide an overview of GDS theory. This theory is the basis of the web application; i.e., an understanding of GDS provides an understanding of the software features, while abstracting away implementation details. We present a set of illustrative examples to demonstrate its use in education and research. Finally, we compare GDSCalc with other discrete dynamical system software tools. Our perspective is that no single software tool will perform all computations that may be required by all users; tools typically have particular features that are more suitable for some tasks. We situate GDSCalc within this space of software tools.

ParallABEL: an R library for generalized parallelization of genome-wide association studies.

PubMed

Sangket, Unitsa; Mahasirimongkol, Surakameth; Chantratita, Wasun; Tandayya, Pichaya; Aulchenko, Yurii S

2010-04-29

Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL.

Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Time Series Data-fMRI Study.

PubMed

Eslami, Taban; Saeed, Fahad

2018-04-20

Functional magnetic resonance imaging (fMRI) is a non-invasive brain imaging technique, which has been regularly used for studying brain’s functional activities in the past few years. A very well-used measure for capturing functional associations in brain is Pearson’s correlation coefficient. Pearson’s correlation is widely used for constructing functional network and studying dynamic functional connectivity of the brain. These are useful measures for understanding the effects of brain disorders on connectivities among brain regions. The fMRI scanners produce huge number of voxels and using traditional central processing unit (CPU)-based techniques for computing pairwise correlations is very time consuming especially when large number of subjects are being studied. In this paper, we propose a graphics processing unit (GPU)-based algorithm called Fast-GPU-PCC for computing pairwise Pearson’s correlation coefficient. Based on the symmetric property of Pearson’s correlation, this approach returns N ( N − 1 ) / 2 correlation coefficients located at strictly upper triangle part of the correlation matrix. Storing correlations in a one-dimensional array with the order as proposed in this paper is useful for further usage. Our experiments on real and synthetic fMRI data for different number of voxels and varying length of time series show that the proposed approach outperformed state of the art GPU-based techniques as well as the sequential CPU-based versions. We show that Fast-GPU-PCC runs 62 times faster than CPU-based version and about 2 to 3 times faster than two other state of the art GPU-based methods.

Pairwise-Comparison Software

NASA Technical Reports Server (NTRS)

Ricks, Wendell R.

1995-01-01

Pairwise comparison (PWC) is computer program that collects data for psychometric scaling techniques now used in cognitive research. It applies technique of pairwise comparisons, which is one of many techniques commonly used to acquire the data necessary for analyses. PWC administers task, collects data from test subject, and formats data for analysis. Written in Turbo Pascal v6.0.

Comment II on ''Dense coding in entangled states''

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akhavan, O.; Institute for Studies in Theoretical Physics and Mathematics; Rezakhani, A. T.

2003-07-01

In a recent Brief Report, L. Lee, D. Ahn, and S. W. Hwang [Phys. Rev. A 66, 024304 (2002)] have claimed that using pairwise entangled qubits gives rise to an exponentially more efficient dense coding when two parties are involved than using maximally entangled qubits shared among N parties. Here we show that their claim is not true.

Inferring Weighted Directed Association Network from Multivariate Time Series with a Synthetic Method of Partial Symbolic Transfer Entropy Spectrum and Granger Causality

PubMed Central

Hu, Yanzhu; Ai, Xinbo

2016-01-01

Complex network methodology is very useful for complex system explorer. However, the relationships among variables in complex system are usually not clear. Therefore, inferring association networks among variables from their observed data has been a popular research topic. We propose a synthetic method, named small-shuffle partial symbolic transfer entropy spectrum (SSPSTES), for inferring association network from multivariate time series. The method synthesizes surrogate data, partial symbolic transfer entropy (PSTE) and Granger causality. A proper threshold selection is crucial for common correlation identification methods and it is not easy for users. The proposed method can not only identify the strong correlation without selecting a threshold but also has the ability of correlation quantification, direction identification and temporal relation identification. The method can be divided into three layers, i.e. data layer, model layer and network layer. In the model layer, the method identifies all the possible pair-wise correlation. In the network layer, we introduce a filter algorithm to remove the indirect weak correlation and retain strong correlation. Finally, we build a weighted adjacency matrix, the value of each entry representing the correlation level between pair-wise variables, and then get the weighted directed association network. Two numerical simulated data from linear system and nonlinear system are illustrated to show the steps and performance of the proposed approach. The ability of the proposed method is approved by an application finally. PMID:27832153

Chevron Behavior and Isostable Enthalpic Barriers in Protein Folding: Successes and Limitations of Simple Gō-like Modeling

PubMed Central

Kaya, Hüseyin; Liu, Zhirong; Chan, Hue Sun

2005-01-01

It has been demonstrated that a “near-Levinthal” cooperative mechanism, whereby the common Gō interaction scheme is augmented by an extra favorability for the native state as a whole, can lead to apparent two-state folding/unfolding kinetics over a broad range of native stabilities in lattice models of proteins. Here such a mechanism is shown to be generalizable to a simplified continuum (off-lattice) Langevin dynamics model with a Cα protein chain representation, with the resulting chevron plots exhibiting an extended quasilinear regime reminiscent of that of apparent two-state real proteins. Similarly high degrees of cooperativity are possible in Gō-like continuum models with rudimentary pairwise desolvation barriers as well. In these models, cooperativity increases with increasing desolvation barrier height, suggesting strongly that two-state-like folding/unfolding kinetics would be achievable when the pairwise desolvation barrier becomes sufficiently high. Besides cooperativity, another generic folding property of interest that has emerged from published experiments on several apparent two-state proteins is that their folding relaxation under constant native stability (isostability) conditions is essentially Arrhenius, entailing high intrinsic enthalpic folding barriers of ∼17–30 kcal/mol. Based on a new analysis of published data on barnase, here we propose that a similar property should also apply to a certain class of non-two-state proteins that fold with chevron rollovers. However, several continuum Gō-like constructs considered here fail to predict any significant intrinsic enthalpic folding barrier under isostability conditions; thus the physical origin of such barriers in real proteins remains to be elucidated. PMID:15863486

A general transformation to canonical form for potentials in pairwise interatomic interactions.

PubMed

Walton, Jay R; Rivera-Rivera, Luis A; Lucchese, Robert R; Bevan, John W

2015-06-14

A generalized formulation of explicit force-based transformations is introduced to investigate the concept of a canonical potential in both fundamental chemical and intermolecular bonding. Different classes of representative ground electronic state pairwise interatomic interactions are referenced to a chosen canonical potential illustrating application of such transformations. Specifically, accurately determined potentials of the diatomic molecules H2, H2(+), HF, LiH, argon dimer, and one-dimensional dissociative coordinates in Ar-HBr, OC-HF, and OC-Cl2 are investigated throughout their bound potentials. Advantages of the current formulation for accurately evaluating equilibrium dissociation energies and a fundamentally different unified perspective on nature of intermolecular interactions will be emphasized. In particular, this canonical approach has significance to previous assertions that there is no very fundamental distinction between van der Waals bonding and covalent bonding or for that matter hydrogen and halogen bonds.

Intrasubject multimodal groupwise registration with the conditional template entropy.

PubMed

Polfliet, Mathias; Klein, Stefan; Huizinga, Wyke; Paulides, Margarethus M; Niessen, Wiro J; Vandemeulebroucke, Jef

2018-05-01

Image registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting remains difficult, due to the lack of generally applicable similarity metrics. In this work, a novel similarity metric for such groupwise registration problems is proposed. The metric calculates the sum of the conditional entropy between each image in the group and a representative template image constructed iteratively using principal component analysis. The proposed metric is validated in extensive experiments on synthetic and intrasubject clinical image data. These experiments showed equivalent or improved registration accuracy compared to other state-of-the-art (dis)similarity metrics and improved transformation consistency compared to pairwise mutual information. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

General parity between trio and pairwise breeding of laboratory mice in static caging.

PubMed

Kedl, Ross M; Wysocki, Lawrence J; Janssen, William J; Born, Willi K; Rosenbaum, Matthew D; Granowski, Julia; Kench, Jennifer A; Fong, Derek L; Switzer, Lisa A; Cruse, Margaret; Huang, Hua; Jakubzick, Claudia V; Kosmider, Beata; Takeda, Katsuyuki; Stranova, Thomas J; Klumm, Randal C; Delgado, Christine; Tummala, Saigiridhar; De Langhe, Stijn; Cambier, John; Haskins, Katherine; Lenz, Laurel L; Curran-Everett, Douglas

2014-11-15

Changes made in the 8th edition of the Guide for the Care and Use of Laboratory Animals included new recommendations for the amount of space for breeding female mice. Adopting the new recommendations required, in essence, the elimination of trio breeding practices for all institutions. Both public opinion and published data did not readily support the new recommendations. In response, the National Jewish Health Institutional Animal Care and Use Committee established a program to directly compare the effects of breeding format on mouse pup survival and growth. Our study showed an overall parity between trio and pairwise breeding formats on the survival and growth of the litters, suggesting that the housing recommendations for breeding female mice as stated in the current Guide for the Care and Use of Laboratory Animals should be reconsidered. Copyright © 2014 by The American Association of Immunologists, Inc.

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

Photon-number correlation for quantum enhanced imaging and sensing

NASA Astrophysics Data System (ADS)

Meda, A.; Losero, E.; Samantaray, N.; Scafirimuto, F.; Pradyumna, S.; Avella, A.; Ruo-Berchera, I.; Genovese, M.

2017-09-01

In this review we present the potentialities and the achievements of the use of non-classical photon-number correlations in twin-beam states for many applications, ranging from imaging to metrology. Photon-number correlations in the quantum regime are easily produced and are rather robust against unavoidable experimental losses, and noise in some cases, if compared to the entanglement, where losing one photon can completely compromise the state and its exploitable advantages. Here, we will focus on quantum enhanced protocols in which only phase-insensitive intensity measurements (photon-number counting) are performed, which allow probing the transmission/absorption properties of a system, leading, for example, to innovative target detection schemes in a strong background. In this framework, one of the advantages is that the sources experimentally available emit a wide number of pair-wise correlated modes, which can be intercepted and exploited separately, for example by many pixels of a camera, providing a parallelism, essential in several applications, such as wide-field sub-shot-noise imaging and quantum enhanced ghost imaging. Finally, non-classical correlation enables new possibilities in quantum radiometry, e.g. the possibility of absolute calibration of a spatial resolving detector from the on-off single-photon regime to the linear regime in the same setup.

Differential Item Functioning Detection across Two Methods of Defining Group Comparisons: Pairwise and Composite Group Comparisons

ERIC Educational Resources Information Center

Sari, Halil Ibrahim; Huggins, Anne Corinne

2015-01-01

This study compares two methods of defining groups for the detection of differential item functioning (DIF): (a) pairwise comparisons and (b) composite group comparisons. We aim to emphasize and empirically support the notion that the choice of pairwise versus composite group definitions in DIF is a reflection of how one defines fairness in DIF…

Unbiased nonorthogonal bases for tomographic reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sainz, Isabel; Klimov, Andrei B.; Roa, Luis

2010-05-15

We have developed a general method for constructing a set of nonorthogonal bases with equal separations between all different basis states in prime dimensions. The results are that the corresponding biorthogonal counterparts are pairwise unbiased with the components of the original bases. Using these bases, we derive an explicit expression for the optimal tomography in nonorthogonal bases. A special two-dimensional case is analyzed separately.

A Computational Study of Rare Gas Clusters: Stepping Stones to the Solid State

ERIC Educational Resources Information Center

Glendening, Eric D.; Halpern, Arthur M.

2012-01-01

An upper-level undergraduate or beginning graduate project is described in which students obtain the Lennard-Jones 6-12 potential parameters for Ne[subscript 2] and Ar[subscript 2] from ab initio calculations and use the results to express pairwise interactions between the atoms in clusters containing up to N = 60 atoms. The students use simulated…

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.

PubMed

Kelly, Brendan J; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D; Collman, Ronald G; Bushman, Frederic D; Li, Hongzhe

2015-08-01

The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Paint and Click: Unified Interactions for Image Boundaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Summa, B.; Gooch, A. A.; Scorzelli, G.

Image boundaries are a fundamental component of many interactive digital photography techniques, enabling applications such as segmentation, panoramas, and seamless image composition. Interactions for image boundaries often rely on two complementary but separate approaches: editing via painting or clicking constraints. In this work, we provide a novel, unified approach for interactive editing of pairwise image boundaries that combines the ease of painting with the direct control of constraints. Rather than a sequential coupling, this new formulation allows full use of both interactions simultaneously, giving users unprecedented flexibility for fast boundary editing. To enable this new approach, we provide technical advancements.more » In particular, we detail a reformulation of image boundaries as a problem of finding cycles, expanding and correcting limitations of the previous work. Our new formulation provides boundary solutions for painted regions with performance on par with state-of-the-art specialized, paint-only techniques. In addition, we provide instantaneous exploration of the boundary solution space with user constraints. Finally, we provide examples of common graphics applications impacted by our new approach.« less

Interspecific competition in plants: how well do current methods answer fundamental questions?

PubMed

Connolly, J; Wayne, P; Bazzaz, F A

2001-02-01

Accurately quantifying and interpreting the processes and outcomes of competition among plants is essential for evaluating theories of plant community organization and evolution. We argue that many current experimental approaches to quantifying competitive interactions introduce size bias, which may significantly impact the quantitative and qualitative conclusions drawn from studies. Size bias generally arises when estimates of competitive ability are erroneously influenced by the initial size of competing individuals. We employ a series of quantitative thought experiments to demonstrate the potential for size bias in analysis of four traditional experimental designs (pairwise, replacement series, additive series, and response surfaces) either when only final measurements are available or when both initial and final measurements are collected. We distinguish three questions relevant to describing competitive interactions: Which species dominates? Which species gains? and How do species affect each other? The choice of experimental design and measurements greatly influences the scope of inference permitted. Conditions under which the latter two questions can give biased information are tabulated. We outline a new approach to characterizing competition that avoids size bias and that improves the concordance between research question and experimental design. The implications of the choice of size metrics used to quantify both the initial state and the responses of elements in interspecific mixtures are discussed. The relevance of size bias in competition studies with organisms other than plants is also discussed.

Abnormal functional network connectivity among resting-state networks in children with frontal lobe epilepsy.

PubMed

Widjaja, E; Zamyadi, M; Raybaud, C; Snead, O C; Smith, M L

2013-12-01

Epilepsy is considered a disorder of neural networks. The aims of this study were to assess functional connectivity within resting-state networks and functional network connectivity across resting-state networks by use of resting-state fMRI in children with frontal lobe epilepsy and to relate changes in resting-state networks with neuropsychological function. Fifteen patients with frontal lobe epilepsy and normal MR imaging and 14 healthy control subjects were recruited. Spatial independent component analysis was used to identify the resting-state networks, including frontal, attention, default mode network, sensorimotor, visual, and auditory networks. The Z-maps of resting-state networks were compared between patients and control subjects. The relation between abnormal connectivity and neuropsychological function was assessed. Correlations from all pair-wise combinations of independent components were performed for each group and compared between groups. The frontal network was the only network that showed reduced connectivity in patients relative to control subjects. The remaining 5 networks demonstrated both reduced and increased functional connectivity within resting-state networks in patients. There was a weak association between connectivity in frontal network and executive function (P = .029) and a significant association between sensorimotor network and fine motor function (P = .004). Control subjects had 79 pair-wise independent components that showed significant temporal coherence across all resting-state networks except for default mode network-auditory network. Patients had 66 pairs of independent components that showed significant temporal coherence across all resting-state networks. Group comparison showed reduced functional network connectivity between default mode network-attention, frontal-sensorimotor, and frontal-visual networks and increased functional network connectivity between frontal-attention, default mode network-sensorimotor, and frontal-visual networks in patients relative to control subjects. We found abnormal functional connectivity within and across resting-state networks in children with frontal lobe epilepsy. Impairment in functional connectivity was associated with impaired neuropsychological function.

Learning a constrained conditional random field for enhanced segmentation of fallen trees in ALS point clouds

NASA Astrophysics Data System (ADS)

Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe

2018-06-01

In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline is composed of two steps. First, short stem segments of equal length are detected and a subset of them is selected for further processing, while in the second step the chosen segments are merged to form entire trees. The first step is accomplished using the specialized CRF defined on the space of segment labelings, capable of finding segment candidates which are easier to merge subsequently. To achieve this, the CRF considers not only the features of every candidate individually, but incorporates pairwise spatial interactions between adjacent segments into the model. In particular, pairwise interactions include a collinearity/angular deviation probability which is learned from training data as well as the ratio of spatial overlap, whereas unary potentials encode a learned probabilistic model of the laser point distribution around each segment. Each of these components enters the CRF energy with its own balance factor. To process previously unseen data, we first calculate the subset of segments for merging on a grid of balance factors by minimizing the CRF energy. Then, we perform the merging and rank the balance configurations according to the quality of their resulting merged trees, obtained from a learned tree appearance model. The final result is derived from the top-ranked configuration. We tested our approach on 5 plots from the Bavarian Forest National Park using reference data acquired in a field inventory. Compared to our previous segment selection method without pairwise interactions, an increase in detection correctness and completeness of up to 7 and 9 percentage points, respectively, was observed.

Pair-Wise Trajectory Management-Oceanic (PTM-O) . [Concept of Operations—Version 3.9

NASA Technical Reports Server (NTRS)

Jones, Kenneth M.

2014-01-01

This document describes the Pair-wise Trajectory Management-Oceanic (PTM-O) Concept of Operations (ConOps). Pair-wise Trajectory Management (PTM) is a concept that includes airborne and ground-based capabilities designed to enable and to benefit from, airborne pair-wise distance-monitoring capability. PTM includes the capabilities needed for the controller to issue a PTM clearance that resolves a conflict for a specific pair of aircraft. PTM avionics include the capabilities needed for the flight crew to manage their trajectory relative to specific designated aircraft. Pair-wise Trajectory Management PTM-Oceanic (PTM-O) is a regional specific application of the PTM concept. PTM is sponsored by the National Aeronautics and Space Administration (NASA) Concept and Technology Development Project (part of NASA's Airspace Systems Program). The goal of PTM is to use enhanced and distributed communications and surveillance along with airborne tools to permit reduced separation standards for given aircraft pairs, thereby increasing the capacity and efficiency of aircraft operations at a given altitude or volume of airspace.

Why rate when you could compare? Using the "EloChoice" package to assess pairwise comparisons of perceived physical strength.

PubMed

Clark, Andrew P; Howard, Kate L; Woods, Andy T; Penton-Voak, Ian S; Neumann, Christof

2018-01-01

We introduce "EloChoice", a package for R which uses Elo rating to assess pairwise comparisons between stimuli in order to measure perceived stimulus characteristics. To demonstrate the package and compare results from forced choice pairwise comparisons to those from more standard single stimulus rating tasks using Likert (or Likert-type) items, we investigated perceptions of physical strength from images of male bodies. The stimulus set comprised images of 82 men standing on a raised platform with minimal clothing. Strength-related anthropometrics and grip strength measurements were available for each man in the set. UK laboratory participants (Study 1) and US online participants (Study 2) viewed all images in both a Likert rating task, to collect mean Likert scores, and a pairwise comparison task, to calculate Elo, mean Elo (mElo), and Bradley-Terry scores. Within both studies, Likert, Elo and Bradley-Terry scores were closely correlated to mElo scores (all rs > 0.95), and all measures were correlated with stimulus grip strength (all rs > 0.38) and body size (all rs > 0.59). However, mElo scores were less variable than Elo scores and were hundreds of times quicker to compute than Bradley-Terry scores. Responses in pairwise comparison trials were 2/3 quicker than in Likert tasks, indicating that participants found pairwise comparisons to be easier. In addition, mElo scores generated from a data set with half the participants randomly excluded produced very comparable results to those produced with Likert scores from the full participant set, indicating that researchers require fewer participants when using pairwise comparisons.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA

PubMed Central

Kelly, Brendan J.; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D.; Collman, Ronald G.; Bushman, Frederic D.; Li, Hongzhe

2015-01-01

Motivation: The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence–absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. Results: We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. Availability and implementation: http://github.com/brendankelly/micropower. Contact: brendank@mail.med.upenn.edu or hongzhe@upenn.edu PMID:25819674

Realistic decision-making processes in a vaccination game

NASA Astrophysics Data System (ADS)

Iwamura, Yoshiro; Tanimoto, Jun

2018-03-01

Previous studies of vaccination games have nearly always assumed a pairwise comparison between a focal and neighboring player for the strategy updating rule, which comes from numerous compiled studies on spatial versions of 2-player and 2-strategy (2 × 2) games such as the spatial prisoner's dilemma (SPD). We propose, in this study, new update rules because the human decision-making process of whether to commit to a vaccination is obviously influenced by a "sense of crisis" or "fear" urging him/her toward vaccination, otherwise they will likely be infected. The rule assumes that an agent evaluates whether getting a vaccination or trying to free ride should be attempted based on observations of whether neighboring non-vaccinators were able to successfully free ride during the previous time-step. Compared to the conventional updating rule (standard pairwise comparison assuming a Fermi function), the new rules generally realize higher vaccination coverage and smaller final epidemic sizes. One rule in particular shows very good performance with significantly smaller epidemic sizes despite comparable levels of vaccination coverage. This is because the specific update rule helps vaccinators spread widely in the domain, which effectively hampers the spread of epidemics.

Anisotropic interaction rules in circular motions of pigeon flocks: An empirical study based on sparse Bayesian learning

NASA Astrophysics Data System (ADS)

Chen, Duxin; Xu, Bowen; Zhu, Tao; Zhou, Tao; Zhang, Hai-Tao

2017-08-01

Coordination shall be deemed to the result of interindividual interaction among natural gregarious animal groups. However, revealing the underlying interaction rules and decision-making strategies governing highly coordinated motion in bird flocks is still a long-standing challenge. Based on analysis of high spatial-temporal resolution GPS data of three pigeon flocks, we extract the hidden interaction principle by using a newly emerging machine learning method, namely the sparse Bayesian learning. It is observed that the interaction probability has an inflection point at pairwise distance of 3-4 m closer than the average maximum interindividual distance, after which it decays strictly with rising pairwise metric distances. Significantly, the density of spatial neighbor distribution is strongly anisotropic, with an evident lack of interactions along individual velocity. Thus, it is found that in small-sized bird flocks, individuals reciprocally cooperate with a variational number of neighbors in metric space and tend to interact with closer time-varying neighbors, rather than interacting with a fixed number of topological ones. Finally, extensive numerical investigation is conducted to verify both the revealed interaction and decision-making principle during circular flights of pigeon flocks.

Smoothed particle hydrodynamics study of the roughness effect on contact angle and droplet flow.

PubMed

Shigorina, Elena; Kordilla, Jannes; Tartakovsky, Alexandre M

2017-09-01

We employ a pairwise force smoothed particle hydrodynamics (PF-SPH) model to simulate sessile and transient droplets on rough hydrophobic and hydrophilic surfaces. PF-SPH allows modeling of free-surface flows without discretizing the air phase, which is achieved by imposing the surface tension and dynamic contact angles with pairwise interaction forces. We use the PF-SPH model to study the effect of surface roughness and microscopic contact angle on the effective contact angle and droplet dynamics. In the first part of this work, we investigate static contact angles of sessile droplets on different types of rough surfaces. We find that the effective static contact angles of Cassie and Wenzel droplets on a rough surface are greater than the corresponding microscale static contact angles. As a result, microscale hydrophobic rough surfaces also show effective hydrophobic behavior. On the other hand, microscale hydrophilic surfaces may be macroscopically hydrophilic or hydrophobic, depending on the type of roughness. We study the dependence of the transition between Cassie and Wenzel states on roughness and droplet size, which can be linked to the critical pressure for the given fluid-substrate combination. We observe good agreement between simulations and theoretical predictions. Finally, we study the impact of the roughness orientation (i.e., an anisotropic roughness) and surface inclination on droplet flow velocities. Simulations show that droplet flow velocities are lower if the surface roughness is oriented perpendicular to the flow direction. If the predominant elements of surface roughness are in alignment with the flow direction, the flow velocities increase compared to smooth surfaces, which can be attributed to the decrease in fluid-solid contact area similar to the lotus effect. We demonstrate that classical linear scaling relationships between Bond and capillary numbers for droplet flow on flat surfaces also hold for flow on rough surfaces.

Why rate when you could compare? Using the “EloChoice” package to assess pairwise comparisons of perceived physical strength

PubMed Central

Howard, Kate L.; Woods, Andy T.; Penton-Voak, Ian S.; Neumann, Christof

2018-01-01

We introduce “EloChoice”, a package for R which uses Elo rating to assess pairwise comparisons between stimuli in order to measure perceived stimulus characteristics. To demonstrate the package and compare results from forced choice pairwise comparisons to those from more standard single stimulus rating tasks using Likert (or Likert-type) items, we investigated perceptions of physical strength from images of male bodies. The stimulus set comprised images of 82 men standing on a raised platform with minimal clothing. Strength-related anthropometrics and grip strength measurements were available for each man in the set. UK laboratory participants (Study 1) and US online participants (Study 2) viewed all images in both a Likert rating task, to collect mean Likert scores, and a pairwise comparison task, to calculate Elo, mean Elo (mElo), and Bradley-Terry scores. Within both studies, Likert, Elo and Bradley-Terry scores were closely correlated to mElo scores (all rs > 0.95), and all measures were correlated with stimulus grip strength (all rs > 0.38) and body size (all rs > 0.59). However, mElo scores were less variable than Elo scores and were hundreds of times quicker to compute than Bradley-Terry scores. Responses in pairwise comparison trials were 2/3 quicker than in Likert tasks, indicating that participants found pairwise comparisons to be easier. In addition, mElo scores generated from a data set with half the participants randomly excluded produced very comparable results to those produced with Likert scores from the full participant set, indicating that researchers require fewer participants when using pairwise comparisons. PMID:29293615

Functional connectivity analysis in resting state fMRI with echo-state networks and non-metric clustering for network structure recovery

NASA Astrophysics Data System (ADS)

Wismüller, Axel; DSouza, Adora M.; Abidin, Anas Z.; Wang, Xixi; Hobbs, Susan K.; Nagarajan, Mahesh B.

2015-03-01

Echo state networks (ESN) are recurrent neural networks where the hidden layer is replaced with a fixed reservoir of neurons. Unlike feed-forward networks, neuron training in ESN is restricted to the output neurons alone thereby providing a computational advantage. We demonstrate the use of such ESNs in our mutual connectivity analysis (MCA) framework for recovering the primary motor cortex network associated with hand movement from resting state functional MRI (fMRI) data. Such a framework consists of two steps - (1) defining a pair-wise affinity matrix between different pixel time series within the brain to characterize network activity and (2) recovering network components from the affinity matrix with non-metric clustering. Here, ESNs are used to evaluate pair-wise cross-estimation performance between pixel time series to create the affinity matrix, which is subsequently subject to non-metric clustering with the Louvain method. For comparison, the ground truth of the motor cortex network structure is established with a task-based fMRI sequence. Overlap between the primary motor cortex network recovered with our model free MCA approach and the ground truth was measured with the Dice coefficient. Our results show that network recovery with our proposed MCA approach is in close agreement with the ground truth. Such network recovery is achieved without requiring low-pass filtering of the time series ensembles prior to analysis, an fMRI preprocessing step that has courted controversy in recent years. Thus, we conclude our MCA framework can allow recovery and visualization of the underlying functionally connected networks in the brain on resting state fMRI.

Entanglement as a signature of quantum chaos.

PubMed

Wang, Xiaoguang; Ghose, Shohini; Sanders, Barry C; Hu, Bambi

2004-01-01

We explore the dynamics of entanglement in classically chaotic systems by considering a multiqubit system that behaves collectively as a spin system obeying the dynamics of the quantum kicked top. In the classical limit, the kicked top exhibits both regular and chaotic dynamics depending on the strength of the chaoticity parameter kappa in the Hamiltonian. We show that the entanglement of the multiqubit system, considered for both the bipartite and the pairwise entanglement, yields a signature of quantum chaos. Whereas bipartite entanglement is enhanced in the chaotic region, pairwise entanglement is suppressed. Furthermore, we define a time-averaged entangling power and show that this entangling power changes markedly as kappa moves the system from being predominantly regular to being predominantly chaotic, thus sharply identifying the edge of chaos. When this entangling power is averaged over all states, it yields a signature of global chaos. The qualitative behavior of this global entangling power is similar to that of the classical Lyapunov exponent.

Quantitative Tools for Examining the Vocalizations of Juvenile Songbirds

PubMed Central

Wellock, Cameron D.; Reeke, George N.

2012-01-01

The singing of juvenile songbirds is highly variable and not well stereotyped, a feature that makes it difficult to analyze with existing computational techniques. We present here a method suitable for analyzing such vocalizations, windowed spectral pattern recognition (WSPR). Rather than performing pairwise sample comparisons, WSPR measures the typicality of a sample against a large sample set. We also illustrate how WSPR can be used to perform a variety of tasks, such as sample classification, song ontogeny measurement, and song variability measurement. Finally, we present a novel measure, based on WSPR, for quantifying the apparent complexity of a bird's singing. PMID:22701474

Genetic structure of Pseudococcus microcirculus (Hemiptera: Pseudococcidae) populations on epiphytic orchids in south Florida.

PubMed

Zettler, J A; Adams, K; Frederick, B; Gutting, A; Ingebretsen, N; Ragsdale, A; Schrey, A

2017-03-01

In 2012, the orchid mealy bug Pseudococcus microcirculus was first detected in situ in North America's more diverse orchid region, the Big Cypress Basin (Collier Co FL). A follow-up survey showed that the mealy bug is more widespread and found on epiphytic orchids in two locations, in both the Fakahatchee Strand State Preserve (sites B and F) and the Florida Panther National Wildlife Refuge (sites M and C). There, we collected mealy bugs (n = 54) from 35 orchid individuals and screened allelic variation at seven microsatellite loci. We estimated genetic diversity and differentiation among all sites and compared the variation among individuals collected on the same plant. Genetic differentiation between sites M and C (F ST = 0.03, P < 0.01) and,Mand B (F ST = 0.04, P < 0.01) was detected.We also detected significantly lower mean pairwise relatedness among individuals from site B compared to all the other locations, and this population had the lowest inbreeding coefficient. Genetic diversity and mean pairwise relatedness were highly variable among plants with multiple individuals; however, plants from sites F and M tend to have collections of individuals with higher mean pairwise relatedness compared to sites B and C. Our results indicate that there is genetic diversity and differentiation among mealy bugs in these locations, and that collections of individuals on the same plant are genetically diverse. As such, the mealy bugs throughout these areas are likely to be genetically diverse and exist in multiple distinct populations.

Fast and accurate estimation of the covariance between pairwise maximum likelihood distances.

PubMed

Gil, Manuel

2014-01-01

Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account to increase precision in any process that compares or combines distances. This paper introduces a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei & Jin, 1989) which links the covariance to path lengths. It is proven here under a simple symmetric substitution model. A simulation shows that the estimator outperforms previously published ones in terms of the mean squared error.

Fast and accurate estimation of the covariance between pairwise maximum likelihood distances

PubMed Central

2014-01-01

Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account to increase precision in any process that compares or combines distances. This paper introduces a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei & Jin, 1989) which links the covariance to path lengths. It is proven here under a simple symmetric substitution model. A simulation shows that the estimator outperforms previously published ones in terms of the mean squared error. PMID:25279263

Pick-off annihilation of positronium in matter using full correlation single particle potentials: solid He.

PubMed

Zubiaga, A; Tuomisto, F; Puska, M J

2015-01-29

We investigate the modeling of positronium (Ps) states and their pick-off annihilation trapped at open volumes pockets in condensed molecular matter. Our starting point is the interacting many-body system of Ps and a He atom because it is the smallest entity that can mimic the energy gap between the highest occupied and lowest unoccupied molecular orbitals of molecules, and yet the many-body structure of the HePs system can be calculated accurately enough. The exact-diagonalization solution of the HePs system enables us to construct a pairwise full-correlation single-particle potential for the Ps-He interaction, and the total potential in solids is obtained as a superposition of the pairwise potentials. We study in detail Ps states and their pick-off annihilation rates in voids inside solid He and analyze experimental results for Ps-induced voids in liquid He obtaining the radii of the voids. More importantly, we generalize our conclusions by testing the validity of the Tao-Eldrup model, widely used to analyze ortho-Ps annihilation measurements for voids in molecular matter, against our theoretical results for the solid He. Moreover, we discuss the influence of the partial charges of polar molecules and the strength of the van der Waals interaction on the pick-off annihilation rate.

ParallABEL: an R library for generalized parallelization of genome-wide association studies

PubMed Central

2010-01-01

Background Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Results Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Conclusions Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL. PMID:20429914

Learning a Markov Logic network for supervised gene regulatory network inference

PubMed Central

2013-01-01

Background Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. Results We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate “regulates”, starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a pairwise SVM while providing relevant insights on the predictions. Conclusions The numerical studies show that MLN achieves very good predictive performance while opening the door to some interpretability of the decisions. Besides the ability to suggest new regulations, such an approach allows to cross-validate experimental data with existing knowledge. PMID:24028533

Learning a Markov Logic network for supervised gene regulatory network inference.

PubMed

Brouard, Céline; Vrain, Christel; Dubois, Julie; Castel, David; Debily, Marie-Anne; d'Alché-Buc, Florence

2013-09-12

Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate "regulates", starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a pairwise SVM while providing relevant insights on the predictions. The numerical studies show that MLN achieves very good predictive performance while opening the door to some interpretability of the decisions. Besides the ability to suggest new regulations, such an approach allows to cross-validate experimental data with existing knowledge.

Non-pairwise additivity of the leading-order dispersion energy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hollett, Joshua W., E-mail: j.hollett@uwinnipeg.ca

2015-02-28

The leading-order (i.e., dipole-dipole) dispersion energy is calculated for one-dimensional (1D) and two-dimensional (2D) infinite lattices, and an infinite 1D array of infinitely long lines, of doubly occupied locally harmonic wells. The dispersion energy is decomposed into pairwise and non-pairwise additive components. By varying the force constant and separation of the wells, the non-pairwise additive contribution to the dispersion energy is shown to depend on the overlap of density between neighboring wells. As well separation is increased, the non-pairwise additivity of the dispersion energy decays. The different rates of decay for 1D and 2D lattices of wells is explained inmore » terms of a Jacobian effect that influences the number of nearest neighbors. For an array of infinitely long lines of wells spaced 5 bohrs apart, and an inter-well spacing of 3 bohrs within a line, the non-pairwise additive component of the leading-order dispersion energy is −0.11 kJ mol{sup −1} well{sup −1}, which is 7% of the total. The polarizability of the wells and the density overlap between them are small in comparison to that of the atomic densities that arise from the molecular density partitioning used in post-density-functional theory (DFT) damped dispersion corrections, or DFT-D methods. Therefore, the nonadditivity of the leading-order dispersion observed here is a conservative estimate of that in molecular clusters.« less

Controllability of symmetric spin networks

NASA Astrophysics Data System (ADS)

Albertini, Francesca; D'Alessandro, Domenico

2018-05-01

We consider a network of n spin 1/2 systems which are pairwise interacting via Ising interaction and are controlled by the same electro-magnetic control field. Such a system presents symmetries since the Hamiltonian is unchanged if we permute two spins. This prevents full (operator) controllability, in that not every unitary evolution can be obtained. We prove however that controllability is verified if we restrict ourselves to unitary evolutions which preserve the above permutation invariance. For low dimensional cases, n = 2 and n = 3, we provide an analysis of the Lie group of available evolutions and give explicit control laws to transfer between two arbitrary permutation invariant states. This class of states includes highly entangled states such as Greenberger-Horne-Zeilinger (GHZ) states and W states, which are of interest in quantum information.

Intransitivity is infrequent and fails to promote annual plant coexistence without pairwise niche differences.

PubMed

Godoy, Oscar; Stouffer, Daniel B; Kraft, Nathan J B; Levine, Jonathan M

2017-05-01

Intransitive competition is often projected to be a widespread mechanism of species coexistence in ecological communities. However, it is unknown how much of the coexistence we observe in nature results from this mechanism when species interactions are also stabilized by pairwise niche differences. We combined field-parameterized models of competition among 18 annual plant species with tools from network theory to quantify the prevalence of intransitive competitive relationships. We then analyzed the predicted outcome of competitive interactions with and without pairwise niche differences. Intransitive competition was found for just 15-19% of the 816 possible triplets, and this mechanism was never sufficient to stabilize the coexistence of the triplet when the pair-wise niche differences between competitors were removed. Of the transitive and intransitive triplets, only four were predicted to coexist and these were more similar in multidimensional trait space defined by 11 functional traits than non-coexisting triplets. Our results argue that intransitive competition may be less frequent than recently posed, and that even when it does operate, pairwise niche differences may be key to possible coexistence. © 2017 by the Ecological Society of America.

Dynamics of pairwise motions in the Cosmic Web

NASA Astrophysics Data System (ADS)

Hellwing, Wojciech A.

2016-10-01

We present results of analysis of the dark matter (DM) pairwise velocity statistics in different Cosmic Web environments. We use the DM velocity and density field from the Millennium 2 simulation together with the NEXUS+ algorithm to segment the simulation volume into voxels uniquely identifying one of the four possible environments: nodes, filaments, walls or cosmic voids. We show that the PDFs of the mean infall velocities v 12 as well as its spatial dependence together with the perpendicular and parallel velocity dispersions bear a significant signal of the large-scale structure environment in which DM particle pairs are embedded. The pairwise flows are notably colder and have smaller mean magnitude in wall and voids, when compared to much denser environments of filaments and nodes. We discuss on our results, indicating that they are consistent with a simple theoretical predictions for pairwise motions as induced by gravitational instability mechanism. Our results indicate that the Cosmic Web elements are coherent dynamical entities rather than just temporal geometrical associations. In addition it should be possible to observationally test various Cosmic Web finding algorithms by segmenting available peculiar velocity data and studying resulting pairwise velocity statistics.

Entropy of spatial network ensembles

NASA Astrophysics Data System (ADS)

Coon, Justin P.; Dettmann, Carl P.; Georgiou, Orestis

2018-04-01

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly in space and links formed independently between pairs of nodes with probability given by a specified function (the "pair connection function") of their mutual distance. We consider the general case where randomness arises in node positions as well as pairwise connections (i.e., for a given pair distance, the corresponding edge state is a random variable). Classical random geometric graph and exponential graph models can be recovered in certain limits. We derive a simple bound for the entropy of a spatial network ensemble and calculate the conditional entropy of an ensemble given the node location distribution for hard and soft (probabilistic) pair connection functions. Under this formalism, we derive the connection function that yields maximum entropy under general constraints. Finally, we apply our analytical framework to study two practical examples: ad hoc wireless networks and the US flight network. Through the study of these examples, we illustrate that both exhibit properties that are indicative of nearly maximally entropic ensembles.

Two-component dark-bright solitons in three-dimensional atomic Bose-Einstein condensates.

PubMed

Wang, Wenlong; Kevrekidis, P G

2017-03-01

In the present work, we revisit two-component Bose-Einstein condensates in their fully three-dimensional (3D) form. Motivated by earlier studies of dark-bright solitons in the 1D case, we explore the stability of these structures in their fully 3D form in two variants. In one the dark soliton is planar and trapping a planar bright (disk) soliton. In the other case, a dark spherical shell soliton creates an effective potential in which a bright spherical shell of atoms is trapped in the second component. We identify these solutions as numerically exact states (up to a prescribed accuracy) and perform a Bogolyubov-de Gennes linearization analysis that illustrates that both structures can be dynamically stable in suitable intervals of sufficiently low chemical potentials. We corroborate this finding theoretically by analyzing the stability via degenerate perturbation theory near the linear limit of the system. When the solitary waves are found to be unstable, we explore their dynamical evolution via direct numerical simulations which, in turn, reveal wave forms that are more robust. Finally, using the SO(2) symmetry of the model, we produce multi-dark-bright planar or shell solitons involved in pairwise oscillatory motion.

Effect of interacting second- and third-order stimulus-dependent correlations on population-coding asymmetries.

PubMed

Montangie, Lisandro; Montani, Fernando

2016-10-01

Spike correlations among neurons are widely encountered in the brain. Although models accounting for pairwise interactions have proved able to capture some of the most important features of population activity at the level of the retina, the evidence shows that pairwise neuronal correlation analysis does not resolve cooperative population dynamics by itself. By means of a series expansion for short time scales of the mutual information conveyed by a population of neurons, the information transmission can be broken down into firing rate and correlational components. In a proposed extension of this framework, we investigate the information components considering both second- and higher-order correlations. We show that the existence of a mixed stimulus-dependent correlation term defines a new scenario for the interplay between pairwise and higher-than-pairwise interactions in noise and signal correlations that would lead either to redundancy or synergy in the information-theoretic sense.

Automatic Camera Calibration Using Multiple Sets of Pairwise Correspondences.

PubMed

Vasconcelos, Francisco; Barreto, Joao P; Boyer, Edmond

2018-04-01

We propose a new method to add an uncalibrated node into a network of calibrated cameras using only pairwise point correspondences. While previous methods perform this task using triple correspondences, these are often difficult to establish when there is limited overlap between different views. In such challenging cases we must rely on pairwise correspondences and our solution becomes more advantageous. Our method includes an 11-point minimal solution for the intrinsic and extrinsic calibration of a camera from pairwise correspondences with other two calibrated cameras, and a new inlier selection framework that extends the traditional RANSAC family of algorithms to sampling across multiple datasets. Our method is validated on different application scenarios where a lack of triple correspondences might occur: addition of a new node to a camera network; calibration and motion estimation of a moving camera inside a camera network; and addition of views with limited overlap to a Structure-from-Motion model.

Shaped Ceria Nanocrystals Catalyze Efficient and Selective Para-Hydrogen-Enhanced Polarization.

PubMed

Zhao, Evan W; Zheng, Haibin; Zhou, Ronghui; Hagelin-Weaver, Helena E; Bowers, Clifford R

2015-11-23

Intense para-hydrogen-enhanced NMR signals are observed in the hydrogenation of propene and propyne over ceria nanocubes, nano-octahedra, and nanorods. The well-defined ceria shapes, synthesized by a hydrothermal method, expose different crystalline facets with various oxygen vacancy densities, which are known to play a role in hydrogenation and oxidation catalysis. While the catalytic activity of the hydrogenation of propene over ceria is strongly facet-dependent, the pairwise selectivity is low (2.4% at 375 °C), which is consistent with stepwise H atom transfer, and it is the same for all three nanocrystal shapes. Selective semi-hydrogenation of propyne over ceria nanocubes yields hyperpolarized propene with a similar pairwise selectivity of (2.7% at 300 °C), indicating product formation predominantly by a non-pairwise addition. Ceria is also shown to be an efficient pairwise replacement catalyst for propene. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiple Quantum Coherences (MQ) NMR and Entanglement Dynamics in the Mixed-Three-Spin XXX Heisenberg Model with Single-Ion Anisotropy

NASA Astrophysics Data System (ADS)

Hamid, Arian Zad

2016-12-01

We analytically investigate Multiple Quantum (MQ) NMR dynamics in a mixed-three-spin (1/2,1,1/2) system with XXX Heisenberg model at the front of an external homogeneous magnetic field B. A single-ion anisotropy property ζ is considered for the spin-1. The intensities dependence of MQ NMR coherences on their orders (zeroth and second orders) for two pairs of spins (1,1/2) and (1/2,1/2) of the favorite tripartite system are obtained. It is also investigated dynamics of the pairwise quantum entanglement for the bipartite (sub)systems (1,1/2) and (1/2,1/2) permanently coupled by, respectively, coupling constants J}1 and J}2, by means of concurrence and fidelity. Then, some straightforward comparisons are done between these quantities and the intensities of MQ NMR coherences and ultimately some interesting results are reported. We also show that the time evolution of MQ coherences based on the reduced density matrix of the pair spins (1,1/2) is closely connected with the dynamics of the pairwise entanglement. Finally, we prove that one can introduce MQ coherence of the zeroth order corresponds to the pair spins (1,1/2) as an entanglement witness at some special time intervals.

Comparisons of false negative rates from a trend test alone and from a trend test jointly with a control-high groups pairwise test in the determination of the carcinogenicity of new drugs.

PubMed

Lin, Karl K; Rahman, Mohammad A

2018-05-21

Interest has been expressed in using a joint test procedure that requires that the results of both a trend test and a pairwise comparison test between the control and the high groups be statistically significant simultaneously at the levels of significance recommended in the FDA 2001 draft guidance for industry document for the separate tests in order for the drug effect on the development of an individual tumor type to be considered as statistically significant. Results of our simulation studies show that there is a serious consequence of large inflations of the false negative rate through large decreases of false positive rate in the use of the above joint test procedure in the final interpretation of the carcinogenicity potential of a new drug if the levels of significance recommended for separate tests are used. The inflation can be as high as 204.5% of the false negative rate when the trend test alone is required to test if the effect is statistically significant. To correct the problem, new sets of levels of significance have also been developed for those who want to use the joint test in reviews of carcinogenicity studies.

Mean convergence theorems and weak laws of large numbers for weighted sums of random variables under a condition of weighted integrability

NASA Astrophysics Data System (ADS)

Ordóñez Cabrera, Manuel; Volodin, Andrei I.

2005-05-01

From the classical notion of uniform integrability of a sequence of random variables, a new concept of integrability (called h-integrability) is introduced for an array of random variables, concerning an array of constantsE We prove that this concept is weaker than other previous related notions of integrability, such as Cesàro uniform integrability [Chandra, Sankhya Ser. A 51 (1989) 309-317], uniform integrability concerning the weights [Ordóñez Cabrera, Collect. Math. 45 (1994) 121-132] and Cesàro [alpha]-integrability [Chandra and Goswami, J. Theoret. ProbabE 16 (2003) 655-669]. Under this condition of integrability and appropriate conditions on the array of weights, mean convergence theorems and weak laws of large numbers for weighted sums of an array of random variables are obtained when the random variables are subject to some special kinds of dependence: (a) rowwise pairwise negative dependence, (b) rowwise pairwise non-positive correlation, (c) when the sequence of random variables in every row is [phi]-mixing. Finally, we consider the general weak law of large numbers in the sense of Gut [Statist. Probab. Lett. 14 (1992) 49-52] under this new condition of integrability for a Banach space setting.

Upper bounds on the error probabilities and asymptotic error exponents in quantum multiple state discrimination

NASA Astrophysics Data System (ADS)

Audenaert, Koenraad M. R.; Mosonyi, Milán

2014-10-01

We consider the multiple hypothesis testing problem for symmetric quantum state discrimination between r given states σ1, …, σr. By splitting up the overall test into multiple binary tests in various ways we obtain a number of upper bounds on the optimal error probability in terms of the binary error probabilities. These upper bounds allow us to deduce various bounds on the asymptotic error rate, for which it has been hypothesized that it is given by the multi-hypothesis quantum Chernoff bound (or Chernoff divergence) C(σ1, …, σr), as recently introduced by Nussbaum and Szkoła in analogy with Salikhov's classical multi-hypothesis Chernoff bound. This quantity is defined as the minimum of the pairwise binary Chernoff divergences min _{j

An enhanced Petri-net model to predict synergistic effects of pairwise drug combinations from gene microarray data.

PubMed

Jin, Guangxu; Zhao, Hong; Zhou, Xiaobo; Wong, Stephen T C

2011-07-01

Prediction of synergistic effects of drug combinations has traditionally been relied on phenotypic response data. However, such methods cannot be used to identify molecular signaling mechanisms of synergistic drug combinations. In this article, we propose an enhanced Petri-Net (EPN) model to recognize the synergistic effects of drug combinations from the molecular response profiles, i.e. drug-treated microarray data. We addressed the downstream signaling network of the targets for the two individual drugs used in the pairwise combinations and applied EPN to the identified targeted signaling network. In EPN, drugs and signaling molecules are assigned to different types of places, while drug doses and molecular expressions are denoted by color tokens. The changes of molecular expressions caused by treatments of drugs are simulated by two actions of EPN: firing and blasting. Firing is to transit the drug and molecule tokens from one node or place to another, and blasting is to reduce the number of molecule tokens by drug tokens in a molecule node. The goal of EPN is to mediate the state characterized by control condition without any treatment to that of treatment and to depict the drug effects on molecules by the drug tokens. We applied EPN to our generated pairwise drug combination microarray data. The synergistic predictions using EPN are consistent with those predicted using phenotypic response data. The molecules responsible for the synergistic effects with their associated feedback loops display the mechanisms of synergism. The software implemented in Python 2.7 programming language is available from request. stwong@tmhs.org.

Dynamics of the Final Stages of Terrestrial Planet Growth and the Formation of the Earth-Moon System

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Rivera, Eugenio J.; DeVincenzi, Donald (Technical Monitor)

2000-01-01

An overview of current theories of star and planet formation, with emphasis on terrestrial planet accretion and the formation of the Earth-Moon system is presented. These models predict that rocky planets should form around most single stars, although it is possible that in some cases such planets are lost to orbital decay within the protoplanetary disk. The frequency of formation of gas giant planets is more difficult to predict theoretically. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant impacts during the final stages of growth can produce large planetary satellites, such as Earth's Moon. Giant planets begin their growth like terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates.

Half-unit weighted bilinear algorithm for image contrast enhancement in capsule endoscopy

NASA Astrophysics Data System (ADS)

Rukundo, Olivier

2018-04-01

This paper proposes a novel enhancement method based exclusively on the bilinear interpolation algorithm for capsule endoscopy images. The proposed method does not convert the original RBG image components to HSV or any other color space or model; instead, it processes directly RGB components. In each component, a group of four adjacent pixels and half-unit weight in the bilinear weighting function are used to calculate the average pixel value, identical for each pixel in that particular group. After calculations, groups of identical pixels are overlapped successively in horizontal and vertical directions to achieve a preliminary-enhanced image. The final-enhanced image is achieved by halving the sum of the original and preliminary-enhanced image pixels. Quantitative and qualitative experiments were conducted focusing on pairwise comparisons between original and enhanced images. Final-enhanced images have generally the best diagnostic quality and gave more details about the visibility of vessels and structures in capsule endoscopy images.

Self-propulsion and interactions of catalytic particles in a chemically active medium.

PubMed

Banigan, Edward J; Marko, John F

2016-01-01

Enzymatic "machines," such as catalytic rods or colloids, can self-propel and interact by generating gradients of their substrates. We theoretically investigate the behaviors of such machines in a chemically active environment where their catalytic substrates are continuously synthesized and destroyed, as occurs in living cells. We show how the kinetic properties of the medium modulate self-propulsion and pairwise interactions between machines, with the latter controlled by a tunable characteristic interaction range analogous to the Debye screening length in an electrolytic solution. Finally, we discuss the effective force arising between interacting machines and possible biological applications, such as partitioning of bacterial plasmids.

Dynamical behavior of susceptible-infected-recovered-susceptible epidemic model on weighted networks

NASA Astrophysics Data System (ADS)

Wu, Qingchu; Zhang, Fei

2018-02-01

We study susceptible-infected-recovered-susceptible epidemic model in weighted, regular, and random complex networks. We institute a pairwise-type mathematical model with a general transmission rate to evaluate the influence of the link-weight distribution on the spreading process. Furthermore, we develop a dimensionality reduction approach to derive the condition for the contagion outbreak. Finally, we analyze the influence of the heterogeneity of weight distribution on the outbreak condition for the scenario with a linear transmission rate. Our theoretical analysis is in agreement with stochastic simulations, showing that the heterogeneity of link-weight distribution can have a significant effect on the epidemic dynamics.

Online Pairwise Learning Algorithms.

PubMed

Ying, Yiming; Zhou, Ding-Xuan

2016-04-01

Pairwise learning usually refers to a learning task that involves a loss function depending on pairs of examples, among which the most notable ones are bipartite ranking, metric learning, and AUC maximization. In this letter we study an online algorithm for pairwise learning with a least-square loss function in an unconstrained setting of a reproducing kernel Hilbert space (RKHS) that we refer to as the Online Pairwise lEaRning Algorithm (OPERA). In contrast to existing works (Kar, Sriperumbudur, Jain, & Karnick, 2013 ; Wang, Khardon, Pechyony, & Jones, 2012 ), which require that the iterates are restricted to a bounded domain or the loss function is strongly convex, OPERA is associated with a non-strongly convex objective function and learns the target function in an unconstrained RKHS. Specifically, we establish a general theorem that guarantees the almost sure convergence for the last iterate of OPERA without any assumptions on the underlying distribution. Explicit convergence rates are derived under the condition of polynomially decaying step sizes. We also establish an interesting property for a family of widely used kernels in the setting of pairwise learning and illustrate the convergence results using such kernels. Our methodology mainly depends on the characterization of RKHSs using its associated integral operators and probability inequalities for random variables with values in a Hilbert space.

Cosmology with the pairwise kinematic SZ effect: Calibration and validation using hydrodynamical simulations

NASA Astrophysics Data System (ADS)

Soergel, Bjoern; Saro, Alexandro; Giannantonio, Tommaso; Efstathiou, George; Dolag, Klaus

2018-05-01

We study the potential of the kinematic SZ effect as a probe for cosmology, focusing on the pairwise method. The main challenge is disentangling the cosmologically interesting mean pairwise velocity from the cluster optical depth and the associated uncertainties on the baryonic physics in clusters. Furthermore, the pairwise kSZ signal might be affected by internal cluster motions or correlations between velocity and optical depth. We investigate these effects using the Magneticum cosmological hydrodynamical simulations, one of the largest simulations of this kind performed to date. We produce tSZ and kSZ maps with an area of ≃ 1600 deg2, and the corresponding cluster catalogues with M500c ≳ 3 × 1013 h-1M⊙ and z ≲ 2. From these data sets we calibrate a scaling relation between the average Compton-y parameter and optical depth. We show that this relation can be used to recover an accurate estimate of the mean pairwise velocity from the kSZ effect, and that this effect can be used as an important probe of cosmology. We discuss the impact of theoretical and observational systematic effects, and find that further work on feedback models is required to interpret future high-precision measurements of the kSZ effect.

Disability Weights for Chronic Mercury Intoxication Resulting from Gold Mining Activities: Results from an Online Pairwise Comparisons Survey.

PubMed

Steckling, Nadine; Devleesschauwer, Brecht; Winkelnkemper, Julia; Fischer, Florian; Ericson, Bret; Krämer, Alexander; Hornberg, Claudia; Fuller, Richard; Plass, Dietrich; Bose-O'Reilly, Stephan

2017-01-10

In artisanal small-scale gold mining, mercury is used for gold-extraction, putting miners and nearby residents at risk of chronic metallic mercury vapor intoxication (CMMVI). Burden of disease (BoD) analyses allow the estimation of the public health relevance of CMMVI, but until now there have been no specific CMMVI disability weights (DWs). The objective is to derive DWs for moderate and severe CMMVI. Disease-specific and generic health state descriptions of 18 diseases were used in a pairwise comparison survey. Mercury and BoD experts were invited to participate in an online survey. Data were analyzed using probit regression. Local regression was used to make the DWs comparable to the Global Burden of Disease (GBD) study. Alternative survey (visual analogue scale) and data analyses approaches (linear interpolation) were evaluated in scenario analyses. A total of 105 participants completed the questionnaire. DWs for moderate and severe CMMVI were 0.368 (0.261-0.484) and 0.588 (0.193-0.907), respectively. Scenario analyses resulted in higher mean values. The results are limited by the sample size, group of interviewees, questionnaire extent, and lack of generally accepted health state descriptions. DWs were derived to improve the data basis of mercury-related BoD estimates, providing useful information for policy-making. Integration of the results into the GBD DWs enhances comparability.

Disability Weights for Chronic Mercury Intoxication Resulting from Gold Mining Activities: Results from an Online Pairwise Comparisons Survey

PubMed Central

Steckling, Nadine; Devleesschauwer, Brecht; Winkelnkemper, Julia; Fischer, Florian; Ericson, Bret; Krämer, Alexander; Hornberg, Claudia; Fuller, Richard; Plass, Dietrich; Bose-O’Reilly, Stephan

2017-01-01

In artisanal small-scale gold mining, mercury is used for gold-extraction, putting miners and nearby residents at risk of chronic metallic mercury vapor intoxication (CMMVI). Burden of disease (BoD) analyses allow the estimation of the public health relevance of CMMVI, but until now there have been no specific CMMVI disability weights (DWs). The objective is to derive DWs for moderate and severe CMMVI. Disease-specific and generic health state descriptions of 18 diseases were used in a pairwise comparison survey. Mercury and BoD experts were invited to participate in an online survey. Data were analyzed using probit regression. Local regression was used to make the DWs comparable to the Global Burden of Disease (GBD) study. Alternative survey (visual analogue scale) and data analyses approaches (linear interpolation) were evaluated in scenario analyses. A total of 105 participants completed the questionnaire. DWs for moderate and severe CMMVI were 0.368 (0.261–0.484) and 0.588 (0.193–0.907), respectively. Scenario analyses resulted in higher mean values. The results are limited by the sample size, group of interviewees, questionnaire extent, and lack of generally accepted health state descriptions. DWs were derived to improve the data basis of mercury-related BoD estimates, providing useful information for policy-making. Integration of the results into the GBD DWs enhances comparability. PMID:28075395

Archaeomagnetic research in the United States midcontinent

NASA Astrophysics Data System (ADS)

Lengyel, Stacey Nicole

This dissertation combines archaeomagnetic and independent chronometric data from 240 archaeological features to develop a regional secular variation curve for the U.S. midcontinent. These data were obtained from features located between 31.5--40.5° N latitude and 82.5--93.5° W longitude that have been dated to between 60 and 10,700 cal BP. The archaeomagnetic samples were collected from 41 sites within this region over the past 35 years under the direction of four different researchers: Robert DuBois (University of Oklahoma), Daniel Wolfman (University of Arkansas and New Mexico State Museum), Wulf Gose (University of Texas at Austin), and myself. In this project, the data are initially smoothed through the moving windows method to form the first approximation of the curve. Outlier analyses and pairwise statistical comparisons are utilized to refine the smoothed curve, and the results are compared to other Holocene-aged secular variation records from North America. These analyses indicate that the final curve should be treated as three distinct segments with different precision and use recommendations. First, the 850--75 cal BP segment can be used to date archaeomagnetic sample from the project area with expected temporal precision of 100--200 years. Second, the 2528--850 cal BP segment can be used cautiously to date archaeomagnetic samples with an expected temporal precision of 200--300 years. Third, the 9755--4650 cal BP segment should be used for contextual dating purposes only, in that an undated sample can be put into a regional context through comparison with the segment's constituent samples. Finally, three archaeological problems are addressed through the archaeomagnetic data. First, archaeomagnetic data are used to resolve the temporal conflict between an eastern Tennessee structure's morphology and a much earlier radiocarbon date obtained for the structure. Then, archaeomagnetic data are used to address a number of internal chronology questions regarding three Powers phase sites in eastern Missouri. Finally, the sequencing of several protohistoric and historic sites in eastern Tennessee is examined through a series of archaeomagnetic data.

Towards photonic quantum simulation of ground states of frustrated Heisenberg spin systems

PubMed Central

Ma, Xiao-song; Dakić, Borivoje; Kropatschek, Sebastian; Naylor, William; Chan, Yang-hao; Gong, Zhe-xuan; Duan, Lu-ming; Zeilinger, Anton; Walther, Philip

2014-01-01

Photonic quantum simulators are promising candidates for providing insight into other small- to medium-sized quantum systems. Recent experiments have shown that photonic quantum systems have the advantage to exploit quantum interference for the quantum simulation of the ground state of Heisenberg spin systems. Here we experimentally characterize this quantum interference at a tuneable beam splitter and further investigate the measurement-induced interactions of a simulated four-spin system by comparing the entanglement dynamics using pairwise concurrence. We also study theoretically a four-site square lattice with next-nearest neighbor interactions and a six-site checkerboard lattice, which might be in reach of current technology. PMID:24394808

Deterministic Generation of All-Photonic Quantum Repeaters from Solid-State Emitters

NASA Astrophysics Data System (ADS)

Buterakos, Donovan; Barnes, Edwin; Economou, Sophia E.

2017-10-01

Quantum repeaters are nodes in a quantum communication network that allow reliable transmission of entanglement over large distances. It was recently shown that highly entangled photons in so-called graph states can be used for all-photonic quantum repeaters, which require substantially fewer resources compared to atomic-memory-based repeaters. However, standard approaches to building multiphoton entangled states through pairwise probabilistic entanglement generation severely limit the size of the state that can be created. Here, we present a protocol for the deterministic generation of large photonic repeater states using quantum emitters such as semiconductor quantum dots and defect centers in solids. We show that arbitrarily large repeater states can be generated using only one emitter coupled to a single qubit, potentially reducing the necessary number of photon sources by many orders of magnitude. Our protocol includes a built-in redundancy, which makes it resilient to photon loss.

Multistate and multihypothesis discrimination with open quantum systems

NASA Astrophysics Data System (ADS)

Kiilerich, Alexander Holm; Mølmer, Klaus

2018-05-01

We show how an upper bound for the ability to discriminate any number N of candidates for the Hamiltonian governing the evolution of an open quantum system may be calculated by numerically efficient means. Our method applies an effective master-equation analysis to evaluate the pairwise overlaps between candidate full states of the system and its environment pertaining to the Hamiltonians. These overlaps are then used to construct an N -dimensional representation of the states. The optimal positive-operator valued measure (POVM) and the corresponding probability of assigning a false hypothesis may subsequently be evaluated by phrasing optimal discrimination of multiple nonorthogonal quantum states as a semidefinite programming problem. We provide three realistic examples of multihypothesis testing with open quantum systems.

Equilibration and non-equilibrium steady states in PT-symmetric Toda lattice

NASA Astrophysics Data System (ADS)

Harter, Andrew; Joglekar, Yogesh; Saxena, Avadh

The Toda lattice is a classical discrete integrable model, describing a chain of particles that interact through an exponentially decaying, pairwise potential. It also supports soliton solutions. We consider the fate of this lattice in the presence of localized, spatially separated, balanced drag (loss) and drive (gain). Such systems with balanced gain and loss undergo a transition, the so called parity-time (PT) symmetry breaking transition, from a quasi-equilibrium state to a state that is far removed from equilibrium. We determine the threshold for such a transition in the presence of stochastic and deterministic driving, and study the robustness of our results in the presence of different boundary conditions. This work is supported by DMR-1054020.

Threesomes destabilise certain relationships: multispecies interactions between wood decay fungi in natural resources

PubMed Central

Savoury, Melanie; Toledo, Selin; Kingscott-Edmunds, James; Bettridge, Aimee; Waili, Nasra Al; Boddy, Lynne

2017-01-01

Abstract Understanding interspecific interactions is key to explaining and modelling community development and associated ecosystem function. Most interactions research has focused on pairwise combinations, overlooking the complexity of multispecies communities. This study investigated three-way interactions between saprotrophic fungi in wood and across soil, and indicated that pairwise combinations are often inaccurate predictors of the outcomes of multispecies competition in wood block interactions. This inconsistency was especially true of intransitive combinations, resulting in increased species coexistence within the resource. Furthermore, the addition of a third competitor frequently destabilised the otherwise consistent outcomes of pairwise combinations in wood blocks, which occasionally resulted in altered resource decomposition rates, depending on the relative decay abilities of the species involved. Conversely, interaction outcomes in soil microcosms were unaffected by the presence of a third combatant. Multispecies interactions promoted species diversity within natural resources, and made community dynamics less consistent than could be predicted from pairwise interaction studies. PMID:28175239

Ranking Highlights in Personal Videos by Analyzing Edited Videos.

PubMed

Sun, Min; Farhadi, Ali; Chen, Tseng-Hung; Seitz, Steve

2016-11-01

We present a fully automatic system for ranking domain-specific highlights in unconstrained personal videos by analyzing online edited videos. A novel latent linear ranking model is proposed to handle noisy training data harvested online. Specifically, given a targeted domain such as "surfing," our system mines the YouTube database to find pairs of raw and their corresponding edited videos. Leveraging the assumption that an edited video is more likely to contain highlights than the trimmed parts of the raw video, we obtain pair-wise ranking constraints to train our model. The learning task is challenging due to the amount of noise and variation in the mined data. Hence, a latent loss function is incorporated to mitigate the issues caused by the noise. We efficiently learn the latent model on a large number of videos (about 870 min in total) using a novel EM-like procedure. Our latent ranking model outperforms its classification counterpart and is fairly competitive compared with a fully supervised ranking system that requires labels from Amazon Mechanical Turk. We further show that a state-of-the-art audio feature mel-frequency cepstral coefficients is inferior to a state-of-the-art visual feature. By combining both audio-visual features, we obtain the best performance in dog activity, surfing, skating, and viral video domains. Finally, we show that impressive highlights can be detected without additional human supervision for seven domains (i.e., skating, surfing, skiing, gymnastics, parkour, dog activity, and viral video) in unconstrained personal videos.

A conditional Granger causality model approach for group analysis in functional MRI

PubMed Central

Zhou, Zhenyu; Wang, Xunheng; Klahr, Nelson J.; Liu, Wei; Arias, Diana; Liu, Hongzhi; von Deneen, Karen M.; Wen, Ying; Lu, Zuhong; Xu, Dongrong; Liu, Yijun

2011-01-01

Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed for identifying effective connectivity in the human brain with functional MR imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pairwise GCM has commonly been applied based on single voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of an fMRI data with GCM. To compare the effectiveness of our approach with traditional pairwise GCM models, we applied a well-established conditional GCM to pre-selected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis (ICA) of an fMRI dataset in the temporal domain. Datasets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM detected brain activation regions in the emotion related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state dataset, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network (DMN) that can be characterized as both afferent and efferent influences on the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive (MVAR) model can achieve greater accuracy in detecting network connectivity than the widely used pairwise GCM, and this group analysis methodology can be quite useful to extend the information obtainable in fMRI. PMID:21232892

Blazing Signature Filter: a library for fast pairwise similarity comparisons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Joon-Yong; Fujimoto, Grant M.; Wilson, Ryan

Identifying similarities between datasets is a fundamental task in data mining and has become an integral part of modern scientific investigation. Whether the task is to identify co-expressed genes in large-scale expression surveys or to predict combinations of gene knockouts which would elicit a similar phenotype, the underlying computational task is often a multi-dimensional similarity test. As datasets continue to grow, improvements to the efficiency, sensitivity or specificity of such computation will have broad impacts as it allows scientists to more completely explore the wealth of scientific data. A significant practical drawback of large-scale data mining is the vast majoritymore » of pairwise comparisons are unlikely to be relevant, meaning that they do not share a signature of interest. It is therefore essential to efficiently identify these unproductive comparisons as rapidly as possible and exclude them from more time-intensive similarity calculations. The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time. The algorithm transforms datasets into binary metrics, allowing it to utilize the computationally efficient bit operators and provide a coarse measure of similarity. As a result, the BSF can scale to high dimensionality and rapidly filter unproductive pairwise comparison. Two bioinformatics applications of the tool are presented to demonstrate the ability to scale to billions of pairwise comparisons and the usefulness of this approach.« less

Pairwise Maximum Entropy Models for Studying Large Biological Systems: When They Can Work and When They Can't

PubMed Central

Roudi, Yasser; Nirenberg, Sheila; Latham, Peter E.

2009-01-01

One of the most critical problems we face in the study of biological systems is building accurate statistical descriptions of them. This problem has been particularly challenging because biological systems typically contain large numbers of interacting elements, which precludes the use of standard brute force approaches. Recently, though, several groups have reported that there may be an alternate strategy. The reports show that reliable statistical models can be built without knowledge of all the interactions in a system; instead, pairwise interactions can suffice. These findings, however, are based on the analysis of small subsystems. Here, we ask whether the observations will generalize to systems of realistic size, that is, whether pairwise models will provide reliable descriptions of true biological systems. Our results show that, in most cases, they will not. The reason is that there is a crossover in the predictive power of pairwise models: If the size of the subsystem is below the crossover point, then the results have no predictive power for large systems. If the size is above the crossover point, then the results may have predictive power. This work thus provides a general framework for determining the extent to which pairwise models can be used to predict the behavior of large biological systems. Applied to neural data, the size of most systems studied so far is below the crossover point. PMID:19424487

Regulation of Intracellular Signaling Leading to Gene Expression in Lipopolysaccharide Stimulated Murine Macrophages

DTIC Science & Technology

1995-09-20

parentheses represent the lower and upper values defined by 1 SEM. The LSD test was used for pairwise mean comparisons. c,d,"Means are significantly...different at the 5% level of significance of the LSD test. 100 Table VI: Effect of Calyculin A on LPS-induced TNF and IFN Production Treatment Medium...transfer an antiviral state. Role of endogenous interferon. J. Immun . 139:1991. Gille. H. G., A. D. Sharrocks, and P. E. Shaw . 1992. Phosphorylation

Addressing the challenges of standalone multi-core simulations in molecular dynamics

NASA Astrophysics Data System (ADS)

Ocaya, R. O.; Terblans, J. J.

2017-07-01

Computational modelling in material science involves mathematical abstractions of force fields between particles with the aim to postulate, develop and understand materials by simulation. The aggregated pairwise interactions of the material's particles lead to a deduction of its macroscopic behaviours. For practically meaningful macroscopic scales, a large amount of data are generated, leading to vast execution times. Simulation times of hours, days or weeks for moderately sized problems are not uncommon. The reduction of simulation times, improved result accuracy and the associated software and hardware engineering challenges are the main motivations for many of the ongoing researches in the computational sciences. This contribution is concerned mainly with simulations that can be done on a "standalone" computer based on Message Passing Interfaces (MPI), parallel code running on hardware platforms with wide specifications, such as single/multi- processor, multi-core machines with minimal reconfiguration for upward scaling of computational power. The widely available, documented and standardized MPI library provides this functionality through the MPI_Comm_size (), MPI_Comm_rank () and MPI_Reduce () functions. A survey of the literature shows that relatively little is written with respect to the efficient extraction of the inherent computational power in a cluster. In this work, we discuss the main avenues available to tap into this extra power without compromising computational accuracy. We also present methods to overcome the high inertia encountered in single-node-based computational molecular dynamics. We begin by surveying the current state of the art and discuss what it takes to achieve parallelism, efficiency and enhanced computational accuracy through program threads and message passing interfaces. Several code illustrations are given. The pros and cons of writing raw code as opposed to using heuristic, third-party code are also discussed. The growing trend towards graphical processor units and virtual computing clouds for high-performance computing is also discussed. Finally, we present the comparative results of vacancy formation energy calculations using our own parallelized standalone code called Verlet-Stormer velocity (VSV) operating on 30,000 copper atoms. The code is based on the Sutton-Chen implementation of the Finnis-Sinclair pairwise embedded atom potential. A link to the code is also given.

Design, Implementation and Deployment of PAIRwise

ERIC Educational Resources Information Center

Knight, Allan; Almeroth, Kevin; Bimber, Bruce

2008-01-01

Increased access to the Internet has dramatically increased the sources from which students can deliberately or accidentally copy information. This article discusses our motivation to design, implement, and deploy an Internet based plagiarism detection system, called PAIRwise, to address this growing problem. We give details as to how we detect…

Exponential series approaches for nonparametric graphical models

NASA Astrophysics Data System (ADS)

Janofsky, Eric

Markov Random Fields (MRFs) or undirected graphical models are parsimonious representations of joint probability distributions. This thesis studies high-dimensional, continuous-valued pairwise Markov Random Fields. We are particularly interested in approximating pairwise densities whose logarithm belongs to a Sobolev space. For this problem we propose the method of exponential series which approximates the log density by a finite-dimensional exponential family with the number of sufficient statistics increasing with the sample size. We consider two approaches to estimating these models. The first is regularized maximum likelihood. This involves optimizing the sum of the log-likelihood of the data and a sparsity-inducing regularizer. We then propose a variational approximation to the likelihood based on tree-reweighted, nonparametric message passing. This approximation allows for upper bounds on risk estimates, leverages parallelization and is scalable to densities on hundreds of nodes. We show how the regularized variational MLE may be estimated using a proximal gradient algorithm. We then consider estimation using regularized score matching. This approach uses an alternative scoring rule to the log-likelihood, which obviates the need to compute the normalizing constant of the distribution. For general continuous-valued exponential families, we provide parameter and edge consistency results. As a special case we detail a new approach to sparse precision matrix estimation which has statistical performance competitive with the graphical lasso and computational performance competitive with the state-of-the-art glasso algorithm. We then describe results for model selection in the nonparametric pairwise model using exponential series. The regularized score matching problem is shown to be a convex program; we provide scalable algorithms based on consensus alternating direction method of multipliers (ADMM) and coordinate-wise descent. We use simulations to compare our method to others in the literature as well as the aforementioned TRW estimator.

River network architecture, genetic effective size and distributional patterns predict differences in genetic structure across species in a dryland stream fish community.

PubMed

Pilger, Tyler J; Gido, Keith B; Propst, David L; Whitney, James E; Turner, Thomas F

2017-05-01

Dendritic ecological network (DEN) architecture can be a strong predictor of spatial genetic patterns in theoretical and simulation studies. Yet, interspecific differences in dispersal capabilities and distribution within the network may equally affect species' genetic structuring. We characterized patterns of genetic variation from up to ten microsatellite loci for nine numerically dominant members of the upper Gila River fish community, New Mexico, USA. Using comparative landscape genetics, we evaluated the role of network architecture for structuring populations within species (pairwise F ST ) while explicitly accounting for intraspecific demographic influences on effective population size (N e ). Five species exhibited patterns of connectivity and/or genetic diversity gradients that were predicted by network structure. These species were generally considered to be small-bodied or habitat specialists. Spatial variation of N e was a strong predictor of pairwise F ST for two species, suggesting patterns of connectivity may also be influenced by genetic drift independent of network properties. Finally, two study species exhibited genetic patterns that were unexplained by network properties and appeared to be related to nonequilibrium processes. Properties of DENs shape community-wide genetic structure but effects are modified by intrinsic traits and nonequilibrium processes. Further theoretical development of the DEN framework should account for such cases. © 2017 John Wiley & Sons Ltd.

Evaluation of key driver categories influencing sustainable waste management development with the analytic hierarchy process (AHP): Serbia example.

PubMed

Tot, Bojana; Srđević, Bojan; Vujić, Bogdana; Russo, Mário Augusto Tavares; Vujić, Goran

2016-08-01

The problems of waste management have become increasingly complex in recent decades. The increasing amount of generated waste, adopted legislation in the field of waste management, administrative issues, economic impacts and social awareness are important drivers in achieving a sustainable waste management system. However, in practice, there are many other drivers that are often mutually in conflict. The purpose of this research is to define the precise driver and their corresponding sub-drivers, which are relevant for developing a waste management system and, on the basis of their importance, to determine which has the predominant influence on the slow development of a waste management system at the national and regional level, within the Republic of Serbia and similar countries of southeast Europe. This research presents two levels of decision making: the first is a pair-wise comparison of the drivers in relation to the goal and the second is a pair-wise comparison of the sub-drivers in relation to the driver and in relation to the goal. Results of performed analyses on the waste management drivers were integrated via the decision-making process supported by an analytic hierarchy process (AHP). The final results of this research shows that the Institutional-Administrative driver is the most important for developing a sustainable waste management system. © The Author(s) 2016.

Elastic K-means using posterior probability.

PubMed

Zheng, Aihua; Jiang, Bo; Li, Yan; Zhang, Xuehan; Ding, Chris

2017-01-01

The widely used K-means clustering is a hard clustering algorithm. Here we propose a Elastic K-means clustering model (EKM) using posterior probability with soft capability where each data point can belong to multiple clusters fractionally and show the benefit of proposed Elastic K-means. Furthermore, in many applications, besides vector attributes information, pairwise relations (graph information) are also available. Thus we integrate EKM with Normalized Cut graph clustering into a single clustering formulation. Finally, we provide several useful matrix inequalities which are useful for matrix formulations of learning models. Based on these results, we prove the correctness and the convergence of EKM algorithms. Experimental results on six benchmark datasets demonstrate the effectiveness of proposed EKM and its integrated model.

Patterns of text reuse in a scientific corpus

PubMed Central

Citron, Daniel T.; Ginsparg, Paul

2015-01-01

We consider the incidence of text “reuse” by researchers via a systematic pairwise comparison of the text content of all articles deposited to arXiv.org from 1991 to 2012. We measure the global frequencies of three classes of text reuse and measure how chronic text reuse is distributed among authors in the dataset. We infer a baseline for accepted practice, perhaps surprisingly permissive compared with other societal contexts, and a clearly delineated set of aberrant authors. We find a negative correlation between the amount of reused text in an article and its influence, as measured by subsequent citations. Finally, we consider the distribution of countries of origin of articles containing large amounts of reused text. PMID:25489072

Generation of Synthetic Spike Trains with Defined Pairwise Correlations

PubMed Central

Niebur, Ernst

2008-01-01

Recent technological advances as well as progress in theoretical understanding of neural systems have created a need for synthetic spike trains with controlled mean rate and pairwise cross-correlation. This report introduces and analyzes a novel algorithm for the generation of discretized spike trains with arbitrary mean rates and controlled cross correlation. Pairs of spike trains with any pairwise correlation can be generated, and higher-order correlations are compatible with common synaptic input. Relations between allowable mean rates and correlations within a population are discussed. The algorithm is highly efficient, its complexity increasing linearly with the number of spike trains generated and therefore inversely with the number of cross-correlated pairs. PMID:17521277

Diatomics-in-molecules description of the Rg-Hal2 rare gas-halogen van der Waals complexes with applications to He-Cl2

NASA Astrophysics Data System (ADS)

Grigorenko, B. L.; Nemukhin, A. V.; Buchachenko, A. A.; Stepanov, N. F.; Umanskii, S. Ya.

1997-03-01

The diatomics-in-molecules (DIM) technique is applied for a description of the low-lying states of the Rg-Hal2 van der Waals complexes correlating with the lowest states of constituent atoms Rg(1S)+Hal(2Pj)+Hal(2Pj). The important feature of this approach is the construction of polyatomic basis functions as products of the Hal2 diatomic eigenstates classified within the Hund "c" scheme and the atomic rare gas wave function. Necessary transformations to the other basis set representations are described, and finally all the matrix elements are expressed in terms of nonrelativistic adiabatic energies of Hal2 and Rg Hal fragments and spin-orbit splitting constant of the halogen atom. Our main concern is to test the DIM-based approximations of different levels taking the He-Cl2 system as an example. Namely, we have compared the results obtained within a hierarchy of approaches: (1) the simplest pairwise potential scheme as a far extreme of the DIM model, (2) the same as (1) but with the different components (Σ and Π) for He-Cl interaction, (3) the accurate DIM technique without spin-orbit terms, and (4) the highest level which takes into account all these contributions. The results have been compared to the other DIM like models as well. The shapes of two-dimensional potential surfaces for the ground (X) and excited (B) states of HeCl2, binding energies De with respect to He+Cl2, stretching and bending vibrational frequencies of the complex, binding energies D0, and spectral shifts for the B←X transition are discussed.

Prospects for inferring pairwise relationships with single nucleotide polymorphisms

Treesearch

Jeffery C. Glaubitz; O. Eugene, Jr. Rhodes; J. Andrew DeWoody

2003-01-01

An extraordinarily large number of single nucleotide polymorphisms (SNPs) are now available in humans as well as in other model organisms. Technological advancements may soon make it feasible to assay hundreds of SNPs in virtually any organism of interest. One potential application of SNPs is the determination of pairwise genetic relationships in populations without...

A new method of content based medical image retrieval and its applications to CT imaging sign retrieval.

PubMed

Ma, Ling; Liu, Xiabi; Gao, Yan; Zhao, Yanfeng; Zhao, Xinming; Zhou, Chunwu

2017-02-01

This paper proposes a new method of content based medical image retrieval through considering fused, context-sensitive similarity. Firstly, we fuse the semantic and visual similarities between the query image and each image in the database as their pairwise similarities. Then, we construct a weighted graph whose nodes represent the images and edges measure their pairwise similarities. By using the shortest path algorithm over the weighted graph, we obtain a new similarity measure, context-sensitive similarity measure, between the query image and each database image to complete the retrieval process. Actually, we use the fused pairwise similarity to narrow down the semantic gap for obtaining a more accurate pairwise similarity measure, and spread it on the intrinsic data manifold to achieve the context-sensitive similarity for a better retrieval performance. The proposed method has been evaluated on the retrieval of the Common CT Imaging Signs of Lung Diseases (CISLs) and achieved not only better retrieval results but also the satisfactory computation efficiency. Copyright © 2017 Elsevier Inc. All rights reserved.

Frequency-Dependent Selection: The High Potential for Permanent Genetic Variation in the Diallelic, Pairwise Interaction Model

PubMed Central

Asmussen, M. A.; Basnayake, E.

1990-01-01

A detailed analytic and numerical study is made of the potential for permanent genetic variation in frequency-dependent models based on pairwise interactions among genotypes at a single diallelic locus. The full equilibrium structure and qualitative gene-frequency dynamics are derived analytically for a symmetric model, in which pairwise fitnesses are chiefly determined by the genetic similarity of the individuals involved. This is supplemented by an extensive numerical investigation of the general model, the symmetric model, and nine other special cases. Together the results show that there is a high potential for permanent genetic diversity in the pairwise interaction model, and provide insight into the extent to which various forms of genotypic interactions enhance or reduce this potential. Technically, although two stable polymorphic equilibria are possible, the increased likelihood of maintaining both alleles, and the poor performance of protected polymorphism conditions as a measure of this likelihood, are primarily due to a greater variety and frequency of equilibrium patterns with one stable polymorphic equilibrium, in conjunction with a disproportionately large domain of attraction for stable internal equilibria. PMID:2341034

Ar(n)HF van der Waals clusters revisited: II. Energetics and HF vibrational frequency shifts from diffusion Monte Carlo calculations on additive and nonadditive potential-energy surfaces for n=1-12.

PubMed

Jiang, Hao; Xu, Minzhong; Hutson, Jeremy M; Bacić, Zlatko

2005-08-01

The ground-state energies and HF vibrational frequency shifts of Ar(n)HF clusters have been calculated on the nonadditive potential-energy surfaces (PESs) for n=2-7 and on the pairwise-additive PESs for the clusters with n=1-12, using the diffusion Monte Carlo (DMC) method. For n>3, the calculations have been performed for the lowest-energy isomer and several higher-lying isomers which are the closest in energy. They provide information about the isomer dependence of the HF redshift, and enable direct comparison with the experimental data recently obtained in helium nanodroplets. The agreement between theory and experiment is excellent, in particular, for the nonadditive DMC redshifts. The relative, incremental redshifts are reproduced accurately even at the lower level of theory, i.e., the DMC and quantum five-dimensional (rigid Ar(n)) calculations on the pairwise-additive PESs. The nonadditive interactions make a significant contribution to the frequency shift, on the order of 10%-12%, and have to be included in the PESs in order for the theory to yield accurate magnitude of the HF redshift. The energy gaps between the DMC ground states of the cluster isomers are very different from the energy separation of their respective minima on the PES, due to the considerable variations in the intermolecular zero-point energy of different Ar(n)HF isomers.

Consistency-based rectification of nonrigid registrations

PubMed Central

Gass, Tobias; Székely, Gábor; Goksel, Orcun

2015-01-01

Abstract. We present a technique to rectify nonrigid registrations by improving their group-wise consistency, which is a widely used unsupervised measure to assess pair-wise registration quality. While pair-wise registration methods cannot guarantee any group-wise consistency, group-wise approaches typically enforce perfect consistency by registering all images to a common reference. However, errors in individual registrations to the reference then propagate, distorting the mean and accumulating in the pair-wise registrations inferred via the reference. Furthermore, the assumption that perfect correspondences exist is not always true, e.g., for interpatient registration. The proposed consistency-based registration rectification (CBRR) method addresses these issues by minimizing the group-wise inconsistency of all pair-wise registrations using a regularized least-squares algorithm. The regularization controls the adherence to the original registration, which is additionally weighted by the local postregistration similarity. This allows CBRR to adaptively improve consistency while locally preserving accurate pair-wise registrations. We show that the resulting registrations are not only more consistent, but also have lower average transformation error when compared to known transformations in simulated data. On clinical data, we show improvements of up to 50% target registration error in breathing motion estimation from four-dimensional MRI and improvements in atlas-based segmentation quality of up to 65% in terms of mean surface distance in three-dimensional (3-D) CT. Such improvement was observed consistently using different registration algorithms, dimensionality (two-dimensional/3-D), and modalities (MRI/CT). PMID:26158083

Crystal genes in a marginal glass-forming system of Ni 50Zr 50

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wen, T. Q.; Tang, L.; Sun, Y.

Glass-forming motifs with B2 traits are found. A perfect Ni-centered B33 motif deteriorates the glass-forming ability of Ni 50Zr 50. The marginal glass-forming ability (GFA) of binary Ni-Zr system is an issue to be explained considering the numerous bulk metallic glasses (BMGs) found in the Cu-Zr system. Using molecular dynamics, the structures and dynamics of Ni 50Zr 50 metallic liquid and glass are investigated at the atomistic level. To achieve a well-relaxed glassy sample, sub-T g annealing method is applied and the final sample is closer to the experiments than the models prepared by continuous cooling. With the state-of-the-art structuralmore » analysis tools such as cluster alignment and pair-wise alignment methods, two glass-forming motifs with some mixed traits of the metastable B2 crystalline phase and the crystalline Ni-centered B33 motif are found to be dominant in the undercooled liquid and glass samples. A new chemical order characterization on each short-range order (SRO) structure is accomplished based on the cluster alignment method. The significant amount of the crystalline motif and the few icosahedra in the glassy sample deteriorate the GFA.« less

Time-Aware Service Ranking Prediction in the Internet of Things Environment

PubMed Central

Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

2017-01-01

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets. PMID:28448451

Time-Aware Service Ranking Prediction in the Internet of Things Environment.

PubMed

Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

2017-04-27

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

Crystal genes in a marginal glass-forming system of Ni 50Zr 50

DOE PAGES

Wen, T. Q.; Tang, L.; Sun, Y.; ...

2017-10-17

Glass-forming motifs with B2 traits are found. A perfect Ni-centered B33 motif deteriorates the glass-forming ability of Ni 50Zr 50. The marginal glass-forming ability (GFA) of binary Ni-Zr system is an issue to be explained considering the numerous bulk metallic glasses (BMGs) found in the Cu-Zr system. Using molecular dynamics, the structures and dynamics of Ni 50Zr 50 metallic liquid and glass are investigated at the atomistic level. To achieve a well-relaxed glassy sample, sub-T g annealing method is applied and the final sample is closer to the experiments than the models prepared by continuous cooling. With the state-of-the-art structuralmore » analysis tools such as cluster alignment and pair-wise alignment methods, two glass-forming motifs with some mixed traits of the metastable B2 crystalline phase and the crystalline Ni-centered B33 motif are found to be dominant in the undercooled liquid and glass samples. A new chemical order characterization on each short-range order (SRO) structure is accomplished based on the cluster alignment method. The significant amount of the crystalline motif and the few icosahedra in the glassy sample deteriorate the GFA.« less

The effect of design modifications to the typographical layout of the New York State elementary science learning standards on user preference and process time

NASA Astrophysics Data System (ADS)

Arnold, Jeffery E.

The purpose of this study was to determine the effect of four different design layouts of the New York State elementary science learning standards on user processing time and preference. Three newly developed layouts contained the same information as the standards core curriculum. In this study, the layout of the core guide is referred to as Book. The layouts of the new documents are referred to as Chart, Map, and Tabloid based on the format used to convey content hierarchy information. Most notably, all the new layouts feature larger page sizes, color, page tabs, and an icon based navigation system (IBNS). A convenience sample of 48 New York State educators representing three educator types (16 pre-service teachers, 16 in-service teachers, and 16 administrators) participated in the study. After completing timed tasks accurately, participants scored each layout based on preference. Educator type and layout were the independent variables, and process time and user preference were the dependent variables. A two-factor experimental design with Educator Type as the between variable and with repeated measures on Layout, the within variable, showed a significant difference in process time for Educator Type and Layout. The main effect for Educator Type (F(2, 45) = 8.03, p <.001) was significant with an observed power of .94, and an effect size of .26. The pair-wise comparisons for process time showed that pre-service teachers (p = .02) and administrators (p =.009) completed the assigned tasks more quickly when compared to in-service teachers. The main effect for Layout (F(3, 135) = 4.47, p =.01) was also significant with an observed power of .80, and an effect size of .09. Pair-wise comparisons showed that the newly developed Chart (p = .019) and Map (p = .032) layouts reduced overall process time when compared to the existing state learning standards (Book). The Layout X Educator type interaction was not significant. The same two-factor experimental design on preference, showed the main effect for Layout (F(3, 135) = 28.43, p =.001) was significant. The observed power was 1.0, with an effect size of .39. Pair-wise comparisons for preference scores showed that the Chart (p = .001), Map (p = .001), and Tabloid (p = .001) were preferred over the Book layout. The Layout Type X Educator Type interaction and the main effect for Educator Type were not significant. This study provides evidence that the newly developed design layouts improve usability (as measured by process time and preference scores) of the New York State elementary science learning standard documents. Features in the new layout design, such as the IBNS, may provide a foundation for a visual language and aid users in navigating standard documents across grade level and subject areas. Implications for the next generation of standard documents are presented.

Quantum-assisted learning of graphical models with arbitrary pairwise connectivity

NASA Astrophysics Data System (ADS)

Realpe-Gómez, John; Benedetti, Marcello; Biswas, Rupak; Perdomo-Ortiz, Alejandro

Mainstream machine learning techniques rely heavily on sampling from generally intractable probability distributions. There is increasing interest in the potential advantages of using quantum computing technologies as sampling engines to speedup these tasks. However, some pressing challenges in state-of-the-art quantum annealers have to be overcome before we can assess their actual performance. The sparse connectivity, resulting from the local interaction between quantum bits in physical hardware implementations, is considered the most severe limitation to the quality of constructing powerful machine learning models. Here we show how to surpass this `curse of limited connectivity' bottleneck and illustrate our findings by training probabilistic generative models with arbitrary pairwise connectivity on a real dataset of handwritten digits and two synthetic datasets in experiments with up to 940 quantum bits. Our model can be trained in quantum hardware without full knowledge of the effective parameters specifying the corresponding Boltzmann-like distribution. Therefore, the need to infer the effective temperature at each iteration is avoided, speeding up learning, and the effect of noise in the control parameters is mitigated, improving accuracy. This work was supported in part by NASA, AFRL, ODNI, and IARPA.

M-Isomap: Orthogonal Constrained Marginal Isomap for Nonlinear Dimensionality Reduction.

PubMed

Zhang, Zhao; Chow, Tommy W S; Zhao, Mingbo

2013-02-01

Isomap is a well-known nonlinear dimensionality reduction (DR) method, aiming at preserving geodesic distances of all similarity pairs for delivering highly nonlinear manifolds. Isomap is efficient in visualizing synthetic data sets, but it usually delivers unsatisfactory results in benchmark cases. This paper incorporates the pairwise constraints into Isomap and proposes a marginal Isomap (M-Isomap) for manifold learning. The pairwise Cannot-Link and Must-Link constraints are used to specify the types of neighborhoods. M-Isomap computes the shortest path distances over constrained neighborhood graphs and guides the nonlinear DR through separating the interclass neighbors. As a result, large margins between both interand intraclass clusters are delivered and enhanced compactness of intracluster points is achieved at the same time. The validity of M-Isomap is examined by extensive simulations over synthetic, University of California, Irvine, and benchmark real Olivetti Research Library, YALE, and CMU Pose, Illumination, and Expression databases. The data visualization and clustering power of M-Isomap are compared with those of six related DR methods. The visualization results show that M-Isomap is able to deliver more separate clusters. Clustering evaluations also demonstrate that M-Isomap delivers comparable or even better results than some state-of-the-art DR algorithms.

Evaluation of criteria for sustainability of community-based rural homestay programs via a modified pairwise comparison method

NASA Astrophysics Data System (ADS)

Ramli, Rohaini; Kasim, Maznah Mat; Ramli, Razamin; Kayat, Kalsom; Razak, Rafidah Abd

2014-12-01

Ministry of Tourism and Culture Malaysia has long introduced homestay programs across the country to enhance the quality of life of people, especially those living in rural areas. This type of program is classified as a community-based tourism (CBT) as it is expected to economically improve livelihood through cultural and community associated activities. It is the aspiration of the ministry to see that the income imbalance between people in the rural and urban areas is reduced, thus would contribute towards creating more developed states of Malaysia. Since 1970s, there are 154 homestay programs registered with the ministry. However, the performance and sustainability of the programs are still not satisfying. There are only a number of homestay programs that perform well and able to sustain. Thus, the aim of this paper is to identify relevant criteria contributing to the sustainability of a homestay program. The criteria are evaluated for their levels of importance via the use of a modified pairwise method and analyzed for other potentials. The findings will help the homestay operators to focus on the necessary criteria and thus, effectively perform as the CBT business initiative.

Searching for Collective Behavior in a Large Network of Sensory Neurons

PubMed Central

Tkačik, Gašper; Marre, Olivier; Amodei, Dario; Schneidman, Elad; Bialek, William; Berry, Michael J.

2014-01-01

Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system; for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such “K-pairwise” models—being systematic extensions of the previously used pairwise Ising models—provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1) estimating its entropy, which constrains the population's capacity to represent visual information; 2) classifying activity patterns into a small set of metastable collective modes; 3) showing that the neural codeword ensembles are extremely inhomogenous; 4) demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction. PMID:24391485

Statistical Mechanics of US Supreme Court

NASA Astrophysics Data System (ADS)

Lee, Edward; Broedersz, Chase; Bialek, William; Biophysics Theory Group Team

2014-03-01

We build simple models for the distribution of voting patterns in a group, using the Supreme Court of the United States as an example. The least structured, or maximum entropy, model that is consistent with the observed pairwise correlations among justices' votes is equivalent to an Ising spin glass. While all correlations (perhaps surprisingly) are positive, the effective pairwise interactions in the spin glass model have both signs, recovering some of our intuition that justices on opposite sides of the ideological spectrum should have a negative influence on one another. Despite the competing interactions, a strong tendency toward unanimity emerges from the model, and this agrees quantitatively with the data. The model shows that voting patterns are organized in a relatively simple ``energy landscape,'' correctly predicts the extent to which each justice is correlated with the majority, and gives us a measure of the influence that justices exert on one another. These results suggest that simple models, grounded in statistical physics, can capture essential features of collective decision making quantitatively, even in a complex political context. Funded by National Science Foundation Grants PHY-0957573 and CCF-0939370, WM Keck Foundation, Lewis-Sigler Fellowship, Burroughs Wellcome Fund, and Winston Foundation.

Document Level Assessment of Document Retrieval Systems in a Pairwise System Evaluation

ERIC Educational Resources Information Center

Rajagopal, Prabha; Ravana, Sri Devi

2017-01-01

Introduction: The use of averaged topic-level scores can result in the loss of valuable data and can cause misinterpretation of the effectiveness of system performance. This study aims to use the scores of each document to evaluate document retrieval systems in a pairwise system evaluation. Method: The chosen evaluation metrics are document-level…

Pairwise Multiple Comparisons in Single Group Repeated Measures Analysis.

ERIC Educational Resources Information Center

Barcikowski, Robert S.; Elliott, Ronald S.

Research was conducted to provide educational researchers with a choice of pairwise multiple comparison procedures (P-MCPs) to use with single group repeated measures designs. The following were studied through two Monte Carlo (MC) simulations: (1) The T procedure of J. W. Tukey (1953); (2) a modification of Tukey's T (G. Keppel, 1973); (3) the…

Impaired Discrimination Learning in Mice Lacking the NMDA Receptor NR2A Subunit

ERIC Educational Resources Information Center

Brigman, Jonathan L.; Feyder, Michael; Saksida, Lisa M.; Bussey, Timothy J.; Mishina, Masayoshi; Holmes, Andrew

2008-01-01

N-Methyl-D-aspartate receptors (NMDARs) mediate certain forms of synaptic plasticity and learning. We used a touchscreen system to assess NR2A subunit knockout mice (KO) for (1) pairwise visual discrimination and reversal learning and (2) acquisition and extinction of an instrumental response requiring no pairwise discrimination. NR2A KO mice…

Pairwise-additive hydrophobic effect for alkanes in water

PubMed Central

Wu, Jianzhong; Prausnitz, John M.

2008-01-01

Pairwise additivity of the hydrophobic effect is indicated by reliable experimental Henry's constants for a large number of linear and branched low-molecular-weight alkanes in water. Pairwise additivity suggests that the hydrophobic effect is primarily a local phenomenon and that the hydrophobic interaction may be represented by a semiempirical force field. By representing the hydrophobic potential between two methane molecules as a linear function of the overlap volume of the hydration layers, we find that the contact value of the hydrophobic potential (−0.72 kcal/mol) is smaller than that from quantum mechanics simulations (−2.8 kcal/mol) but is close to that from classical molecular dynamics (−0.5∼−0.9 kcal/mol). PMID:18599448

A comparison of scoring weights for the EuroQol derived from patients and the general public.

PubMed

Polsky, D; Willke, R J; Scott, K; Schulman, K A; Glick, H A

2001-01-01

General health state classification systems, such as the EuroQol instrument, have been developed to improve the systematic measurement and comparability of health state preferences. In this paper we generate valuations for EuroQol health states using responses to this instrument's visual analogue scale made by patients enrolled in a randomized clinical trial evaluating tirilazad mesylate, a new drug used to treat subarachnoid haemorrhage. We then compare these valuations derived from patients with published valuations derived from responses made by a sample from the general public. The data were derived from two sources: (1) responses to the EuroQol instrument from 649 patients 3 months after enrollment in the clinical trial, and (2) from a published study reporting a scoring rule for the EuroQol instrument that was based upon responses made by the general public. We used a linear regression model to develop an additive scoring rule. This rule enables direct valuation of all 243 EuroQol health states using patients' scores for their own health states elicited using a visual analogue scale. We then compared predicted scores generated using our scoring rule with predicted scores derived from a sample from the general public. The predicted scores derived using the additive scoring rules met convergent validity criteria and explained a substantial amount of the variation in visual analogue scale scores (R(2)=0.57). In the pairwise comparison of the predicted scores derived from the study sample with those derived from the general public, we found that the former set of scores were higher for 223 of the 243 states. Despite the low level of correspondence in the pairwise comparison, the overall correlation between the two sets of scores was 87%. The model presented in this paper demonstrated that scoring weights for the EuroQol instrument can be derived directly from patient responses from a clinical trial and that these weights can explain a substantial amount of variation in health valuations. Scoring weights based on patient responses are significantly higher than those derived from the general public. Further research is required to understand the source of these differences. Copyright 2001 John Wiley & Sons, Ltd.

A configuration space of homologous proteins conserving mutual information and allowing a phylogeny inference based on pair-wise Z-score probabilities.

PubMed

Bastien, Olivier; Ortet, Philippe; Roy, Sylvaine; Maréchal, Eric

2005-03-10

Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topology. We have sought a representation of homologous proteins that would conserve the information of pair-wise sequence alignments, respect probabilistic properties of Z-scores (Monte Carlo methods applied to pair-wise comparisons) and be the basis for a novel method of consistent and stable phylogenetic reconstruction. We have built up a spatial representation of protein sequences using concepts from particle physics (configuration space) and respecting a frame of constraints deduced from pair-wise alignment score properties in information theory. The obtained configuration space of homologous proteins (CSHP) allows the representation of real and shuffled sequences, and thereupon an expression of the TULIP theorem for Z-score probabilities. Based on the CSHP, we propose a phylogeny reconstruction using Z-scores. Deduced trees, called TULIP trees, are consistent with multiple-alignment based trees. Furthermore, the TULIP tree reconstruction method provides a solution for some previously reported incongruent results, such as the apicomplexan enolase phylogeny. The CSHP is a unified model that conserves mutual information between proteins in the way physical models conserve energy. Applications include the reconstruction of evolutionary consistent and robust trees, the topology of which is based on a spatial representation that is not reordered after addition or removal of sequences. The CSHP and its assigned phylogenetic topology, provide a powerful and easily updated representation for massive pair-wise genome comparisons based on Z-score computations.

Simulations of the pairwise kinematic Sunyaev-Zel'dovich signal

DOE PAGES

Flender, Samuel; Bleem, Lindsey; Finkel, Hal; ...

2016-05-26

The pairwise kinematic Sunyaev–Zel'dovich (kSZ) signal from galaxy clusters is a probe of their line of sight momenta, and thus a potentially valuable source of cosmological information. In addition to the momenta, the amplitude of the measured signal depends on the properties of the intracluster gas and observational limitations such as errors in determining cluster centers and redshifts. In this work, we simulate the pairwise kSZ signal of clusters atmore » $$z\\lt 1$$, using the output from a cosmological N-body simulation and including the properties of the intracluster gas via a model that can be varied in post-processing. We find that modifications to the gas profile due to star formation and feedback reduce the pairwise kSZ amplitude of clusters by $$\\sim 50\\%$$, relative to the naive "gas traces mass" assumption. We demonstrate that miscentering can reduce the overall amplitude of the pairwise kSZ signal by up to 10%, while redshift errors can lead to an almost complete suppression of the signal at small separations. We confirm that a high-significance detection is expected from the combination of data from current generation, high-resolution cosmic microwave background experiments, such as the South Pole Telescope, and cluster samples from optical photometric surveys, such as the Dark Energy Survey. As a result, we forecast that future experiments such as Advanced ACTPol in conjunction with data from the Dark Energy Spectroscopic Instrument will yield detection significances of at least $$20\\sigma $$, and up to $$57\\sigma $$ in an optimistic scenario.« less

Modularity, pollination systems, and interaction turnover in plant-pollinator networks across space.

PubMed

Carstensen, Daniel W; Sabatino, Malena; Morellato, Leonor Patricia C

2016-05-01

Mutualistic interaction networks have been shown to be structurally conserved over space and time while pairwise interactions show high variability. In such networks, modularity is the division of species into compartments, or modules, where species within modules share more interactions with each other than they do with species from other modules. Such a modular structure is common in mutualistic networks and several evolutionary and ecological mechanisms have been proposed as underlying drivers. One prominent explanation is the existence of pollination syndromes where flowers tend to attract certain pollinators as determined by a set of traits. We investigate the modularity of seven community level plant-pollinator networks sampled in rupestrian grasslands, or campos rupestres, in SE Brazil. Defining pollination systems as corresponding groups of flower syndromes and pollinator functional groups, we test the two hypotheses that (1) interacting species from the same pollination system are more often assigned to the same module than interacting species from different pollination systems and; that (2) interactions between species from the same pollination system are more consistent across space than interactions between species from different pollination systems. Specifically we ask (1) whether networks are consistently modular across space; (2) whether interactions among species of the same pollination system occur more often inside modules, compared to interactions among species of different pollination systems, and finally; (3) whether the spatial variation in interaction identity, i.e., spatial interaction rewiring, is affected by trait complementarity among species as indicated by pollination systems. We confirm that networks are consistently modular across space and that interactions within pollination systems principally occur inside modules. Despite a strong tendency, we did not find a significant effect of pollination systems on the spatial consistency of pairwise interactions. These results indicate that the spatial rewiring of interactions could be constrained by pollination systems, resulting in conserved network structures in spite of high variation in pairwise interactions. Our findings suggest a relevant role of pollination systems in structuring plant-pollinator networks and we argue that structural patterns at the sub-network level can help us to fully understand how and why interactions vary across space and time.

Classification of forest-based ecotourism areas in Pocahontas County of West Virginia using GIS and pairwise comparison method

Treesearch

Ishwar Dhami; Jinyang. Deng

2012-01-01

Many previous studies have examined ecotourism primarily from the perspective of tourists while largely ignoring ecotourism destinations. This study used geographical information system (GIS) and pairwise comparison to identify forest-based ecotourism areas in Pocahontas County, West Virginia. The study adopted the criteria and scores developed by Boyd and Butler (1994...

Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models

ERIC Educational Resources Information Center

Pavlik, Philip I. Jr.; Cen, Hao; Koedinger, Kenneth R.

2009-01-01

This paper describes a novel method to create a quantitative model of an educational content domain of related practice item-types using learning curves. By using a pairwise test to search for the relationships between learning curves for these item-types, we show how the test results in a set of pairwise transfer relationships that can be…

Macrobenthic assemblages of the Changjiang River estuary (Yangtze River, China) and adjacent continental shelf relative to mild summer hypoxia

NASA Astrophysics Data System (ADS)

Liao, Yibo; Shou, Lu; Tang, Yanbin; Zeng, Jiangning; Gao, Aigen; Chen, Quanzhen; Yan, Xiaojun

2017-05-01

To assess the effects of hypoxia, macrobenthic communities along an estuarine gradient of the Changjiang estuary and adjacent continental shelf were analyzed. This revealed spatial variations in the communities and relationships with environmental variables during periods of reduced dissolved oxygen (DO) concentration in summer. Statistical analyses revealed significant differences in macrobenthic community composition among the three zones: estuarine zone (EZ), mildly hypoxic zone (MHZ) in the continental shelf, and normoxic zone (NZ) in the continental shelf (Global R =0.206, P =0.002). Pairwise tests showed that the macrobenthic community composition of the EZ was significantly different from the MHZ (pairwise test R =0.305, P =0.001) and the NZ (pairwise test R =0.259, P =0.001). There was no significant difference in macrobenthic communities between the MHZ and the NZ (pairwise test R =0.062, P =0.114). The taxa included small and typically opportunistic polychaetes, which made the greatest contribution to the dissimilarity between the zones. The effects of mild hypoxia on the macrobenthic communities are a result not only of reduced DO concentration but also of differences in environmental variables such as temperature, salinity, and nutrient concentrations caused by stratification.

From pairwise to group interactions in games of cyclic dominance.

PubMed

Szolnoki, Attila; Vukov, Jeromos; Perc, Matjaž

2014-06-01

We study the rock-paper-scissors game in structured populations, where the invasion rates determine individual payoffs that govern the process of strategy change. The traditional version of the game is recovered if the payoffs for each potential invasion stem from a single pairwise interaction. However, the transformation of invasion rates to payoffs also allows the usage of larger interaction ranges. In addition to the traditional pairwise interaction, we therefore consider simultaneous interactions with all nearest neighbors, as well as with all nearest and next-nearest neighbors, thus effectively going from single pair to group interactions in games of cyclic dominance. We show that differences in the interaction range affect not only the stationary fractions of strategies but also their relations of dominance. The transition from pairwise to group interactions can thus decelerate and even revert the direction of the invasion between the competing strategies. Like in evolutionary social dilemmas, in games of cyclic dominance, too, the indirect multipoint interactions that are due to group interactions hence play a pivotal role. Our results indicate that, in addition to the invasion rates, the interaction range is at least as important for the maintenance of biodiversity among cyclically competing strategies.

Detection of the kinematic Sunyaev–Zel'dovich effect with DES Year 1 and SPT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soergel, B.; Flender, S.; Story, K. T.

Here, we detect the kinematic Sunyaev-Zel'dovich (kSZ) effect with a statistical significance ofmore » $$4.2 \\sigma$$ by combining a cluster catalogue derived from the first year data of the Dark Energy Survey (DES) with CMB temperature maps from the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) Survey. This measurement is performed with a differential statistic that isolates the pairwise kSZ signal, providing the first detection of the large-scale, pairwise motion of clusters using redshifts derived from photometric data. By fitting the pairwise kSZ signal to a theoretical template we measure the average central optical depth of the cluster sample, $$\\bar{\\tau}_e = (3.75 \\pm 0.89)\\cdot 10^{-3}$$. We compare the extracted signal to realistic simulations and find good agreement with respect to the signal-to-noise, the constraint on $$\\bar{\\tau}_e$$, and the corresponding gas fraction. High-precision measurements of the pairwise kSZ signal with future data will be able to place constraints on the baryonic physics of galaxy clusters, and could be used to probe gravity on scales $$ \\gtrsim 100$$ Mpc.« less

Detection of the kinematic Sunyaev–Zel'dovich effect with DES Year 1 and SPT

DOE PAGES

Soergel, B.; Flender, S.; Story, K. T.; ...

2016-06-17

Here, we detect the kinematic Sunyaev-Zel'dovich (kSZ) effect with a statistical significance ofmore » $$4.2 \\sigma$$ by combining a cluster catalogue derived from the first year data of the Dark Energy Survey (DES) with CMB temperature maps from the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) Survey. This measurement is performed with a differential statistic that isolates the pairwise kSZ signal, providing the first detection of the large-scale, pairwise motion of clusters using redshifts derived from photometric data. By fitting the pairwise kSZ signal to a theoretical template we measure the average central optical depth of the cluster sample, $$\\bar{\\tau}_e = (3.75 \\pm 0.89)\\cdot 10^{-3}$$. We compare the extracted signal to realistic simulations and find good agreement with respect to the signal-to-noise, the constraint on $$\\bar{\\tau}_e$$, and the corresponding gas fraction. High-precision measurements of the pairwise kSZ signal with future data will be able to place constraints on the baryonic physics of galaxy clusters, and could be used to probe gravity on scales $$ \\gtrsim 100$$ Mpc.« less

State-Based Implicit Coordination and Applications

NASA Technical Reports Server (NTRS)

Narkawicz, Anthony J.; Munoz, Cesar A.

2011-01-01

In air traffic management, pairwise coordination is the ability to achieve separation requirements when conflicting aircraft simultaneously maneuver to solve a conflict. Resolution algorithms are implicitly coordinated if they provide coordinated resolution maneuvers to conflicting aircraft when only surveillance data, e.g., position and velocity vectors, is periodically broadcast by the aircraft. This paper proposes an abstract framework for reasoning about state-based implicit coordination. The framework consists of a formalized mathematical development that enables and simplifies the design and verification of implicitly coordinated state-based resolution algorithms. The use of the framework is illustrated with several examples of algorithms and formal proofs of their coordination properties. The work presented here supports the safety case for a distributed self-separation air traffic management concept where different aircraft may use different conflict resolution algorithms and be assured that separation will be maintained.

Upper bounds on the error probabilities and asymptotic error exponents in quantum multiple state discrimination

DOE Office of Scientific and Technical Information (OSTI.GOV)

Audenaert, Koenraad M. R., E-mail: koenraad.audenaert@rhul.ac.uk; Department of Physics and Astronomy, University of Ghent, S9, Krijgslaan 281, B-9000 Ghent; Mosonyi, Milán, E-mail: milan.mosonyi@gmail.com

2014-10-01

We consider the multiple hypothesis testing problem for symmetric quantum state discrimination between r given states σ₁, …, σ{sub r}. By splitting up the overall test into multiple binary tests in various ways we obtain a number of upper bounds on the optimal error probability in terms of the binary error probabilities. These upper bounds allow us to deduce various bounds on the asymptotic error rate, for which it has been hypothesized that it is given by the multi-hypothesis quantum Chernoff bound (or Chernoff divergence) C(σ₁, …, σ{sub r}), as recently introduced by Nussbaum and Szkoła in analogy with Salikhov'smore » classical multi-hypothesis Chernoff bound. This quantity is defined as the minimum of the pairwise binary Chernoff divergences min{sub j« less

Elastic K-means using posterior probability

PubMed Central

Zheng, Aihua; Jiang, Bo; Li, Yan; Zhang, Xuehan; Ding, Chris

2017-01-01

The widely used K-means clustering is a hard clustering algorithm. Here we propose a Elastic K-means clustering model (EKM) using posterior probability with soft capability where each data point can belong to multiple clusters fractionally and show the benefit of proposed Elastic K-means. Furthermore, in many applications, besides vector attributes information, pairwise relations (graph information) are also available. Thus we integrate EKM with Normalized Cut graph clustering into a single clustering formulation. Finally, we provide several useful matrix inequalities which are useful for matrix formulations of learning models. Based on these results, we prove the correctness and the convergence of EKM algorithms. Experimental results on six benchmark datasets demonstrate the effectiveness of proposed EKM and its integrated model. PMID:29240756

Development and characterization of fast-dissolving tablet formulations of glyburide based on solid self-microemulsifying systems.

PubMed

Cirri, Marzia; Roghi, Alessandra; Valleri, Maurizio; Mura, Paola

2016-07-01

The aim of this work was to develop effective fast-dissolving tablet formulations of glyburide, endowed with improved dissolution and technological properties, investigating the actual effectiveness of the Solid-Self MicroEmulsifying Drug Delivery System (S-SMEDDS) approach. An initial screening aimed to determine the solubility of the drug in different oils, Surfactants and CoSurfactants allowed the selection of the most suitable components for liquid SMEDDS, whose relative amounts were defined by the construction of pseudo-ternary phase diagrams. The selected liquid SMEDDS formulations (Capyol 90 as oil, Tween 20 as Surfactant and Glycofurol or Transcutol as CoSurfactant) were converted into Solid-SMEDDS, by adsorbing them onto Neusilin (1:1 and 1:0.8w/w S-SMEDDS:carrier), and fully characterized in terms of solid state (DSC and X-ray powder diffraction), morphological (ESEM) and dissolution properties, particle size and reconstitution ability. Finally, the 1:1 S-SMEDDS containing Glycofurol as CoSurfactant, showing the best performance, was selected to prepare two final tablet formulations. The ratio test (t10 min ratio and DE60 ratio) and pair-wise procedures (difference (f1) and similarity (f2) factors) highlighted the similarity of the new developed tablets and the marked difference between their drug dissolution profiles and those of formulations based on the micronized drug. The S-SMEDDS approach allowed to develop fast-dissolving tablets of glyburide, endowed with good technological properties and able to achieve the complete drug dissolution in a time ranging from 10 to 15min, depending on the formulation composition. Copyright © 2016 Elsevier B.V. All rights reserved.

Evolution of pairwise entanglement in a coupled n-body system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pineda, Carlos; Centro de Ciencias Fisicas, University of Mexico; Seligman, Thomas H.

2006-01-15

We study the exact evolution of two noninteracting qubits, initially in a Bell state, in the presence of an environment, modeled by a kicked Ising spin chain. Dynamics of this model range from integrable to chaotic and we can handle numerics for a large number of qubits. We find that the entanglement (as measured by concurrence) of the two qubits has a close relation to the purity of the pair, and closely follows an analytic relation derived for Werner states. As a collateral result we find that an integrable environment causes quadratic decay of concurrence as well as of purity,more » while a chaotic environment causes linear decay. Both quantities display recurrences in an integrable environment.« less

Retinal image mosaicing using the radial distortion correction model

NASA Astrophysics Data System (ADS)

Lee, Sangyeol; Abràmoff, Michael D.; Reinhardt, Joseph M.

2008-03-01

Fundus camera imaging can be used to examine the retina to detect disorders. Similar to looking through a small keyhole into a large room, imaging the fundus with an ophthalmologic camera allows only a limited view at a time. Thus, the generation of a retinal montage using multiple images has the potential to increase diagnostic accuracy by providing larger field of view. A method of mosaicing multiple retinal images using the radial distortion correction (RADIC) model is proposed in this paper. Our method determines the inter-image connectivity by detecting feature correspondences. The connectivity information is converted to a tree structure that describes the spatial relationships between the reference and target images for pairwise registration. The montage is generated by cascading pairwise registration scheme starting from the anchor image downward through the connectivity tree hierarchy. The RADIC model corrects the radial distortion that is due to the spherical-to-planar projection during retinal imaging. Therefore, after radial distortion correction, individual images can be properly mapped onto a montage space by a linear geometric transformation, e.g. affine transform. Compared to the most existing montaging methods, our method is unique in that only a single registration per image is required because of the distortion correction property of RADIC model. As a final step, distance-weighted intensity blending is employed to correct the inter-image differences in illumination encountered when forming the montage. Visual inspection of the experimental results using three mosaicing cases shows our method can produce satisfactory montages.

Rise of pairwise thermal entanglement for an alternating Ising and Heisenberg spin chain in an arbitrarily oriented magnetic field

NASA Astrophysics Data System (ADS)

Rojas, M.; de Souza, S. M.; Rojas, Onofre

2014-03-01

Typically two particles (spins) could be maximally entangled at zero temperature, and for a certain temperature the phenomenon of entanglement vanishes at the threshold temperature. For the Heisenberg coupled model or even the Ising model with a transverse magnetic field, one can observe some rise of entanglement even for a disentangled region at zero temperature. So we can understand this emergence of entanglement at finite temperature as being due to the mixing of some maximally entangled states with some other untangled states. Here, we present a simple one-dimensional Ising model with alternating Ising and Heisenberg spins in an arbitrarily oriented magnetic field, which can be mapped onto the classical Ising model with a magnetic field. This model does not show any evidence of entanglement at zero temperature, but surprisingly at finite temperature rise a pairwise thermal entanglement between two untangled spins at zero temperature when an arbitrarily oriented magnetic field is applied. This effect is a purely magnetic field, and the temperature dependence, as soon as the temperature increases, causes a small increase in concurrence, achieving its maximum at around 0.1. Even for long-range entanglement, a weak concurrence still survives. There are also some real materials that could serve as candidates that would exhibit this effect, such as Dy(NO3)(DMSO)2Cu(opba)(DMSO)2 [DMSO = dimethyl sulfoxide; opba = o-phenylenebis(oxamoto)] [J. Strečka, M. Hagiwara, Y. Han, T. Kida, Z. Honda, and M. Ikeda, Condens. Matter Phys. 15, 43002 (2012), 10.5488/CMP.15.43002].

CombAlign: a code for generating a one-to-many sequence alignment from a set of pairwise structure-based sequence alignments.

PubMed

Zhou, Carol L Ecale

2015-01-01

In order to better define regions of similarity among related protein structures, it is useful to identify the residue-residue correspondences among proteins. Few codes exist for constructing a one-to-many multiple sequence alignment derived from a set of structure or sequence alignments, and a need was evident for creating such a tool for combining pairwise structure alignments that would allow for insertion of gaps in the reference structure. This report describes a new Python code, CombAlign, which takes as input a set of pairwise sequence alignments (which may be structure based) and generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA). The use and utility of CombAlign was demonstrated by generating gapped MSSAs using sets of pairwise structure-based sequence alignments between structure models of the matrix protein (VP40) and pre-small/secreted glycoprotein (sGP) of Reston Ebolavirus and the corresponding proteins of several other filoviruses. The gapped MSSAs revealed structure-based residue-residue correspondences, which enabled identification of structurally similar versus differing regions in the Reston proteins compared to each of the other corresponding proteins. CombAlign is a new Python code that generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA) given a set of pairwise sequence alignments (which may be structure based). CombAlign has utility in assisting the user in distinguishing structurally conserved versus divergent regions on a reference protein structure relative to other closely related proteins. CombAlign was developed in Python 2.6, and the source code is available for download from the GitHub code repository.

APOLLO: a quality assessment service for single and multiple protein models.

PubMed

Wang, Zheng; Eickholt, Jesse; Cheng, Jianlin

2011-06-15

We built a web server named APOLLO, which can evaluate the absolute global and local qualities of a single protein model using machine learning methods or the global and local qualities of a pool of models using a pair-wise comparison approach. Based on our evaluations on 107 CASP9 (Critical Assessment of Techniques for Protein Structure Prediction) targets, the predicted quality scores generated from our machine learning and pair-wise methods have an average per-target correlation of 0.671 and 0.917, respectively, with the true model quality scores. Based on our test on 92 CASP9 targets, our predicted absolute local qualities have an average difference of 2.60 Å with the actual distances to native structure. http://sysbio.rnet.missouri.edu/apollo/. Single and pair-wise global quality assessment software is also available at the site.

Comparison of type 2 diabetes mellitus incidence in different phases of hepatitis B virus infection: A meta-analysis.

PubMed

Shen, Yi; Zhang, Sheng; Wang, Xulin; Wang, Yuanyuan; Zhang, Jian; Qin, Gang; Li, Wenchao; Ding, Kun; Zhang, Lei; Liang, Feng

2017-10-01

Because whether hepatitis B virus infection increases the risk of type 2 diabetes mellitus has been a controversial topic, pair-wise and network meta-analyses of published literature were carried out to accurately evaluate the association between different phases of hepatitis B virus infection and the risk of type 2 diabetes mellitus. A comprehensive literature retrieval was conducted from the PubMed, Embase, Cochrane Library and Chinese Database to identify epidemiological studies on the association between hepatitis B virus infection and the risk of type 2 diabetes mellitus that were published from 1999 to 2015. A pair-wise meta-analysis of direct evidence was performed to estimate the pooled odds ratios and 95% confidence intervals. A network meta-analysis was conducted, including the construction of a network plot, inconsistency plot, predictive interval plot, comparison-adjusted funnel plot and rank diagram, to graphically link the direct and indirect comparisons between different hepatitis B virus infective phases. Eighteen publications (n=113 639) describing 32 studies were included in this meta-analysis. In the pair-wise meta-analysis, the pooled odds ratio for type 2 diabetes mellitus in chronic hepatitis B cirrhosis patients was 1.76 (95% confidence interval: 1.44-2.14) when compared with non-cirrhotic chronic hepatitis B patients. In the network meta-analysis, six comparisons of four hepatitis B virus infectious states indicated the following descending order for the risk of type 2 diabetes mellitus: hepatitis B cirrhosis patients, non-cirrhotic chronic hepatitis B patients, hepatitis B virus carriers and non-hepatitis B virus controls. This study suggests that hepatitis B virus infection is not an independent risk factor for type 2 diabetes mellitus, but the development of cirrhosis may increase the incidence of type 2 diabetes mellitus cirrhosis. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Alphasatellitidae: a new family with two subfamilies for the classification of geminivirus- and nanovirus-associated alphasatellites.

PubMed

Briddon, Rob W; Martin, Darren P; Roumagnac, Philippe; Navas-Castillo, Jesús; Fiallo-Olivé, Elvira; Moriones, Enrique; Lett, Jean-Michel; Zerbini, F Murilo; Varsani, Arvind

2018-05-09

Nanoviruses and geminiviruses are circular, single stranded DNA viruses that infect many plant species around the world. Nanoviruses and certain geminiviruses that belong to the Begomovirus and Mastrevirus genera are associated with additional circular, single stranded DNA molecules (~ 1-1.4 kb) that encode a replication-associated protein (Rep). These Rep-encoding satellite molecules are commonly referred to as alphasatellites and here we communicate the establishment of the family Alphasatellitidae to which these have been assigned. Within the Alphasatellitidae family two subfamilies, Geminialphasatellitinae and Nanoalphasatellitinae, have been established to respectively accommodate the geminivirus- and nanovirus-associated alphasatellites. Whereas the pairwise nucleotide sequence identity distribution of all the known geminialphasatellites (n = 628) displayed a troughs at ~ 70% and 88% pairwise identity, that of the known nanoalphasatellites (n = 54) had a troughs at ~ 67% and ~ 80% pairwise identity. We use these pairwise identity values as thresholds together with phylogenetic analyses to establish four genera and 43 species of geminialphasatellites and seven genera and 19 species of nanoalphasatellites. Furthermore, a divergent alphasatellite associated with coconut foliar decay disease is assigned to a species but not a subfamily as it likely represents a new alphasatellite subfamily that could be established once other closely related molecules are discovered.

Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

PubMed Central

Ackerman, Matthew S.; Johri, Parul; Spitze, Ken; Xu, Sen; Doak, Thomas G.; Young, Kimberly; Lynch, Michael

2017-01-01

Population structure can be described by genotypic-correlation coefficients between groups of individuals, the most basic of which are the pairwise relatedness coefficients between any two individuals. There are nine pairwise relatedness coefficients in the most general model, and we show that these can be reduced to seven coefficients for biallelic loci. Although all nine coefficients can be estimated from pedigrees, six coefficients have been beyond empirical reach. We provide a numerical optimization procedure that estimates all seven reduced coefficients from population-genomic data. Simulations show that the procedure is nearly unbiased, even at 3× coverage, and errors in five of the seven coefficients are statistically uncorrelated. The remaining two coefficients have a negative correlation of errors, but their sum provides an unbiased assessment of the overall correlation of heterozygosity between two individuals. Application of these new methods to four populations of the freshwater crustacean Daphnia pulex reveal the occurrence of half siblings in our samples, as well as a number of identical individuals that are likely obligately asexual clone mates. Statistically significant negative estimates of these pairwise relatedness coefficients, including inbreeding coefficients that were typically negative, underscore the difficulties that arise when interpreting genotypic correlations as estimations of the probability that alleles are identical by descent. PMID:28341647

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting

PubMed Central

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-01-01

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes. PMID:29453930

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernardis, F. De; Aiola, S.; Vavagiakis, E. M.

Here, we present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariancemore » matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.« less

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernardis, F. De; Vavagiakis, E.M.; Niemack, M.D.

We present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariance matrixmore » of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.« less

Detection of the Pairwise Kinematic Sunyaev-Zel'dovich Effect with BOSS DR11 and the Atacama Cosmology Telescope

NASA Technical Reports Server (NTRS)

De Bernardis, F.; Aiola, S.; Vavagiakis, E. M.; Battaglia, N.; Niemack, M. D.; Beall, J.; Becker, D. T.; Bond, J. R.; Calabrese, E.; Cho, H.;

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

NASA Astrophysics Data System (ADS)

De Bernardis, F.; Aiola, S.; Vavagiakis, E. M.; Battaglia, N.; Niemack, M. D.; Beall, J.; Becker, D. T.; Bond, J. R.; Calabrese, E.; Cho, H.; Coughlin, K.; Datta, R.; Devlin, M.; Dunkley, J.; Dunner, R.; Ferraro, S.; Fox, A.; Gallardo, P. A.; Halpern, M.; Hand, N.; Hasselfield, M.; Henderson, S. W.; Hill, J. C.; Hilton, G. C.; Hilton, M.; Hincks, A. D.; Hlozek, R.; Hubmayr, J.; Huffenberger, K.; Hughes, J. P.; Irwin, K. D.; Koopman, B. J.; Kosowsky, A.; Li, D.; Louis, T.; Lungu, M.; Madhavacheril, M. S.; Maurin, L.; McMahon, J.; Moodley, K.; Naess, S.; Nati, F.; Newburgh, L.; Nibarger, J. P.; Page, L. A.; Partridge, B.; Schaan, E.; Schmitt, B. L.; Sehgal, N.; Sievers, J.; Simon, S. M.; Spergel, D. N.; Staggs, S. T.; Stevens, J. R.; Thornton, R. J.; van Engelen, A.; Van Lanen, J.; Wollack, E. J.

2017-03-01

We present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariance matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.

Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.

PubMed

Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter

2018-02-17

Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes.

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

DOE PAGES

Bernardis, F. De; Aiola, S.; Vavagiakis, E. M.; ...

2017-03-07

Here, we present a new measurement of the kinematic Sunyaev-Zel'dovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariancemore » matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zel'dovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.« less

Synchrony, Waves, and Spatial Hierarchies in the Spread of Influenza

NASA Astrophysics Data System (ADS)

Viboud, Cécile; Bjørnstad, Ottar N.; Smith, David L.; Simonsen, Lone; Miller, Mark A.; Grenfell, Bryan T.

2006-04-01

Quantifying long-range dissemination of infectious diseases is a key issue in their dynamics and control. Here, we use influenza-related mortality data to analyze the between-state progression of interpandemic influenza in the United States over the past 30 years. Outbreaks show hierarchical spatial spread evidenced by higher pairwise synchrony between more populous states. Seasons with higher influenza mortality are associated with higher disease transmission and more rapid spread than are mild ones. The regional spread of infection correlates more closely with rates of movement of people to and from their workplaces (workflows) than with geographical distance. Workflows are described in turn by a gravity model, with a rapid decay of commuting up to around 100 km and a long tail of rare longer range flow. A simple epidemiological model, based on the gravity formulation, captures the observed increase of influenza spatial synchrony with transmissibility; high transmission allows influenza to spread rapidly beyond local spatial constraints.

Quantum error-correcting code for ternary logic

NASA Astrophysics Data System (ADS)

Majumdar, Ritajit; Basu, Saikat; Ghosh, Shibashis; Sur-Kolay, Susmita

2018-05-01

Ternary quantum systems are being studied because they provide more computational state space per unit of information, known as qutrit. A qutrit has three basis states, thus a qubit may be considered as a special case of a qutrit where the coefficient of one of the basis states is zero. Hence both (2 ×2 ) -dimensional and (3 ×3 ) -dimensional Pauli errors can occur on qutrits. In this paper, we (i) explore the possible (2 ×2 ) -dimensional as well as (3 ×3 ) -dimensional Pauli errors in qutrits and show that any pairwise bit swap error can be expressed as a linear combination of shift errors and phase errors, (ii) propose a special type of error called a quantum superposition error and show its equivalence to arbitrary rotation, (iii) formulate a nine-qutrit code which can correct a single error in a qutrit, and (iv) provide its stabilizer and circuit realization.

Balanced Synaptic Input Shapes the Correlation between Neural Spike Trains

PubMed Central

Litwin-Kumar, Ashok; Oswald, Anne-Marie M.; Urban, Nathaniel N.; Doiron, Brent

2011-01-01

Stimulus properties, attention, and behavioral context influence correlations between the spike times produced by a pair of neurons. However, the biophysical mechanisms that modulate these correlations are poorly understood. With a combined theoretical and experimental approach, we show that the rate of balanced excitatory and inhibitory synaptic input modulates the magnitude and timescale of pairwise spike train correlation. High rate synaptic inputs promote spike time synchrony rather than long timescale spike rate correlations, while low rate synaptic inputs produce opposite results. This correlation shaping is due to a combination of enhanced high frequency input transfer and reduced firing rate gain in the high input rate state compared to the low state. Our study extends neural modulation from single neuron responses to population activity, a necessary step in understanding how the dynamics and processing of neural activity change across distinct brain states. PMID:22215995

Binary Multidimensional Scaling for Hashing.

PubMed

Huang, Yameng; Lin, Zhouchen

2017-10-04

Hashing is a useful technique for fast nearest neighbor search due to its low storage cost and fast query speed. Unsupervised hashing aims at learning binary hash codes for the original features so that the pairwise distances can be best preserved. While several works have targeted on this task, the results are not satisfactory mainly due to the oversimplified model. In this paper, we propose a unified and concise unsupervised hashing framework, called Binary Multidimensional Scaling (BMDS), which is able to learn the hash code for distance preservation in both batch and online mode. In the batch mode, unlike most existing hashing methods, we do not need to simplify the model by predefining the form of hash map. Instead, we learn the binary codes directly based on the pairwise distances among the normalized original features by Alternating Minimization. This enables a stronger expressive power of the hash map. In the online mode, we consider the holistic distance relationship between current query example and those we have already learned, rather than only focusing on current data chunk. It is useful when the data come in a streaming fashion. Empirical results show that while being efficient for training, our algorithm outperforms state-of-the-art methods by a large margin in terms of distance preservation, which is practical for real-world applications.

Probabilistic visual and electromagnetic data fusion for robust drift-free sequential mosaicking: application to fetoscopy

PubMed Central

Tella-Amo, Marcel; Peter, Loic; Shakir, Dzhoshkun I.; Deprest, Jan; Iglesias, Juan Eugenio; Ourselin, Sebastien

2018-01-01

Abstract. The most effective treatment for twin-to-twin transfusion syndrome is laser photocoagulation of the shared vascular anastomoses in the placenta. Vascular connections are extremely challenging to locate due to their caliber and the reduced field-of-view of the fetoscope. Therefore, mosaicking techniques are beneficial to expand the scene, facilitate navigation, and allow vessel photocoagulation decision-making. Local vision-based mosaicking algorithms inherently drift over time due to the use of pairwise transformations. We propose the use of an electromagnetic tracker (EMT) sensor mounted at the tip of the fetoscope to obtain camera pose measurements, which we incorporate into a probabilistic framework with frame-to-frame visual information to achieve globally consistent sequential mosaics. We parametrize the problem in terms of plane and camera poses constrained by EMT measurements to enforce global consistency while leveraging pairwise image relationships in a sequential fashion through the use of local bundle adjustment. We show that our approach is drift-free and performs similarly to state-of-the-art global alignment techniques like bundle adjustment albeit with much less computational burden. Additionally, we propose a version of bundle adjustment that uses EMT information. We demonstrate the robustness to EMT noise and loss of visual information and evaluate mosaics for synthetic, phantom-based and ex vivo datasets. PMID:29487889

Discovery of the first maize-infecting mastrevirus in the Americas using a vector-enabled metagenomics approach.

PubMed

Fontenele, Rafaela S; Alves-Freitas, Dione M T; Silva, Pedro I T; Foresti, Josemar; Silva, Paulo R; Godinho, Márcio T; Varsani, Arvind; Ribeiro, Simone G

2018-01-01

The genus Mastrevirus (family Geminiviridae) is composed of single-stranded DNA viruses that infect mono- and dicotyledonous plants and are transmitted by leafhoppers. In South America, there have been only two previous reports of mastreviruses, both identified in sweet potatoes (from Peru and Uruguay). As part of a general viral surveillance program, we used a vector-enabled metagenomics (VEM) approach and sampled leafhoppers (Dalbulus maidis) in Itumbiara (State of Goiás), Brazil. High-throughput sequencing of viral DNA purified from the leafhopper sample revealed mastrevirus-like contigs. Using a set of abutting primers, a 2746-nt circular genome was recovered. The circular genome has a typical mastrevirus genome organization and shares <63% pairwise identity with other mastrevirus isolates from around the world. Therefore, the new mastrevirus was tentatively named "maize striate mosaic virus". Seventeen maize leaf samples were collected in the same field as the leafhoppers, and ten samples were found to be positive for this mastrevirus. Furthermore, the ten genomes recovered from the maize samples share >99% pairwise identity with the one from the leafhopper. This is the first report of a maize-infecting mastrevirus in the Americas, the first identified in a non-vegetatively propagated mastrevirus host in South America, and the first mastrevirus to be identified in Brazil.

Polarizable polymer chain under external electric field: Effects of many-body electrostatic dipole correlations.

PubMed

Budkov, Yu A; Kolesnikov, A L

2016-11-01

We present a new simple self-consistent field theory of a polarizable flexible polymer chain under an external constant electric field with account for the many-body electrostatic dipole correlations. We show the effects of electrostatic dipole correlations on the electric-field-induced globule-coil transition. We demonstrate that only when the polymer chain is in the coil conformation, the electrostatic dipole correlations of monomers can be considered as pairwise. However, when the polymer chain is in a collapsed state, the dipole correlations have to be considered at the many-body level.

A process of rumour scotching on finite populations.

PubMed

de Arruda, Guilherme Ferraz; Lebensztayn, Elcio; Rodrigues, Francisco A; Rodríguez, Pablo Martín

2015-09-01

Rumour spreading is a ubiquitous phenomenon in social and technological networks. Traditional models consider that the rumour is propagated by pairwise interactions between spreaders and ignorants. Only spreaders are active and may become stiflers after contacting spreaders or stiflers. Here we propose a competition-like model in which spreaders try to transmit an information, while stiflers are also active and try to scotch it. We study the influence of transmission/scotching rates and initial conditions on the qualitative behaviour of the process. An analytical treatment based on the theory of convergence of density-dependent Markov chains is developed to analyse how the final proportion of ignorants behaves asymptotically in a finite homogeneously mixing population. We perform Monte Carlo simulations in random graphs and scale-free networks and verify that the results obtained for homogeneously mixing populations can be approximated for random graphs, but are not suitable for scale-free networks. Furthermore, regarding the process on a heterogeneous mixing population, we obtain a set of differential equations that describes the time evolution of the probability that an individual is in each state. Our model can also be applied for studying systems in which informed agents try to stop the rumour propagation, or for describing related susceptible-infected-recovered systems. In addition, our results can be considered to develop optimal information dissemination strategies and approaches to control rumour propagation.

A process of rumour scotching on finite populations

PubMed Central

de Arruda, Guilherme Ferraz; Lebensztayn, Elcio; Rodrigues, Francisco A.; Rodríguez, Pablo Martín

2015-01-01

Rumour spreading is a ubiquitous phenomenon in social and technological networks. Traditional models consider that the rumour is propagated by pairwise interactions between spreaders and ignorants. Only spreaders are active and may become stiflers after contacting spreaders or stiflers. Here we propose a competition-like model in which spreaders try to transmit an information, while stiflers are also active and try to scotch it. We study the influence of transmission/scotching rates and initial conditions on the qualitative behaviour of the process. An analytical treatment based on the theory of convergence of density-dependent Markov chains is developed to analyse how the final proportion of ignorants behaves asymptotically in a finite homogeneously mixing population. We perform Monte Carlo simulations in random graphs and scale-free networks and verify that the results obtained for homogeneously mixing populations can be approximated for random graphs, but are not suitable for scale-free networks. Furthermore, regarding the process on a heterogeneous mixing population, we obtain a set of differential equations that describes the time evolution of the probability that an individual is in each state. Our model can also be applied for studying systems in which informed agents try to stop the rumour propagation, or for describing related susceptible–infected–recovered systems. In addition, our results can be considered to develop optimal information dissemination strategies and approaches to control rumour propagation. PMID:26473048

Pair-Wise and Many-Body Dispersive Interactions Coupled to an Optimally Tuned Range-Separated Hybrid Functional.

PubMed

Agrawal, Piyush; Tkatchenko, Alexandre; Kronik, Leeor

2013-08-13

We propose a nonempirical, pair-wise or many-body dispersion-corrected, optimally tuned range-separated hybrid functional. This functional retains the advantages of the optimal-tuning approach in the prediction of the electronic structure. At the same time, it gains accuracy in the prediction of binding energies for dispersively bound systems, as demonstrated on the S22 and S66 benchmark sets of weakly bound dimers.

Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis.

PubMed

Kim, Eunwoo; Park, HyunWook

2017-02-01

The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.

A composite likelihood approach for spatially correlated survival data

PubMed Central

Paik, Jane; Ying, Zhiliang

2013-01-01

The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory. PMID:24223450

Pairwise adaptive thermostats for improved accuracy and stability in dissipative particle dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leimkuhler, Benedict, E-mail: b.leimkuhler@ed.ac.uk; Shang, Xiaocheng, E-mail: x.shang@brown.edu

2016-11-01

We examine the formulation and numerical treatment of dissipative particle dynamics (DPD) and momentum-conserving molecular dynamics. We show that it is possible to improve both the accuracy and the stability of DPD by employing a pairwise adaptive Langevin thermostat that precisely matches the dynamical characteristics of DPD simulations (e.g., autocorrelation functions) while automatically correcting thermodynamic averages using a negative feedback loop. In the low friction regime, it is possible to replace DPD by a simpler momentum-conserving variant of the Nosé–Hoover–Langevin method based on thermostatting only pairwise interactions; we show that this method has an extra order of accuracy for anmore » important class of observables (a superconvergence result), while also allowing larger timesteps than alternatives. All the methods mentioned in the article are easily implemented. Numerical experiments are performed in both equilibrium and nonequilibrium settings; using Lees–Edwards boundary conditions to induce shear flow.« less

Pairwise Interaction Extended Point-Particle (PIEP) model for multiphase jets and sedimenting particles

NASA Astrophysics Data System (ADS)

Liu, Kai; Balachandar, S.

2017-11-01

We perform a series of Euler-Lagrange direct numerical simulations (DNS) for multiphase jets and sedimenting particles. The forces the flow exerts on the particles in these two-way coupled simulations are computed using the Basset-Bousinesq-Oseen (BBO) equations. These forces do not explicitly account for particle-particle interactions, even though such pairwise interactions induced by the perturbations from neighboring particles may be important especially when the particle volume fraction is high. Such effects have been largely unaddressed in the literature. Here, we implement the Pairwise Interaction Extended Point-Particle (PIEP) model to simulate the effect of neighboring particle pairs. A simple collision model is also applied to avoid unphysical overlapping of solid spherical particles. The simulation results indicate that the PIEP model provides a more elaborative and complicated movement of the dispersed phase (droplets and particles). Office of Naval Research (ONR) Multidisciplinary University Research Initiative (MURI) project N00014-16-1-2617.

Single-atom gold catalysis in the context of developments in parahydrogen-induced polarization.

PubMed

Corma, Avelino; Salnikov, Oleg G; Barskiy, Danila A; Kovtunov, Kirill V; Koptyug, Igor V

2015-05-04

A highly isolated monoatomic gold catalyst, with single gold atoms dispersed on multiwalled carbon nanotubes (MWCNTs), has been synthesized, characterized, and tested in heterogeneous hydrogenation of 1,3-butadiene and 1-butyne with parahydrogen to maximize the polarization level and the contribution of the pairwise hydrogen addition route. The Au/MWCNTs catalyst was found to be active and efficient in pairwise hydrogen addition and the estimated contributions from the pairwise hydrogen addition route are at least an order of magnitude higher than those for supported metal nanoparticle catalysts. Therefore, the use of the highly isolated monoatomic catalysts is very promising for production of hyperpolarized fluids that can be used for the significant enhancement of NMR signals. A mechanism of 1,3-butadiene hydrogenation with parahydrogen over the highly isolated monoatomic Au/MWCNTs catalyst is also proposed. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

PubMed Central

Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

2015-01-01

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

GetReal in network meta-analysis: a review of the methodology.

PubMed

Efthimiou, Orestis; Debray, Thomas P A; van Valkenhoef, Gert; Trelle, Sven; Panayidou, Klea; Moons, Karel G M; Reitsma, Johannes B; Shang, Aijing; Salanti, Georgia

2016-09-01

Pairwise meta-analysis is an established statistical tool for synthesizing evidence from multiple trials, but it is informative only about the relative efficacy of two specific interventions. The usefulness of pairwise meta-analysis is thus limited in real-life medical practice, where many competing interventions may be available for a certain condition and studies informing some of the pairwise comparisons may be lacking. This commonly encountered scenario has led to the development of network meta-analysis (NMA). In the last decade, several applications, methodological developments, and empirical studies in NMA have been published, and the area is thriving as its relevance to public health is increasingly recognized. This article presents a review of the relevant literature on NMA methodology aiming to pinpoint the developments that have appeared in the field. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A composite likelihood approach for spatially correlated survival data.

PubMed

Paik, Jane; Ying, Zhiliang

2013-01-01

The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory.

Clustering and propulsion of isotropic catalytic swimmers

NASA Astrophysics Data System (ADS)

Varma, Akhil; Montenegro-Johnson, Thomas D.; Michelin, Sebastien

2017-11-01

Catalytic micro-swimmers such as phoretic particles use local gradients in solute concentration for propulsion. An isolated isotropic phoretic particle generates a uniform concentration field on its surface and hence cannot propel on its own. Symmetry of this field is broken by the presence of at least another similar particle in the system, which leads to phoretic attraction or repulsion. Phoretic attraction drives the clustering of identical homogeneous particles into stable clusters of various configurations which may self-propel or rotate due to their geometric asymmetry. Using full numerical simulations and analytic approximations based on pairwise interactions of the particles, we study the cluster formation and its impact on the statistics of the propulsion properties. We finally analyze the effect of background noise on the results. European Research Council (Grant Agreement 714027).

Single and multiple vortex rings in three-dimensional Bose-Einstein condensates: Existence, stability, and dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Wenlong; Bisset, R. N.; Ticknor, Christopher

In the present work, we explore the existence, stability, and dynamics of single- and multiple-vortex-ring states that can arise in Bose-Einstein condensates. Earlier works have illustrated the bifurcation of such states in the vicinity of the linear limit for isotropic or anisotropic three-dimensional harmonic traps. Here, we extend these states to the regime of large chemical potentials, the so-called Thomas-Fermi limit, and explore their properties such as equilibrium radii and inter-ring distance for multi-ring states, as well as their vibrational spectra and possible instabilities. In this limit, both the existence and stability characteristics can be partially traced to a particlemore » picture that considers the rings as individual particles oscillating within the trap and interacting pairwise with one another. In conclusion, we examine some representative instability scenarios of the multi-ring dynamics, including breakup and reconnections, as well as the transient formation of vortex lines.« less

Single and multiple vortex rings in three-dimensional Bose-Einstein condensates: Existence, stability, and dynamics

DOE PAGES

Wang, Wenlong; Bisset, R. N.; Ticknor, Christopher; ...

2017-04-27

In the present work, we explore the existence, stability, and dynamics of single- and multiple-vortex-ring states that can arise in Bose-Einstein condensates. Earlier works have illustrated the bifurcation of such states in the vicinity of the linear limit for isotropic or anisotropic three-dimensional harmonic traps. Here, we extend these states to the regime of large chemical potentials, the so-called Thomas-Fermi limit, and explore their properties such as equilibrium radii and inter-ring distance for multi-ring states, as well as their vibrational spectra and possible instabilities. In this limit, both the existence and stability characteristics can be partially traced to a particlemore » picture that considers the rings as individual particles oscillating within the trap and interacting pairwise with one another. In conclusion, we examine some representative instability scenarios of the multi-ring dynamics, including breakup and reconnections, as well as the transient formation of vortex lines.« less

Development of a methodology to compute solvation free energies on the basis of the theory of energy representation for solutions represented with a polarizable force field.

PubMed

Suzuoka, Daiki; Takahashi, Hideaki; Ishiyama, Tatsuya; Morita, Akihiro

2012-12-07

We have developed a method of molecular simulations utilizing a polarizable force field in combination with the theory of energy representation (ER) for the purpose of establishing an efficient and accurate methodology to compute solvation free energies. The standard version of the ER method is, however, based on the assumption that the solute-solvent interaction is pairwise additive for its construction. A crucial step in the present method is to introduce an intermediate state in the solvation process to treat separately the many-body interaction associated with the polarizable model. The intermediate state is chosen so that the solute-solvent interaction can be formally written in the pairwise form, though the solvent molecules are interacting with each other with polarizable charges dependent on the solvent configuration. It is, then, possible to extract the free energy contribution δμ due to the many-body interaction between solute and solvent from the total solvation free energy Δμ. It is shown that the free energy δμ can be computed by an extension of the recent development implemented in quantum mechanical∕molecular mechanical simulations. To assess the numerical robustness of the approach, we computed the solvation free energies of a water and a methanol molecule in water solvent, where two paths for the solvation processes were examined by introducing different intermediate states. The solvation free energies of a water molecule associated with the two paths were obtained as -5.3 and -5.8 kcal∕mol. Those of a methanol molecule were determined as -3.5 and -3.7 kcal∕mol. These results of the ER simulations were also compared with those computed by a numerically exact approach. It was demonstrated that the present approach produces the solvation free energies in comparable accuracies to simulations of thermodynamic integration (TI) method within a tenth of computational time used for the TI simulations.

Bioinformatics algorithm based on a parallel implementation of a machine learning approach using transducers

NASA Astrophysics Data System (ADS)

Roche-Lima, Abiel; Thulasiram, Ruppa K.

2012-02-01

Finite automata, in which each transition is augmented with an output label in addition to the familiar input label, are considered finite-state transducers. Transducers have been used to analyze some fundamental issues in bioinformatics. Weighted finite-state transducers have been proposed to pairwise alignments of DNA and protein sequences; as well as to develop kernels for computational biology. Machine learning algorithms for conditional transducers have been implemented and used for DNA sequence analysis. Transducer learning algorithms are based on conditional probability computation. It is calculated by using techniques, such as pair-database creation, normalization (with Maximum-Likelihood normalization) and parameters optimization (with Expectation-Maximization - EM). These techniques are intrinsically costly for computation, even worse when are applied to bioinformatics, because the databases sizes are large. In this work, we describe a parallel implementation of an algorithm to learn conditional transducers using these techniques. The algorithm is oriented to bioinformatics applications, such as alignments, phylogenetic trees, and other genome evolution studies. Indeed, several experiences were developed using the parallel and sequential algorithm on Westgrid (specifically, on the Breeze cluster). As results, we obtain that our parallel algorithm is scalable, because execution times are reduced considerably when the data size parameter is increased. Another experience is developed by changing precision parameter. In this case, we obtain smaller execution times using the parallel algorithm. Finally, number of threads used to execute the parallel algorithm on the Breezy cluster is changed. In this last experience, we obtain as result that speedup is considerably increased when more threads are used; however there is a convergence for number of threads equal to or greater than 16.

Quantum Spin Dynamics with Pairwise-Tunable, Long-Range Interactions

DTIC Science & Technology

2016-08-05

rection of the arrows. Dashed (dotted) lines mark the NNN hopping terms (coefficients ±t2). NNNN long -range hopping along curved lines are included to...Quantum spin dynamics with pairwise-tunable, long -range interactions C.-L. Hunga,b,1,2, Alejandro González-Tudelac,1,2, J. Ignacio Ciracc, and H. J...atoms) that interact by way of a variety of processes, such as atomic collisions. Such pro- cesses typically lead to short -range, nearest-neighbor

Exploring the roles of cannot-link constraint in community detection via Multi-variance Mixed Gaussian Generative Model.

PubMed

Yang, Liang; Ge, Meng; Jin, Di; He, Dongxiao; Fu, Huazhu; Wang, Jing; Cao, Xiaochun

2017-01-01

Due to the demand for performance improvement and the existence of prior information, semi-supervised community detection with pairwise constraints becomes a hot topic. Most existing methods have been successfully encoding the must-link constraints, but neglect the opposite ones, i.e., the cannot-link constraints, which can force the exclusion between nodes. In this paper, we are interested in understanding the role of cannot-link constraints and effectively encoding pairwise constraints. Towards these goals, we define an integral generative process jointly considering the network topology, must-link and cannot-link constraints. We propose to characterize this process as a Multi-variance Mixed Gaussian Generative (MMGG) Model to address diverse degrees of confidences that exist in network topology and pairwise constraints and formulate it as a weighted nonnegative matrix factorization problem. The experiments on artificial and real-world networks not only illustrate the superiority of our proposed MMGG, but also, most importantly, reveal the roles of pairwise constraints. That is, though the must-link is more important than cannot-link when either of them is available, both must-link and cannot-link are equally important when both of them are available. To the best of our knowledge, this is the first work on discovering and exploring the importance of cannot-link constraints in semi-supervised community detection.

Exploring the roles of cannot-link constraint in community detection via Multi-variance Mixed Gaussian Generative Model

PubMed Central

Ge, Meng; Jin, Di; He, Dongxiao; Fu, Huazhu; Wang, Jing; Cao, Xiaochun

2017-01-01

Due to the demand for performance improvement and the existence of prior information, semi-supervised community detection with pairwise constraints becomes a hot topic. Most existing methods have been successfully encoding the must-link constraints, but neglect the opposite ones, i.e., the cannot-link constraints, which can force the exclusion between nodes. In this paper, we are interested in understanding the role of cannot-link constraints and effectively encoding pairwise constraints. Towards these goals, we define an integral generative process jointly considering the network topology, must-link and cannot-link constraints. We propose to characterize this process as a Multi-variance Mixed Gaussian Generative (MMGG) Model to address diverse degrees of confidences that exist in network topology and pairwise constraints and formulate it as a weighted nonnegative matrix factorization problem. The experiments on artificial and real-world networks not only illustrate the superiority of our proposed MMGG, but also, most importantly, reveal the roles of pairwise constraints. That is, though the must-link is more important than cannot-link when either of them is available, both must-link and cannot-link are equally important when both of them are available. To the best of our knowledge, this is the first work on discovering and exploring the importance of cannot-link constraints in semi-supervised community detection. PMID:28678864

POEM: Identifying Joint Additive Effects on Regulatory Circuits.

PubMed

Botzman, Maya; Nachshon, Aharon; Brodt, Avital; Gat-Viks, Irit

2016-01-01

Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such "modularization" approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects. Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs. The software described in this article is available at csgi.tau.ac.il/POEM/.

POEM: Identifying Joint Additive Effects on Regulatory Circuits

PubMed Central

Botzman, Maya; Nachshon, Aharon; Brodt, Avital; Gat-Viks, Irit

2016-01-01

Motivation: Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such “modularization” approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects. Results: Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs. Availability: The software described in this article is available at csgi.tau.ac.il/POEM/. PMID:27148351

SANA NetGO: a combinatorial approach to using Gene Ontology (GO) terms to score network alignments.

PubMed

Hayes, Wayne B; Mamano, Nil

2018-04-15

Gene Ontology (GO) terms are frequently used to score alignments between protein-protein interaction (PPI) networks. Methods exist to measure GO similarity between proteins in isolation, but proteins in a network alignment are not isolated: each pairing is dependent on every other via the alignment itself. Existing measures fail to take into account the frequency of GO terms across networks, instead imposing arbitrary rules on when to allow GO terms. Here we develop NetGO, a new measure that naturally weighs infrequent, informative GO terms more heavily than frequent, less informative GO terms, without arbitrary cutoffs, instead downweighting GO terms according to their frequency in the networks being aligned. This is a global measure applicable only to alignments, independent of pairwise GO measures, in the same sense that the edge-based EC or S3 scores are global measures of topological similarity independent of pairwise topological similarities. We demonstrate the superiority of NetGO in alignments of predetermined quality and show that NetGO correlates with alignment quality better than any existing GO-based alignment measures. We also demonstrate that NetGO provides a measure of taxonomic similarity between species, consistent with existing taxonomic measuresa feature not shared with existing GObased network alignment measures. Finally, we re-score alignments produced by almost a dozen aligners from a previous study and show that NetGO does a better job at separating good alignments from bad ones. Available as part of SANA. whayes@uci.edu. Supplementary data are available at Bioinformatics online.

A Comparison of Online, Video Synchronous, and Traditional Learning Modes for an Introductory Undergraduate Physics Course

NASA Astrophysics Data System (ADS)

Faulconer, E. K.; Griffith, J.; Wood, B.; Acharyya, S.; Roberts, D.

2018-05-01

While the equivalence between online and traditional classrooms has been well-researched, very little of this includes college-level introductory Physics. Only one study explored Physics at the whole-class level rather than specific course components such as a single lab or a homework platform. In this work, we compared the failure rate, grade distribution, and withdrawal rates in an introductory undergraduate Physics course across several learning modes including traditional face-to-face instruction, synchronous video instruction, and online classes. Statistically significant differences were found for student failure rates, grade distribution, and withdrawal rates but yielded small effect sizes. Post-hoc pair-wise test was run to determine differences between learning modes. Online students had a significantly lower failure rate than students who took the class via synchronous video classroom. While statistically significant differences were found for grade distributions, the pair-wise comparison yielded no statistically significance differences between learning modes when using the more conservative Bonferroni correction in post-hoc testing. Finally, in this study, student withdrawal rates were lowest for students who took the class in person (in-person classroom and synchronous video classroom) than online. Students that persist in an online introductory Physics class are more likely to achieve an A than in other modes. However, the withdrawal rate is higher from online Physics courses. Further research is warranted to better understand the reasons for higher withdrawal rates in online courses. Finding the root cause to help eliminate differences in student performance across learning modes should remain a high priority for education researchers and the education community as a whole.

Comparing and explaining differences in the magnitude, content, and sensitivity of utilities predicted by the EQ-5D, SF-6D, HUI 3, 15D, QWB, and AQoL-8D multiattribute utility instruments.

PubMed

Richardson, Jeff; Khan, Munir A; Iezzi, Angelo; Maxwell, Aimee

2015-04-01

Cost utility analysis permits the comparison of disparate health services by measuring outcomes in comparable units, namely, quality-adjusted life-years, which equal life-years times the utility of the health state. However, comparability is compromised when different utility instruments predict different utilities for the same health state. The present paper measures the extent of, and reason for, differences between the utilities predicted by the EQ-5D-5L, SF-6D, HUI 3, 15D, QWB, and AQoL-8D. Data were obtained from patients in seven disease areas and members of the healthy public in six countries. Differences between public and patient utilities were estimated using each of the instruments. To explain discrepancies between the estimates, the measurement scales and content of the instruments were compared. The sensitivity of instruments to independently measured health dimensions was measured in pairwise comparisons of all combinations of the instruments. The difference between public and patient utilities varied with the choice of instrument by more than 50% for every disease group and in four of the seven groups by more than 100%. Discrepancies were associated with differences in both the instrument content and their measurement scales. Pairwise comparisons of instruments found that variation in the sensitivity to physical and psychosocial dimensions of health closely reflected the items in the instrument's descriptive systems. Results indicate that instruments measure related but different constructs. They imply that commonly used instruments systematically discriminate against some classes of services, most notably mental health services. Differences in the instrument scales imply the need for transformations between the instruments to increase the comparability of measurement. © The Author(s) 2014.

Measurements of the pairwise kinematic Sunyaev-Zel'dovich effect with the Atacama Cosmology Telescope and future surveys

NASA Astrophysics Data System (ADS)

Vavagiakis, Eve Marie; De Bernardis, Francesco; Aiola, Simone; Battaglia, Nicholas; Niemack, Michael D.; ACTPol Collaboration

2017-06-01

We have made improved measurements of the kinematic Sunyaev-Zel’dovich (kSZ) effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). We used a map of the Cosmic Microwave Background (CMB) from two seasons of observations each by ACT and the Atacama Cosmology Telescope Polarimeter (ACTPol) receiver. We evaluated the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog via 600 square degrees of overlapping sky area. The measurement of the kSZ signal arising from the large-scale motions of clusters was made by fitting data to an analytical model. The free parameter of the fit determined the optical depth to microwave photon scattering for the cluster sample. We estimated the covariance matrix of the mean pairwise momentum as a function of galaxy separation using CMB simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based uncertainties gave signal-to-noise estimates between 3.6 and 4.1 for various luminosity cuts. Additionally, we explored a novel approach to estimating cluster optical depths from the average thermal Sunyaev-Zel’dovich (tSZ) signal at the BOSS DR11 catalog positions. Our results were broadly consistent with those obtained from the kSZ signal. In the future, the tSZ signal may provide a valuable probe of cluster optical depths, enabling the extraction of velocities from the kSZ sourced mean pairwise momenta. New CMB maps from three seasons of ACTPol observations with multi-frequency coverage overlap with nearly four times as many DR11 sources and promise to improve statistics and systematics for SZ measurements. With these and other upcoming data, the pairwise kSZ signal is poised to become a powerful new cosmological tool, able to probe large physical scales to inform neutrino physics and test models of modified gravity and dark energy.

Comorbidities in the diseasome are more apparent than real: What Bayesian filtering reveals about the comorbidities of depression

PubMed Central

Bolgar, Bence; Deakin, Bill

2017-01-01

Comorbidity patterns have become a major source of information to explore shared mechanisms of pathogenesis between disorders. In hypothesis-free exploration of comorbid conditions, disease-disease networks are usually identified by pairwise methods. However, interpretation of the results is hindered by several confounders. In particular a very large number of pairwise associations can arise indirectly through other comorbidity associations and they increase exponentially with the increasing breadth of the investigated diseases. To investigate and filter this effect, we computed and compared pairwise approaches with a systems-based method, which constructs a sparse Bayesian direct multimorbidity map (BDMM) by systematically eliminating disease-mediated comorbidity relations. Additionally, focusing on depression-related parts of the BDMM, we evaluated correspondence with results from logistic regression, text-mining and molecular-level measures for comorbidities such as genetic overlap and the interactome-based association score. We used a subset of the UK Biobank Resource, a cross-sectional dataset including 247 diseases and 117,392 participants who filled out a detailed questionnaire about mental health. The sparse comorbidity map confirmed that depressed patients frequently suffer from both psychiatric and somatic comorbid disorders. Notably, anxiety and obesity show strong and direct relationships with depression. The BDMM identified further directly co-morbid somatic disorders, e.g. irritable bowel syndrome, fibromyalgia, or migraine. Using the subnetwork of depression and metabolic disorders for functional analysis, the interactome-based system-level score showed the best agreement with the sparse disease network. This indicates that these epidemiologically strong disease-disease relations have improved correspondence with expected molecular-level mechanisms. The substantially fewer number of comorbidity relations in the BDMM compared to pairwise methods implies that biologically meaningful comorbid relations may be less frequent than earlier pairwise methods suggested. The computed interactive comprehensive multimorbidity views over the diseasome are available on the web at Co=MorNet: bioinformatics.mit.bme.hu/UKBNetworks. PMID:28644851

The introduction of hydrogen bond and hydrophobicity effects into the rotational isomeric states model for conformational analysis of unfolded peptides.

PubMed

Engin, Ozge; Sayar, Mehmet; Erman, Burak

2009-01-13

Relative contributions of local and non-local interactions to the unfolded conformations of peptides are examined by using the rotational isomeric states model which is a Markov model based on pairwise interactions of torsion angles. The isomeric states of a residue are well described by the Ramachandran map of backbone torsion angles. The statistical weight matrices for the states are determined by molecular dynamics simulations applied to monopeptides and dipeptides. Conformational properties of tripeptides formed from combinations of alanine, valine, tyrosine and tryptophan are investigated based on the Markov model. Comparison with molecular dynamics simulation results on these tripeptides identifies the sequence-distant long-range interactions that are missing in the Markov model. These are essentially the hydrogen bond and hydrophobic interactions that are obtained between the first and the third residue of a tripeptide. A systematic correction is proposed for incorporating these long-range interactions into the rotational isomeric states model. Preliminary results suggest that the Markov assumption can be improved significantly by renormalizing the statistical weight matrices to include the effects of the long-range correlations.

The introduction of hydrogen bond and hydrophobicity effects into the rotational isomeric states model for conformational analysis of unfolded peptides

NASA Astrophysics Data System (ADS)

Engin, Ozge; Sayar, Mehmet; Erman, Burak

2009-03-01

Relative contributions of local and non-local interactions to the unfolded conformations of peptides are examined by using the rotational isomeric states model which is a Markov model based on pairwise interactions of torsion angles. The isomeric states of a residue are well described by the Ramachandran map of backbone torsion angles. The statistical weight matrices for the states are determined by molecular dynamics simulations applied to monopeptides and dipeptides. Conformational properties of tripeptides formed from combinations of alanine, valine, tyrosine and tryptophan are investigated based on the Markov model. Comparison with molecular dynamics simulation results on these tripeptides identifies the sequence-distant long-range interactions that are missing in the Markov model. These are essentially the hydrogen bond and hydrophobic interactions that are obtained between the first and the third residue of a tripeptide. A systematic correction is proposed for incorporating these long-range interactions into the rotational isomeric states model. Preliminary results suggest that the Markov assumption can be improved significantly by renormalizing the statistical weight matrices to include the effects of the long-range correlations.

Self-Diffusion of Drops in a Dilute Sheared Emulsion

NASA Technical Reports Server (NTRS)

Loewenberg, Michael; Hinch, E. J.

1996-01-01

Self-diffusion coefficients that describe cross-flow migration of non-Brownian drops in a dilute sheared emulsion were obtained by trajectory calculations. A boundary integral formulation was used to describe pairwise interactions between deformable drops; interactions between undeformed drops were described with mobility functions for spherical drops. The results indicate that drops have large anisotropic self-diffusivities which depend strongly on the drop viscosity and modestly on the shear-rate. Pairwise interactions between drops in shear-flow do not appreciably promote drop breakup.

Unified Pairwise Spatial Relations: An Application to Graphical Symbol Retrieval

NASA Astrophysics Data System (ADS)

Santosh, K. C.; Wendling, Laurent; Lamiroy, Bart

In this paper, we present a novel unifying concept of pairwise spatial relations. We develop two way directional relations with respect to a unique point set, based on topology of the studied objects and thus avoids problems related to erroneous choices of reference objects while preserving symmetry. The method is robust to any type of image configuration since the directional relations are topologically guided. An automatic prototype graphical symbol retrieval is presented in order to establish its expressiveness.

Generalized thermodynamics of phase equilibria in scalar active matter

NASA Astrophysics Data System (ADS)

Solon, Alexandre P.; Stenhammar, Joakim; Cates, Michael E.; Kafri, Yariv; Tailleur, Julien

2018-02-01

Motility-induced phase separation (MIPS) arises generically in fluids of self-propelled particles when interactions lead to a kinetic slowdown at high densities. Starting from a continuum description of scalar active matter akin to a generalized Cahn-Hilliard equation, we give a general prescription for the mean densities of coexisting phases in flux-free steady states that amounts, at a hydrodynamics scale, to extremizing an effective free energy. We illustrate our approach on two well-known models: self-propelled particles interacting either through a density-dependent propulsion speed or via direct pairwise forces. Our theory accounts quantitatively for their phase diagrams, providing a unified description of MIPS.

Hybrid pairwise likelihood analysis of animal behavior experiments.

PubMed

Cattelan, Manuela; Varin, Cristiano

2013-12-01

The study of the determinants of fights between animals is an important issue in understanding animal behavior. For this purpose, tournament experiments among a set of animals are often used by zoologists. The results of these tournament experiments are naturally analyzed by paired comparison models. Proper statistical analysis of these models is complicated by the presence of dependence between the outcomes of fights because the same animal is involved in different contests. This paper discusses two different model specifications to account for between-fights dependence. Models are fitted through the hybrid pairwise likelihood method that iterates between optimal estimating equations for the regression parameters and pairwise likelihood inference for the association parameters. This approach requires the specification of means and covariances only. For this reason, the method can be applied also when the computation of the joint distribution is difficult or inconvenient. The proposed methodology is investigated by simulation studies and applied to real data about adult male Cape Dwarf Chameleons. © 2013, The International Biometric Society.

Scale dependence in species turnover reflects variance in species occupancy.

PubMed

McGlinn, Daniel J; Hurlbert, Allen H

2012-02-01

Patterns of species turnover may reflect the processes driving community dynamics across scales. While the majority of studies on species turnover have examined pairwise comparison metrics (e.g., the average Jaccard dissimilarity), it has been proposed that the species-area relationship (SAR) also offers insight into patterns of species turnover because these two patterns may be analytically linked. However, these previous links only apply in a special case where turnover is scale invariant, and we demonstrate across three different plant communities that over 90% of the pairwise turnover values are larger than expected based on scale-invariant predictions from the SAR. Furthermore, the degree of scale dependence in turnover was negatively related to the degree of variance in the occupancy frequency distribution (OFD). These findings suggest that species turnover diverges from scale invariance, and as such pairwise turnover and the slope of the SAR are not redundant. Furthermore, models developed to explain the OFD should be linked with those developed to explain species turnover to achieve a more unified understanding of community structure.

Pairwise velocities in the "Running FLRW" cosmological model

NASA Astrophysics Data System (ADS)

Bibiano, Antonio; Croton, Darren J.

2017-05-01

We present an analysis of the pairwise velocity statistics from a suite of cosmological N-body simulations describing the 'Running Friedmann-Lemaître-Robertson-Walker' (R-FLRW) cosmological model. This model is based on quantum field theory in a curved space-time and extends Λ cold dark matter (CDM) with a time-evolving vacuum energy density, ρ _Λ. To enforce local conservation of matter, a time-evolving gravitational coupling is also included. Our results constitute the first study of velocities in the R-FLRW cosmology, and we also compare with other dark energy simulations suites, repeating the same analysis. We find a strong degeneracy between the pairwise velocity and σ8 at z = 0 for almost all scenarios considered, which remains even when we look back to epochs as early as z = 2. We also investigate various coupled dark energy models, some of which show minimal degeneracy, and reveal interesting deviations from ΛCDM that could be readily exploited by future cosmological observations to test and further constrain our understanding of dark energy.

Clear and Measurable Signature of Modified Gravity in the Galaxy Velocity Field

NASA Astrophysics Data System (ADS)

Hellwing, Wojciech A.; Barreira, Alexandre; Frenk, Carlos S.; Li, Baojiu; Cole, Shaun

2014-06-01

The velocity field of dark matter and galaxies reflects the continued action of gravity throughout cosmic history. We show that the low-order moments of the pairwise velocity distribution v12 are a powerful diagnostic of the laws of gravity on cosmological scales. In particular, the projected line-of-sight galaxy pairwise velocity dispersion σ12(r) is very sensitive to the presence of modified gravity. Using a set of high-resolution N-body simulations, we compute the pairwise velocity distribution and its projected line-of-sight dispersion for a class of modified gravity theories: the chameleon f(R) gravity and Galileon gravity (cubic and quartic). The velocities of dark matter halos with a wide range of masses would exhibit deviations from general relativity at the (5-10)σ level. We examine strategies for detecting these deviations in galaxy redshift and peculiar velocity surveys. If detected, this signature would be a "smoking gun" for modified gravity.

Emergent behaviors of the Schrödinger-Lohe model on cooperative-competitive networks

NASA Astrophysics Data System (ADS)

Huh, Hyungjin; Ha, Seung-Yeal; Kim, Dohyun

2017-12-01

We present several sufficient frameworks leading to the emergent behaviors of the coupled Schrödinger-Lohe (S-L) model under the same one-body external potential on cooperative-competitive networks. The S-L model was first introduced as a possible phenomenological model exhibiting quantum synchronization and its emergent dynamics on all-to-all cooperative networks has been treated via two distinct approaches, Lyapunov functional approach and the finite-dimensional reduction based on pairwise correlations. In this paper, we further generalize the finite-dimensional dynamical systems approach for pairwise correlation functions on cooperative-competitive networks and provide several sufficient frameworks leading to the collective exponential synchronization. For small systems consisting of three and four quantum subsystem, we also show that the system for pairwise correlations can be reduced to the Lotka-Volterra model with cooperative and competitive interactions, in which lots of interesting dynamical patterns appear, e.g., existence of closed orbits and limit-cycles.

Cosmological Constraints from Galaxy Cluster Velocity Statistics

NASA Astrophysics Data System (ADS)

Bhattacharya, Suman; Kosowsky, Arthur

2007-04-01

Future microwave sky surveys will have the sensitivity to detect the kinematic Sunyaev-Zeldovich signal from moving galaxy clusters, thus providing a direct measurement of their line-of-sight peculiar velocity. We show that cluster peculiar velocity statistics applied to foreseeable surveys will put significant constraints on fundamental cosmological parameters. We consider three statistical quantities that can be constructed from a cluster peculiar velocity catalog: the probability density function, the mean pairwise streaming velocity, and the pairwise velocity dispersion. These quantities are applied to an envisioned data set that measures line-of-sight cluster velocities with normal errors of 100 km s-1 for all clusters with masses larger than 1014 Msolar over a sky area of up to 5000 deg2. A simple Fisher matrix analysis of this survey shows that the normalization of the matter power spectrum and the dark energy equation of state can be constrained to better than 10%, and that the Hubble constant and the primordial power spectrum index can be constrained to a few percent, independent of any other cosmological observations. We also find that the current constraint on the power spectrum normalization can be improved by more than a factor of 2 using data from a 400 deg2 survey and WMAP third-year priors. We also show how the constraints on cosmological parameters change if cluster velocities are measured with normal errors of 300 km s-1.

Caveats for the spatial arrangement method: Comment on Hout, Goldinger, and Ferguson (2013).

PubMed

Verheyen, Steven; Voorspoels, Wouter; Vanpaemel, Wolf; Storms, Gert

2016-03-01

The gold standard among proximity data collection methods for multidimensional scaling is the (dis)similarity rating of pairwise presented stimuli. A drawback of the pairwise method is its lengthy duration, which may cause participants to change their strategy over time, become fatigued, or disengage altogether. Hout, Goldinger, and Ferguson (2013) recently made a case for the Spatial Arrangement Method (SpAM) as an alternative to the pairwise method, arguing that it is faster and more engaging. SpAM invites participants to directly arrange stimuli on a computer screen such that the interstimuli distances are proportional to psychological proximity. Based on a reanalysis of the Hout et al. (2013), data we identify three caveats for SpAM. An investigation of the distributional characteristics of the SpAM proximity data reveals that the spatial nature of SpAM imposes structure on the data, invoking a bias against featural representations. Individual-differences scaling of the SpAM proximity data reveals that the two-dimensional nature of SpAM allows individuals to only communicate two dimensions of variation among stimuli properly, invoking a bias against high-dimensional scaling representations. Monte Carlo simulations indicate that in order to obtain reliable estimates of the group average, SpAM requires more individuals to be tested. We conclude with an overview of considerations that can inform the choice between SpAM and the pairwise method and offer suggestions on how to overcome their respective limitations. (c) 2016 APA, all rights reserved).

SFESA: a web server for pairwise alignment refinement by secondary structure shifts.

PubMed

Tong, Jing; Pei, Jimin; Grishin, Nick V

2015-09-03

Protein sequence alignment is essential for a variety of tasks such as homology modeling and active site prediction. Alignment errors remain the main cause of low-quality structure models. A bioinformatics tool to refine alignments is needed to make protein alignments more accurate. We developed the SFESA web server to refine pairwise protein sequence alignments. Compared to the previous version of SFESA, which required a set of 3D coordinates for a protein, the new server will search a sequence database for the closest homolog with an available 3D structure to be used as a template. For each alignment block defined by secondary structure elements in the template, SFESA evaluates alignment variants generated by local shifts and selects the best-scoring alignment variant. A scoring function that combines the sequence score of profile-profile comparison and the structure score of template-derived contact energy is used for evaluation of alignments. PROMALS pairwise alignments refined by SFESA are more accurate than those produced by current advanced alignment methods such as HHpred and CNFpred. In addition, SFESA also improves alignments generated by other software. SFESA is a web-based tool for alignment refinement, designed for researchers to compute, refine, and evaluate pairwise alignments with a combined sequence and structure scoring of alignment blocks. To our knowledge, the SFESA web server is the only tool that refines alignments by evaluating local shifts of secondary structure elements. The SFESA web server is available at http://prodata.swmed.edu/sfesa.

Redshift-space distortions of group and galaxy correlations in the Updated Zwicky Catalog

NASA Astrophysics Data System (ADS)

Padilla, N. D.; Merchán, M.; García Lambas, D.; Maia, M. G.

We calculate two-point correlation functions of galaxies and groups of galaxies selected in three dimensions from the Updated Zwicky Galaxy Catalog - (UZC). The redshift space distortion of the correlation function ξ(σ,π) in the directions parallel and perpendicular to the line of sight, induced by pairwise group peculiar velocities is evaluated. Two methods are used to characterize the pairwise velocity field. The first method consists in fitting the observed ξ(σ,π) with a distorted model with an exponential pairwise velocity distribution, in fixed σ bins. The second method compares the contours of constant predicted correlation function of this model with the data. The results are consistent with a one-dimensional pairwise rms velocity dispersion of groups 1/2=250 ± 110 km/s. We find that UZC galaxy pairwise velocity dispersion is 1/2 = 460 ± 35 km/s. Such findings point towards a smoothly varying peculiar velocity field from galaxies to systems of galaxies, a expected in a hierarchical scenario of structure formation. We estimate the real-space correlation function in the power-law approximation ξ(r)=(r/r0)γ for groups and galaxies in UZC. We obtain the correlation length, r0, from the projected correlation function W(σ)=∫- ∞∞ξ(σ,π)dπ= 2 ∫0∞ ξ(σ,π) dπ using the values of γ derived from the correlation function in projected separations ω(σ). The best fitting parameters are γ=-1.89 ± 0.17 and r0=9.7 ± 4.5 Mpc h-1 for groups, and γ=-2.00 ± 0.03, r0=5.29 ± 0.21 Mpc h-1 for galaxies. We carried out an estimate of the parameter β= Ω0.6/b for groups and galaxies using the linear approximation regime relating the real and the redshift-space correlation functions. We find βgalaxies=0.51 ± 0.15 for galaxies, in agreement with previous works, while for groups we obtain a noisy estimate β < 1.5. We have tested our methods on mock UZC catalogs taken from N-body simulations. The results of these tests show that the conclusions derived from the application of our methods to the observations are reliable and provide a suitable characterization of the spatial correlation and pairwise velocities of groups and galaxies. We also find that the second method, developed in this work, provides more stable and precise results.

Population activity statistics dissect subthreshold and spiking variability in V1.

PubMed

Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

2017-07-01

Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of variability. Our work shows that stimulus-dependent changes in pairwise but not in single-cell statistics can differentiate between two widely used models of neuronal variability. Contrasting model predictions with neuronal data provides hints on the noise sources in spiking and provides constraints on statistical models of population activity. Copyright © 2017 the American Physiological Society.

Dunkl operator, integrability, and pairwise scattering in rational Calogero model

NASA Astrophysics Data System (ADS)

Karakhanyan, David

2017-05-01

The integrability of the Calogero model can be expressed as zero curvature condition using Dunkl operators. The corresponding flat connections are non-local gauge transformations, which map the Calogero wave functions to symmetrized wave functions of the set of N free particles, i.e. it relates the corresponding scattering matrices to each other. The integrability of the Calogero model implies that any k-particle scattering is reduced to successive pairwise scatterings. The consistency condition of this requirement is expressed by the analog of the Yang-Baxter relation.

Causal analysis of ordinal treatments and binary outcomes under truncation by death.

PubMed

Wang, Linbo; Richardson, Thomas S; Zhou, Xiao-Hua

2017-06-01

It is common that in multi-arm randomized trials, the outcome of interest is "truncated by death," meaning that it is only observed or well-defined conditioning on an intermediate outcome. In this case, in addition to pairwise contrasts, the joint inference for all treatment arms is also of interest. Under a monotonicity assumption we present methods for both pairwise and joint causal analyses of ordinal treatments and binary outcomes in presence of truncation by death. We illustrate via examples the appropriateness of our assumptions in different scientific contexts.

The effective colloid interaction in the Asakura-Oosawa model. Assessment of non-pairwise terms from the virial expansion.

PubMed

Santos, Andrés; López de Haro, Mariano; Fiumara, Giacomo; Saija, Franz

2015-06-14

The relevance of neglecting three- and four-body interactions in the coarse-grained version of the Asakura-Oosawa model is examined. A mapping between the first few virial coefficients of the binary nonadditive hard-sphere mixture representative of this model and those arising from the coarse-grained (pairwise) depletion potential approximation allows for a quantitative evaluation of the effect of such interactions. This turns out to be especially important for large size ratios and large reservoir polymer packing fractions.

Multimodal Discriminative Binary Embedding for Large-Scale Cross-Modal Retrieval.

PubMed

Wang, Di; Gao, Xinbo; Wang, Xiumei; He, Lihuo; Yuan, Bo

2016-10-01

Multimodal hashing, which conducts effective and efficient nearest neighbor search across heterogeneous data on large-scale multimedia databases, has been attracting increasing interest, given the explosive growth of multimedia content on the Internet. Recent multimodal hashing research mainly aims at learning the compact binary codes to preserve semantic information given by labels. The overwhelming majority of these methods are similarity preserving approaches which approximate pairwise similarity matrix with Hamming distances between the to-be-learnt binary hash codes. However, these methods ignore the discriminative property in hash learning process, which results in hash codes from different classes undistinguished, and therefore reduces the accuracy and robustness for the nearest neighbor search. To this end, we present a novel multimodal hashing method, named multimodal discriminative binary embedding (MDBE), which focuses on learning discriminative hash codes. First, the proposed method formulates the hash function learning in terms of classification, where the binary codes generated by the learned hash functions are expected to be discriminative. And then, it exploits the label information to discover the shared structures inside heterogeneous data. Finally, the learned structures are preserved for hash codes to produce similar binary codes in the same class. Hence, the proposed MDBE can preserve both discriminability and similarity for hash codes, and will enhance retrieval accuracy. Thorough experiments on benchmark data sets demonstrate that the proposed method achieves excellent accuracy and competitive computational efficiency compared with the state-of-the-art methods for large-scale cross-modal retrieval task.

Qualitative and quantitative evaluation of solvent systems for countercurrent separation.

PubMed

Friesen, J Brent; Ahmed, Sana; Pauli, Guido F

2015-01-16

Rational solvent system selection for countercurrent chromatography and centrifugal partition chromatography technology (collectively known as countercurrent separation) studies continues to be a scientific challenge as the fundamental questions of comparing polarity range and selectivity within a solvent system family and between putative orthogonal solvent systems remain unanswered. The current emphasis on metabolomic investigations and analysis of complex mixtures necessitates the use of successive orthogonal countercurrent separation (CS) steps as part of complex fractionation protocols. Addressing the broad range of metabolite polarities demands development of new CS solvent systems with appropriate composition, polarity (π), selectivity (σ), and suitability. In this study, a mixture of twenty commercially available natural products, called the GUESSmix, was utilized to evaluate both solvent system polarity and selectively characteristics. Comparisons of GUESSmix analyte partition coefficient (K) values give rise to a measure of solvent system polarity range called the GUESSmix polarity index (GUPI). Solvatochromic dye and electrical permittivity measurements were also evaluated in quantitatively assessing solvent system polarity. The relative selectivity of solvent systems were evaluated with the GUESSmix by calculating the pairwise resolution (αip), the number of analytes found in the sweet spot (Nsw), and the pairwise resolution of those sweet spot analytes (αsw). The combination of these parameters allowed for both intra- and inter-family comparison of solvent system selectivity. Finally, 2-dimensional reciprocal shifted symmetry plots (ReSS(2)) were created to visually compare both the polarities and selectivities of solvent system pairs. This study helps to pave the way to the development of new solvent systems that are amenable to successive orthogonal CS protocols employed in metabolomic studies. Copyright © 2014 Elsevier B.V. All rights reserved.

Molecular simulations of the pairwise interaction of monoclonal antibodies.

PubMed

Lapelosa, Mauro; Patapoff, Thomas W; Zarraga, Isidro E

2014-11-20

Molecular simulations are employed to compute the free energy of pairwise monoclonal antibodies (mAbs) association using a conformational sampling algorithm with a scoring function. The work reported here is aimed at investigating the mAb-mAb association driven by weak interactions with a computational method capable of predicting experimental observations of low binding affinity. The simulations are able to explore the free energy landscape. A steric interaction component, electrostatic interactions, and a nonpolar component of the free energy form the energy scoring function. Electrostatic interactions are calculated by solving the Poisson-Boltzmann equation. The nonpolar component is derived from the van der Waals interactions upon close contact of the protein surfaces. Two mAbs with similar IgG1 framework but with small sequence differences, mAb1 and mAb2, are considered for their different viscosity and propensity to form a weak interacting dimer. mAb1 presents favorable free energy of association at pH 6 with 15 mM of ion concentration reproducing experimental trends of high viscosity and dimer formation at high concentration. Free energy landscape and minimum free energy configurations of the dimer, as well as the second virial coefficient (B22) values are calculated. The energy distributions for mAb1 are obtained, and the most probable configurations are seen to be consistent with experimental measurements. In contrast, mAb2 shows an unfavorable average free energy at the same buffer conditions due to poor electrostatic complementarity, and reversible dimer configurations with favorable free energy are found to be unlikely. Finally, the simulations of the mAb association dynamics provide insights on the self-association responsible for bulk solution behavior and aggregation, which are important to the processing and the quality of biopharmaceuticals.

Blood-Based Gene Expression Profiles Models for Classification of Subsyndromal Symptomatic Depression and Major Depressive Disorder

PubMed Central

Yu, Shunying; Yuan, Chengmei; Hong, Wu; Wang, Zuowei; Cui, Jian; Shi, Tieliu; Fang, Yiru

2012-01-01

Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and also lead to significant psychosocial functional impairment as same as major depressive disorder (MDD). Several studies have suggested that SSD is a transitory phenomena in the depression spectrum and is thus considered a subtype of depression. However, the pathophysioloy of depression remain largely obscure and studies on SSD are limited. The present study compared the expression profile and made the classification with the leukocytes by using whole-genome cRNA microarrays among drug-free first-episode subjects with SSD, MDD, and matched controls (8 subjects in each group). Support vector machines (SVMs) were utilized for training and testing on candidate signature expression profiles from signature selection step. Firstly, we identified 63 differentially expressed SSD signatures in contrast to control (P< = 5.0E-4) and 30 differentially expressed MDD signatures in contrast to control, respectively. Then, 123 gene signatures were identified with significantly differential expression level between SSD and MDD. Secondly, in order to conduct priority selection for biomarkers for SSD and MDD together, we selected top gene signatures from each group of pair-wise comparison results, and merged the signatures together to generate better profiles used for clearly classify SSD and MDD sets in the same time. In details, we tried different combination of signatures from the three pair-wise compartmental results and finally determined 48 gene expression signatures with 100% accuracy. Our finding suggested that SSD and MDD did not exhibit the same expressed genome signature with peripheral blood leukocyte, and blood cell–derived RNA of these 48 gene models may have significant value for performing diagnostic functions and classifying SSD, MDD, and healthy controls. PMID:22348066

Family-Based Benchmarking of Copy Number Variation Detection Software.

PubMed

Nutsua, Marcel Elie; Fischer, Annegret; Nebel, Almut; Hofmann, Sylvia; Schreiber, Stefan; Krawczak, Michael; Nothnagel, Michael

2015-01-01

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

Interbreed variation in serum serotonin (5-hydroxytryptamine) concentration in healthy dogs.

PubMed

Höglund, K; Häggström, J; Hanås, S; Merveille, A-C; Gouni, V; Wiberg, M; Lundgren Willesen, J; Entee, K Mc; Mejer Sørensen, L; Tiret, L; Seppälä, E H; Lohi, H; Chetboul, V; Fredholm, M; Lequarré, A-S; Ljungvall, I

2018-06-16

Serotonin (5-hydroxytryptamine [5-HT]) has several biological functions. In different species, excessive 5-HT has been linked to valvular lesions, similar to those seen in dogs with myxomatous mitral valve disease. Previous studies suggest higher 5-HT in healthy Cavalier King Charles Spaniels (CKCSs), a breed highly affected by myxomatous mitral valve disease, compared to other breeds. To investigate potential interbreed variation in serum 5-HT in healthy dogs. 483 healthy dogs of nine breeds aged 1-7 years. Dogs were examined at five European centers. Absence of cardiovascular, organ-related, or systemic diseases was ensured by thorough clinical investigations including echocardiography. Serum was frozen and later analyzed by enzyme-linked immunosorbent assay (ELISA). Median 5-HT concentration was 252.5 (interquartile range = 145.5-390.6) ng/mL. Overall breed difference was found (p<0.0001), and 42% of pairwise breed comparisons were significant. Univariate regression analysis showed association between serum 5-HT concentration and breed, center of examination, storage time, and sex, with higher 5-HT in females. In multiple regression analysis, the final model had an adjusted R 2 of 0.27 with breed (p<0.0001), center (p<0.0001), and storage time (p=0.014) remaining significant. Within centers, overall breed differences were found at 3/5 centers (p≤0.028), and pairwise comparisons within those centers showed breed differences in 42% of comparisons. Among the included breeds, Newfoundlands, Belgian Shepherds and CKCSs had highest 5-HT concentrations. Interbreed variation in serum 5-HT concentration was found in healthy dogs aged 1-7 years. These differences should be taken into account when designing clinical studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia.

PubMed

Damaraju, E; Allen, E A; Belger, A; Ford, J M; McEwen, S; Mathalon, D H; Mueller, B A; Pearlson, G D; Potkin, S G; Preda, A; Turner, J A; Vaidya, J G; van Erp, T G; Calhoun, V D

2014-01-01

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical-subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivity with sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences.

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

PubMed Central

Damaraju, E.; Allen, E.A.; Belger, A.; Ford, J.M.; McEwen, S.; Mathalon, D.H.; Mueller, B.A.; Pearlson, G.D.; Potkin, S.G.; Preda, A.; Turner, J.A.; Vaidya, J.G.; van Erp, T.G.; Calhoun, V.D.

2014-01-01

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical–subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivity with sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences. PMID:25161896

Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers.

PubMed

Galpert, Deborah; Fernández, Alberto; Herrera, Francisco; Antunes, Agostinho; Molina-Ruiz, Reinaldo; Agüero-Chapin, Guillermin

2018-05-03

The development of new ortholog detection algorithms and the improvement of existing ones are of major importance in functional genomics. We have previously introduced a successful supervised pairwise ortholog classification approach implemented in a big data platform that considered several pairwise protein features and the low ortholog pair ratios found between two annotated proteomes (Galpert, D et al., BioMed Research International, 2015). The supervised models were built and tested using a Saccharomycete yeast benchmark dataset proposed by Salichos and Rokas (2011). Despite several pairwise protein features being combined in a supervised big data approach; they all, to some extent were alignment-based features and the proposed algorithms were evaluated on a unique test set. Here, we aim to evaluate the impact of alignment-free features on the performance of supervised models implemented in the Spark big data platform for pairwise ortholog detection in several related yeast proteomes. The Spark Random Forest and Decision Trees with oversampling and undersampling techniques, and built with only alignment-based similarity measures or combined with several alignment-free pairwise protein features showed the highest classification performance for ortholog detection in three yeast proteome pairs. Although such supervised approaches outperformed traditional methods, there were no significant differences between the exclusive use of alignment-based similarity measures and their combination with alignment-free features, even within the twilight zone of the studied proteomes. Just when alignment-based and alignment-free features were combined in Spark Decision Trees with imbalance management, a higher success rate (98.71%) within the twilight zone could be achieved for a yeast proteome pair that underwent a whole genome duplication. The feature selection study showed that alignment-based features were top-ranked for the best classifiers while the runners-up were alignment-free features related to amino acid composition. The incorporation of alignment-free features in supervised big data models did not significantly improve ortholog detection in yeast proteomes regarding the classification qualities achieved with just alignment-based similarity measures. However, the similarity of their classification performance to that of traditional ortholog detection methods encourages the evaluation of other alignment-free protein pair descriptors in future research.

Level of literacy and dementia: A secondary post-hoc analysis from North-West India.

PubMed

Raina, Sunil Kumar; Chander, Vishav; Kumar, Dinesh; Raina, Sujeet; Bhardwaj, Ashok

2014-10-01

A relation between literacy and dementia has been studied in past and an association has been documented. This is in spite of some studies pointing to the contrary. The current study was aimed at investigating the influence of level of literacy on dementia in a sample stratified by geography (Migrant, Urban, Rural and Tribal areas of sub-Himalayan state of Himachal Pradesh, India). The study was based on post-hoc analysis of data obtained from a study conducted on elderly population (60 years and above) from selected geographical areas (Migrant, Urban, Rural and Tribal) of Himachal Pradesh state in North-west India. Analysis of variance revealed an effect of education on cognitive scores [F = 2.823, P =0.01], however, post-hoc Tukey's HSD test did not reveal any significant pairwise comparisons. The possibility that education effects dementia needs further evaluation, more so in Indian context.

Test of mutually unbiased bases for six-dimensional photonic quantum systems

PubMed Central

D'Ambrosio, Vincenzo; Cardano, Filippo; Karimi, Ebrahim; Nagali, Eleonora; Santamato, Enrico; Marrucci, Lorenzo; Sciarrino, Fabio

2013-01-01

In quantum information, complementarity of quantum mechanical observables plays a key role. The eigenstates of two complementary observables form a pair of mutually unbiased bases (MUBs). More generally, a set of MUBs consists of bases that are all pairwise unbiased. Except for specific dimensions of the Hilbert space, the maximal sets of MUBs are unknown in general. Even for a dimension as low as six, the identification of a maximal set of MUBs remains an open problem, although there is strong numerical evidence that no more than three simultaneous MUBs do exist. Here, by exploiting a newly developed holographic technique, we implement and test different sets of three MUBs for a single photon six-dimensional quantum state (a “qusix”), encoded exploiting polarization and orbital angular momentum of photons. A close agreement is observed between theory and experiments. Our results can find applications in state tomography, quantitative wave-particle duality, quantum key distribution. PMID:24067548

Test of mutually unbiased bases for six-dimensional photonic quantum systems.

PubMed

D'Ambrosio, Vincenzo; Cardano, Filippo; Karimi, Ebrahim; Nagali, Eleonora; Santamato, Enrico; Marrucci, Lorenzo; Sciarrino, Fabio

2013-09-25

In quantum information, complementarity of quantum mechanical observables plays a key role. The eigenstates of two complementary observables form a pair of mutually unbiased bases (MUBs). More generally, a set of MUBs consists of bases that are all pairwise unbiased. Except for specific dimensions of the Hilbert space, the maximal sets of MUBs are unknown in general. Even for a dimension as low as six, the identification of a maximal set of MUBs remains an open problem, although there is strong numerical evidence that no more than three simultaneous MUBs do exist. Here, by exploiting a newly developed holographic technique, we implement and test different sets of three MUBs for a single photon six-dimensional quantum state (a "qusix"), encoded exploiting polarization and orbital angular momentum of photons. A close agreement is observed between theory and experiments. Our results can find applications in state tomography, quantitative wave-particle duality, quantum key distribution.

Observation of Genuine Three-Photon Interference

NASA Astrophysics Data System (ADS)

Agne, Sascha; Kauten, Thomas; Jin, Jeongwan; Meyer-Scott, Evan; Salvail, Jeff Z.; Hamel, Deny R.; Resch, Kevin J.; Weihs, Gregor; Jennewein, Thomas

2017-04-01

Multiparticle quantum interference is critical for our understanding and exploitation of quantum information, and for fundamental tests of quantum mechanics. A remarkable example of multi-partite correlations is exhibited by the Greenberger-Horne-Zeilinger (GHZ) state. In a GHZ state, three particles are correlated while no pairwise correlation is found. The manifestation of these strong correlations in an interferometric setting has been studied theoretically since 1990 but no three-photon GHZ interferometer has been realized experimentally. Here we demonstrate three-photon interference that does not originate from two-photon or single photon interference. We observe phase-dependent variation of three-photon coincidences with (92.7 ±4.6 )% visibility in a generalized Franson interferometer using energy-time entangled photon triplets. The demonstration of these strong correlations in an interferometric setting provides new avenues for multiphoton interferometry, fundamental tests of quantum mechanics, and quantum information applications in higher dimensions.

Analysis and observation of moving domain fronts in a ring of coupled electronic self-oscillators

NASA Astrophysics Data System (ADS)

English, L. Q.; Zampetaki, A.; Kevrekidis, P. G.; Skowronski, K.; Fritz, C. B.; Abdoulkary, Saidou

2017-10-01

In this work, we consider a ring of coupled electronic (Wien-bridge) oscillators from a perspective combining modeling, simulation, and experimental observation. Following up on earlier work characterizing the pairwise interaction of Wien-bridge oscillators by Kuramoto-Sakaguchi phase dynamics, we develop a lattice model for a chain thereof, featuring an exponentially decaying spatial kernel. We find that for certain values of the Sakaguchi parameter α, states of traveling phase-domain fronts involving the coexistence of two clearly separated regions of distinct dynamical behavior, can establish themselves in the ring lattice. Experiments and simulations show that stationary coexistence domains of synchronization only manifest themselves with the introduction of a local impurity; here an incoherent cluster of oscillators can arise reminiscent of the chimera states in a range of systems with homogeneous oscillators and suitable nonlocal interactions between them.

Quantum spin dynamics with pairwise-tunable, long-range interactions

PubMed Central

Hung, C.-L.; González-Tudela, Alejandro; Cirac, J. Ignacio; Kimble, H. J.

2016-01-01

We present a platform for the simulation of quantum magnetism with full control of interactions between pairs of spins at arbitrary distances in 1D and 2D lattices. In our scheme, two internal atomic states represent a pseudospin for atoms trapped within a photonic crystal waveguide (PCW). With the atomic transition frequency aligned inside a band gap of the PCW, virtual photons mediate coherent spin–spin interactions between lattice sites. To obtain full control of interaction coefficients at arbitrary atom–atom separations, ground-state energy shifts are introduced as a function of distance across the PCW. In conjunction with auxiliary pump fields, spin-exchange versus atom–atom separation can be engineered with arbitrary magnitude and phase, and arranged to introduce nontrivial Berry phases in the spin lattice, thus opening new avenues for realizing topological spin models. We illustrate the broad applicability of our scheme by explicit construction for several well-known spin models. PMID:27496329

Diagnostic Capability of Peripapillary Retinal Volume Measurements in Glaucoma.

PubMed

Simavli, Huseyin; Poon, Linda Yi-Chieh; Que, Christian J; Liu, Yingna; Akduman, Mustafa; Tsikata, Edem; de Boer, Johannes F; Chen, Teresa C

2017-06-01

To determine the diagnostic capability of spectral domain optical coherence tomography peripapillary retinal volume (RV) measurements. A total of 156 patients, 89 primary open-angle glaucoma and 67 normal subjects, were recruited. Spectral domain optical coherence tomography peripapillary RV was calculated for 4 quadrants using 3 annuli of varying scan circle diameters: outer circumpapillary annuli of circular grids 1, 2, and 3 (OCA1, OCA2, OCA3). Area under the receiver operating characteristic curves and pairwise comparisons of receiver operating characteristic (ROC) curves were performed to determine which quadrants were best for diagnosing primary open-angle glaucoma. The pairwise comparisons of the best ROC curves for RV and retinal nerve fiber layer (RNFL) were performed. The artifact rates were analyzed. Pairwise comparisons showed that the smaller annuli OCA1 and OCA2 had better diagnostic performance than the largest annulus OCA3 (P<0.05 for all quadrants). OCA1 and OCA2 had similar diagnostic performance, except for the inferior quadrant which was better for OCA1 (P=0.0033). The pairwise comparisons of the best ROC curves for RV and RNFL were not statistically significant. RV measurements had lower rates of artifacts at 7.4% while RNFL measurements had higher rates at 42.9%. Peripapillary RV measurements have excellent ability for diagnosing not only glaucoma patients but also a subset of early glaucoma patients. The inferior quadrant of peripapillary annulus OCA1 demonstrated the best diagnostic capability for both glaucoma and early glaucoma. The diagnostic ability of RV is comparable with that of RNFL parameters in glaucoma but with lower artifact rates.

Diagnostic Capability of Peripapillary Retinal Volume Measurements in Glaucoma

PubMed Central

Simavli, Huseyin; Poon, Linda Yi-Chieh; Que, Christian John; Liu, Yingna; Akduman, Mustafa; Tsikata, Edem; de Boer, Johannes F.; Chen, Teresa C.

2017-01-01

Purpose To determine the diagnostic capability of spectral domain optical coherence tomography (SD-OCT) peripapillary retinal volume (RV) measurements. Materials and Methods A total of 156 patients, 89 primary open angle (POAG) and 67 normal subjects, were recruited. SD-OCT peripapillary RV was calculated for four quadrants using 3 annuli of varying scan circle diameters: outer circumpapillary annuli of circular grids 1, 2, and 3 (OCA1, OCA2, OCA3). Area under the receiver operating characteristic (AUROC) curves and pairwise comparisons of receiver operating characteristic (ROC) curves were performed to determine which quadrants were best for diagnosing POAG. The pairwise comparisons of the best ROC curves for RV and RNFL were performed. The artifact rates were analyzed. Results Pairwise comparisons showed that the smaller annuli OCA1 and OCA2 had better diagnostic performance than the largest annulus OCA3 (p<0.05 for all quadrants). OCA1 and OCA2 had similar diagnostic performance, except for the inferior quadrant which was better for OCA1 (p=0.0033).The pairwise comparisons of the best ROC curves for RV and RNFL were not statistically significant. Retinal volume measurements had lower rates of artifacts at 7.4% while RNFL measurements had higher rates at 42.9%. Conclusion Peripapillary RV measurements have excellent ability for diagnosing not only glaucoma patients but also a subset of early glaucoma patients. The inferior quadrant of peripapillary annulus OCA1 demonstrated the best diagnostic capability for both glaucoma and early glaucoma. The diagnostic ability of RV is comparable to that of RNFL parameters in glaucoma but with lower artifact rates. PMID:28079657

Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations

PubMed Central

van Albada, Sacha Jennifer; Helias, Moritz; Diesmann, Markus

2015-01-01

Network models are routinely downscaled compared to nature in terms of numbers of nodes or edges because of a lack of computational resources, often without explicit mention of the limitations this entails. While reliable methods have long existed to adjust parameters such that the first-order statistics of network dynamics are conserved, here we show that limitations already arise if also second-order statistics are to be maintained. The temporal structure of pairwise averaged correlations in the activity of recurrent networks is determined by the effective population-level connectivity. We first show that in general the converse is also true and explicitly mention degenerate cases when this one-to-one relationship does not hold. The one-to-one correspondence between effective connectivity and the temporal structure of pairwise averaged correlations implies that network scalings should preserve the effective connectivity if pairwise averaged correlations are to be held constant. Changes in effective connectivity can even push a network from a linearly stable to an unstable, oscillatory regime and vice versa. On this basis, we derive conditions for the preservation of both mean population-averaged activities and pairwise averaged correlations under a change in numbers of neurons or synapses in the asynchronous regime typical of cortical networks. We find that mean activities and correlation structure can be maintained by an appropriate scaling of the synaptic weights, but only over a range of numbers of synapses that is limited by the variance of external inputs to the network. Our results therefore show that the reducibility of asynchronous networks is fundamentally limited. PMID:26325661

Unjamming in models with analytic pairwise potentials

NASA Astrophysics Data System (ADS)

Kooij, Stefan; Lerner, Edan

2017-06-01

Canonical models for studying the unjamming scenario in systems of soft repulsive particles assume pairwise potentials with a sharp cutoff in the interaction range. The sharp cutoff renders the potential nonanalytic but makes it possible to describe many properties of the solid in terms of the coordination number z , which has an unambiguous definition in these cases. Pairwise potentials without a sharp cutoff in the interaction range have not been studied in this context, but should in fact be considered to understand the relevance of the unjamming phenomenology in systems where such a cutoff is not present. In this work we explore two systems with such interactions: an inverse power law and an exponentially decaying pairwise potential, with the control parameters being the exponent (of the inverse power law) for the former and the number density for the latter. Both systems are shown to exhibit the characteristic features of the unjamming transition, among which are the vanishing of the shear-to-bulk modulus ratio and the emergence of an excess of low-frequency vibrational modes. We establish a relation between the pressure-to-bulk modulus ratio and the distance to unjamming in each of our model systems. This allows us to predict the dependence of other key observables on the distance to unjamming. Our results provide the means for a quantitative estimation of the proximity of generic glass-forming models to the unjamming transition in the absence of a clear-cut definition of the coordination number and highlight the general irrelevance of nonaffine contributions to the bulk modulus.

Unjamming in models with analytic pairwise potentials.

PubMed

Kooij, Stefan; Lerner, Edan

2017-06-01

Canonical models for studying the unjamming scenario in systems of soft repulsive particles assume pairwise potentials with a sharp cutoff in the interaction range. The sharp cutoff renders the potential nonanalytic but makes it possible to describe many properties of the solid in terms of the coordination number z, which has an unambiguous definition in these cases. Pairwise potentials without a sharp cutoff in the interaction range have not been studied in this context, but should in fact be considered to understand the relevance of the unjamming phenomenology in systems where such a cutoff is not present. In this work we explore two systems with such interactions: an inverse power law and an exponentially decaying pairwise potential, with the control parameters being the exponent (of the inverse power law) for the former and the number density for the latter. Both systems are shown to exhibit the characteristic features of the unjamming transition, among which are the vanishing of the shear-to-bulk modulus ratio and the emergence of an excess of low-frequency vibrational modes. We establish a relation between the pressure-to-bulk modulus ratio and the distance to unjamming in each of our model systems. This allows us to predict the dependence of other key observables on the distance to unjamming. Our results provide the means for a quantitative estimation of the proximity of generic glass-forming models to the unjamming transition in the absence of a clear-cut definition of the coordination number and highlight the general irrelevance of nonaffine contributions to the bulk modulus.

DincRNA: a comprehensive web-based bioinformatics toolkit for exploring disease associations and ncRNA function.

PubMed

Cheng, Liang; Hu, Yang; Sun, Jie; Zhou, Meng; Jiang, Qinghua

2018-06-01

DincRNA aims to provide a comprehensive web-based bioinformatics toolkit to elucidate the entangled relationships among diseases and non-coding RNAs (ncRNAs) from the perspective of disease similarity. The quantitative way to illustrate relationships of pair-wise diseases always depends on their molecular mechanisms, and structures of the directed acyclic graph of Disease Ontology (DO). Corresponding methods for calculating similarity of pair-wise diseases involve Resnik's, Lin's, Wang's, PSB and SemFunSim methods. Recently, disease similarity was validated suitable for calculating functional similarities of ncRNAs and prioritizing ncRNA-disease pairs, and it has been widely applied for predicting the ncRNA function due to the limited biological knowledge from wet lab experiments of these RNAs. For this purpose, a large number of algorithms and priori knowledge need to be integrated. e.g. 'pair-wise best, pairs-average' (PBPA) and 'pair-wise all, pairs-maximum' (PAPM) methods for calculating functional similarities of ncRNAs, and random walk with restart (RWR) method for prioritizing ncRNA-disease pairs. To facilitate the exploration of disease associations and ncRNA function, DincRNA implemented all of the above eight algorithms based on DO and disease-related genes. Currently, it provides the function to query disease similarity scores, miRNA and lncRNA functional similarity scores, and the prioritization scores of lncRNA-disease and miRNA-disease pairs. http://bio-annotation.cn:18080/DincRNAClient/. biofomeng@hotmail.com or qhjiang@hit.edu.cn. Supplementary data are available at Bioinformatics online.

Pairwise additivity of energy components in protein-ligand binding: The HIV II protease-Indinavir case

NASA Astrophysics Data System (ADS)

Ucisik, Melek N.; Dashti, Danial S.; Faver, John C.; Merz, Kenneth M.

2011-08-01

An energy expansion (binding energy decomposition into n-body interaction terms for n ≥ 2) to express the receptor-ligand binding energy for the fragmented HIV II protease-Indinavir system is described to address the role of cooperativity in ligand binding. The outcome of this energy expansion is compared to the total receptor-ligand binding energy at the Hartree-Fock, density functional theory, and semiempirical levels of theory. We find that the sum of the pairwise interaction energies approximates the total binding energy to ˜82% for HF and to >95% for both the M06-L density functional and PM6-DH2 semiempirical method. The contribution of the three-body interactions amounts to 18.7%, 3.8%, and 1.4% for HF, M06-L, and PM6-DH2, respectively. We find that the expansion can be safely truncated after n = 3. That is, the contribution of the interactions involving more than three parties to the total binding energy of Indinavir to the HIV II protease receptor is negligible. Overall, we find that the two-body terms represent a good approximation to the total binding energy of the system, which points to pairwise additivity in the present case. This basic principle of pairwise additivity is utilized in fragment-based drug design approaches and our results support its continued use. The present results can also aid in the validation of non-bonded terms contained within common force fields and in the correction of systematic errors in physics-based score functions.

Bioinformatic prediction and in vivo validation of residue-residue interactions in human proteins

NASA Astrophysics Data System (ADS)

Jordan, Daniel; Davis, Erica; Katsanis, Nicholas; Sunyaev, Shamil

2014-03-01

Identifying residue-residue interactions in protein molecules is important for understanding both protein structure and function in the context of evolutionary dynamics and medical genetics. Such interactions can be difficult to predict using existing empirical or physical potentials, especially when residues are far from each other in sequence space. Using a multiple sequence alignment of 46 diverse vertebrate species we explore the space of allowed sequences for orthologous protein families. Amino acid changes that are known to damage protein function allow us to identify specific changes that are likely to have interacting partners. We fit the parameters of the continuous-time Markov process used in the alignment to conclude that these interactions are primarily pairwise, rather than higher order. Candidates for sites under pairwise epistasis are predicted, which can then be tested by experiment. We report the results of an initial round of in vivo experiments in a zebrafish model that verify the presence of multiple pairwise interactions predicted by our model. These experimentally validated interactions are novel, distant in sequence, and are not readily explained by known biochemical or biophysical features.

related: an R package for analysing pairwise relatedness from codominant molecular markers.

PubMed

Pew, Jack; Muir, Paul H; Wang, Jinliang; Frasier, Timothy R

2015-05-01

Analyses of pairwise relatedness represent a key component to addressing many topics in biology. However, such analyses have been limited because most available programs provide a means to estimate relatedness based on only a single estimator, making comparison across estimators difficult. Second, all programs to date have been platform specific, working only on a specific operating system. This has the undesirable outcome of making choice of relatedness estimator limited by operating system preference, rather than being based on scientific rationale. Here, we present a new R package, called related, that can calculate relatedness based on seven estimators, can account for genotyping errors, missing data and inbreeding, and can estimate 95% confidence intervals. Moreover, simulation functions are provided that allow for easy comparison of the performance of different estimators and for analyses of how much resolution to expect from a given data set. Because this package works in R, it is platform independent. Combined, this functionality should allow for more appropriate analyses and interpretation of pairwise relatedness and will also allow for the integration of relatedness data into larger R workflows. © 2014 John Wiley & Sons Ltd.

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm.

PubMed

Hoffmann, Thomas J; Zhan, Yiping; Kvale, Mark N; Hesselson, Stephanie E; Gollub, Jeremy; Iribarren, Carlos; Lu, Yontao; Mei, Gangwu; Purdy, Matthew M; Quesenberry, Charles; Rowell, Sarah; Shapero, Michael H; Smethurst, David; Somkin, Carol P; Van den Eeden, Stephen K; Walter, Larry; Webster, Teresa; Whitmer, Rachel A; Finn, Andrea; Schaefer, Catherine; Kwok, Pui-Yan; Risch, Neil

2011-12-01

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies. Copyright © 2011 Elsevier Inc. All rights reserved.

Weighted projected networks: mapping hypergraphs to networks.

PubMed

López, Eduardo

2013-05-01

Many natural, technological, and social systems incorporate multiway interactions, yet are characterized and measured on the basis of weighted pairwise interactions. In this article, I propose a family of models in which pairwise interactions originate from multiway interactions, by starting from ensembles of hypergraphs and applying projections that generate ensembles of weighted projected networks. I calculate analytically the statistical properties of weighted projected networks, and suggest ways these could be used beyond theoretical studies. Weighted projected networks typically exhibit weight disorder along links even for very simple generating hypergraph ensembles. Also, as the size of a hypergraph changes, a signature of multiway interaction emerges on the link weights of weighted projected networks that distinguishes them from fundamentally weighted pairwise networks. This signature could be used to search for hidden multiway interactions in weighted network data. I find the percolation threshold and size of the largest component for hypergraphs of arbitrary uniform rank, translate the results into projected networks, and show that the transition is second order. This general approach to network formation has the potential to shed new light on our understanding of weighted networks.

The intrinsic dependence structure of peak, volume, duration, and average intensity of hyetographs and hydrographs

NASA Astrophysics Data System (ADS)

Serinaldi, Francesco; Kilsby, Chris G.

2013-06-01

The information contained in hyetographs and hydrographs is often synthesized by using key properties such as the peak or maximum value Xp, volume V, duration D, and average intensity I. These variables play a fundamental role in hydrologic engineering as they are used, for instance, to define design hyetographs and hydrographs as well as to model and simulate the rainfall and streamflow processes. Given their inherent variability and the empirical evidence of the presence of a significant degree of association, such quantities have been studied as correlated random variables suitable to be modeled by multivariate joint distribution functions. The advent of copulas in geosciences simplified the inference procedures allowing for splitting the analysis of the marginal distributions and the study of the so-called dependence structure or copula. However, the attention paid to the modeling task has overlooked a more thorough study of the true nature and origin of the relationships that link Xp,V,D, and I. In this study, we apply a set of ad hoc bootstrap algorithms to investigate these aspects by analyzing the hyetographs and hydrographs extracted from 282 daily rainfall series from central eastern Europe, three 5 min rainfall series from central Italy, 80 daily streamflow series from the continental United States, and two sets of 200 simulated universal multifractal time series. Our results show that all the pairwise dependence structures between Xp,V,D, and I exhibit some key properties that can be reproduced by simple bootstrap algorithms that rely on a standard univariate resampling without resort to multivariate techniques. Therefore, the strong similarities between the observed dependence structures and the agreement between the observed and bootstrap samples suggest the existence of a numerical generating mechanism based on the superposition of the effects of sampling data at finite time steps and the process of summing realizations of independent random variables over random durations. We also show that the pairwise dependence structures are weakly dependent on the internal patterns of the hyetographs and hydrographs, meaning that the temporal evolution of the rainfall and runoff events marginally influences the mutual relationships of Xp,V,D, and I. Finally, our findings point out that subtle and often overlooked deterministic relationships between the properties of the event hyetographs and hydrographs exist. Confusing these relationships with genuine stochastic relationships can lead to an incorrect application of multivariate distributions and copulas and to misleading results.

Punishment and reputation in spatial public goods games.

PubMed

Brandt, Hannelore; Hauert, Christoph; Sigmund, Karl

2003-05-22

The puzzle of the emergence of cooperation between unrelated individuals is shared across diverse fields of behavioural sciences and economics. In this article we combine the public goods game originating in economics with evolutionary approaches traditionally used in biology. Instead of pairwise encounters, we consider the more complex case of groups of three interacting individuals. We show that territoriality is capable of promoting cooperative behaviour, as in the case of the Prisoner's Dilemma. Moreover, by adding punishment opportunities, the readiness to cooperate is greatly enhanced and asocial strategies can be largely suppressed. Finally, as soon as players carry a reputation for being willing or unwilling to punish, highly cooperative and fair outcomes are achieved. This group-beneficial result is obtained, intriguingly, by making individuals more likely to exploit their co-players if they can get away with it. Thus, less-cooperative individuals make more-cooperative societies.

Modified screening interaction potential on dust lattice waves in dusty plasma ring

NASA Astrophysics Data System (ADS)

He, Kerong; Chen, Hui; Liu, Sanqiu

2017-05-01

In the present paper, the modified screening interaction potential was adopted to investigate the dust lattice waves in dusty ring. Firstly, the influence of parameter ε on the modified screening interaction potential was analyzed; and it was found that the parameter ε has a long-range effect on the pairwise interaction between the particles. Secondly, the dispersion relations of longitudinal and transverse waves are obtained, and the effect of long-range action parameter ε, dimensionless lattice parameter α and dimensionless shielding parameter \\tilde{κ } on the dust lattice waves propagation in dusty ring are studied. Some interesting phenomena, such as the coupling of longitudinal and transverse waves, and instabilities of transverse waves are found, which are in good agreement with some previous works. Finally, the transverse wave instabilities and the relevant critical lattice parameter αc are presented and discussed.

Evaluation of the Three Gorges Dam project using multi-criteria analysis (MCA) based on a sustainable perspective

NASA Astrophysics Data System (ADS)

Han, Yue; Zheng, Wei; Guo, Junshan; Ma, Yihe; Ding, Junqi; Zhu, Lingkai; Che, Yongqiang; Zhang, Yanpeng

2018-02-01

Abstract . The Three Gorges dam of China is one of the largest and expensive hydropower projects of the world. The four main purposes of the project are flood control,energy production, improved navigation and fresh water supply. The dam project has been completed and running successfully with the potential benefits. However, this project is still a controversial issue among many environmentalists and socialists due to various impacts. This study focuses on the benefit and the impacts of the project, and also evaluates the performance of the project using multi-criteria analysis (MCA) approach from a sustainable perspective. Different sustainability criteria related with the dam project have been identified and used for the ranking and rating process. The final result of MCA comes with this scoring process and pairwise comparison, which evaluates the performance of the project considering different positive and negative aspects.

An integrative multi-criteria decision making techniques for supplier evaluation problem with its application

NASA Astrophysics Data System (ADS)

Fatrias, D.; Kamil, I.; Meilani, D.

2018-03-01

Coordinating business operation with suppliers becomes increasingly important to survive and prosper under the dynamic business environment. A good partnership with suppliers not only increase efficiency, but also strengthen corporate competitiveness. Associated with such concern, this study aims to develop a practical approach of multi-criteria supplier evaluation using combined methods of Taguchi loss function (TLF), best-worst method (BWM) and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR). A new framework of integrative approach adopting these methods is our main contribution for supplier evaluation in literature. In this integrated approach, a compromised supplier ranking list based on the loss score of suppliers is obtained using efficient steps of a pairwise comparison based decision making process. Implemetation to the case problem with real data from crumb rubber industry shows the usefulness of the proposed approach. Finally, a suitable managerial implication is presented.

Feeling small: exploring the tactile perception limits.

PubMed

Skedung, Lisa; Arvidsson, Martin; Chung, Jun Young; Stafford, Christopher M; Berglund, Birgitta; Rutland, Mark W

2013-01-01

The human finger is exquisitely sensitive in perceiving different materials, but the question remains as to what length scales are capable of being distinguished in active touch. We combine material science with psychophysics to manufacture and haptically explore a series of topographically patterned surfaces of controlled wavelength, but identical chemistry. Strain-induced surface wrinkling and subsequent templating produced 16 surfaces with wrinkle wavelengths ranging from 300 nm to 90 μm and amplitudes between 7 nm and 4.5 μm. Perceived similarities of these surfaces (and two blanks) were pairwise scaled by participants, and interdistances among all stimuli were determined by individual differences scaling (INDSCAL). The tactile space thus generated and its two perceptual dimensions were directly linked to surface physical properties - the finger friction coefficient and the wrinkle wavelength. Finally, the lowest amplitude of the wrinkles so distinguished was approximately 10 nm, demonstrating that human tactile discrimination extends to the nanoscale.

Solvent Effects on Protein Folding/Unfolding

NASA Astrophysics Data System (ADS)

García, A. E.; Hillson, N.; Onuchic, J. N.

Pressure effects on the hydrophobic potential of mean force led Hummer et al. to postulate a model for pressure denaturation of proteins in which denaturation occurs by means of water penetration into the protein interior, rather than by exposing the protein hydrophobic core to the solvent --- commonly used to describe temperature denaturation. We study the effects of pressure in protein folding/unfolding kinetics in an off-lattice minimalist model of a protein in which pressure effects have been incorporated by means of the pair-wise potential of mean force of hydrophobic groups in water. We show that pressure slows down the kinetics of folding by decreasing the reconfigurational diffusion coefficient and moves the location of the folding transition state.

Rotation invariant deep binary hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Dai, Lai; Liu, Jianming; Jiang, Aiwen

2017-07-01

In this paper, we study how to compactly represent image's characteristics for fast image retrieval. We propose supervised rotation invariant compact discriminative binary descriptors through combining convolutional neural network with hashing. In the proposed network, binary codes are learned by employing a hidden layer for representing latent concepts that dominate on class labels. A loss function is proposed to minimize the difference between binary descriptors that describe reference image and the rotated one. Compared with some other supervised methods, the proposed network doesn't have to require pair-wised inputs for binary code learning. Experimental results show that our method is effective and achieves state-of-the-art results on the CIFAR-10 and MNIST datasets.

Hierarchical structure of biological systems

PubMed Central

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

Hierarchical structure of biological systems: a bioengineering approach.

PubMed

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems.

Referring to the social performance promotes cooperation in spatial prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Shigaki, Keizo; Tanimoto, Jun; Wang, Zhen; Kokubo, Satoshi; Hagishima, Aya; Ikegaya, Naoki

2012-09-01

We propose a new pairwise Fermi updating rule by considering a social average payoff when an agent copies a neighbor's strategy. In the update rule, a focal agent compares her payoff with the social average payoff of the same strategy that her pairwise opponent has. This concept might be justified by the fact that people reference global and, somehow, statistical information, not local information when imitating social behaviors. We presume several possible ways for the social average. Simulation results prove that the social average of some limited agents realizes more significant cooperation than that of the entire population.

Stability and minimum size of colloidal clusters on a liquid-air interface.

PubMed

Pergamenshchik, V M

2012-02-01

A vertical force applied to each of two colloids, trapped at a liquid-air interface, induces their logarithmic pairwise attraction. I recently showed [Phys. Rev. E 79, 011407 (2009)] that in clusters of size R much larger than the capillary length λ, the attraction changes to that of a power law and is much stronger due to a many-body effect, and I derived two equations that describe the equilibrium coarse-grained meniscus profile and colloid density in such clusters. In this paper, this theory is shown also to describe small clusters with R≪ λ provided the number N of colloids therein is sufficiently large. An analytical solution for a small circular cluster with an arbitrary short-range power-law pairwise repulsion is found. The energy of a cluster is obtained as a function of its radius R and colloid number N. As in large clusters, the attraction force and energy universally scale with the distance L between colloids as L(-3) and L(-2), respectively, for any repulsion forces. The states of an equilibrium cluster, predicted by the theory, are shown to be stable with respect to small perturbations of the meniscus profile and colloid density. The minimum number of colloids in a circular cluster, which sustains the thermal motion, is estimated. For standard parameters, it can be very modest, e.g., in the range 20-200, which is in line with experimental findings on reversible clusterization on a liquid-air interface. © 2012 American Physical Society

The use of many-body expansions and geometry optimizations in fragment-based methods.

PubMed

Fedorov, Dmitri G; Asada, Naoya; Nakanishi, Isao; Kitaura, Kazuo

2014-09-16

Conspectus Chemists routinely work with complex molecular systems: solutions, biochemical molecules, and amorphous and composite materials provide some typical examples. The questions one often asks are what are the driving forces for a chemical phenomenon? How reasonable are our views of chemical systems in terms of subunits, such as functional groups and individual molecules? How can one quantify the difference in physicochemical properties of functional units found in a different chemical environment? Are various effects on functional units in molecular systems additive? Can they be represented by pairwise potentials? Are there effects that cannot be represented in a simple picture of pairwise interactions? How can we obtain quantitative values for these effects? Many of these questions can be formulated in the language of many-body effects. They quantify the properties of subunits (fragments), referred to as one-body properties, pairwise interactions (two-body properties), couplings of two-body interactions described by three-body properties, and so on. By introducing the notion of fragments in the framework of quantum chemistry, one obtains two immense benefits: (a) chemists can finally relate to quantum chemistry, which now speaks their language, by discussing chemically interesting subunits and their interactions and (b) calculations become much faster due to a reduced computational scaling. For instance, the somewhat academic sounding question of the importance of three-body effects in water clusters is actually another way of asking how two hydrogen bonds affect each other, when they involve three water molecules. One aspect of this is the many-body charge transfer (CT), because the charge transfers in the two hydrogen bonds are coupled to each other (not independent). In this work, we provide a generalized view on the use of many-body expansions in fragment-based methods, focusing on the general aspects of the property expansion and a contraction of a many-body expansion in a formally two-body series, as exemplified in the development of the fragment molecular orbital (FMO) method. Fragment-based methods have been very successful in delivering the properties of fragments, as well as the fragment interactions, providing insights into complex chemical processes in large molecular systems. We briefly review geometry optimizations performed with fragment-based methods and present an efficient geometry optimization method based on the combination of FMO with molecular mechanics (MM), applied to the complex of a subunit of protein kinase 2 (CK2) with a ligand. FMO results are discussed in comparison with experimental and MM-optimized structures.

Are Health State Valuations from the General Public Biased? A Test of Health State Reference Dependency Using Self-assessed Health and an Efficient Discrete Choice Experiment.

PubMed

Jonker, Marcel F; Attema, Arthur E; Donkers, Bas; Stolk, Elly A; Versteegh, Matthijs M

2017-12-01

Health state valuations of patients and non-patients are not the same, whereas health state values obtained from general population samples are a weighted average of both. The latter constitutes an often-overlooked source of bias. This study investigates the resulting bias and tests for the impact of reference dependency on health state valuations using an efficient discrete choice experiment administered to a Dutch nationally representative sample of 788 respondents. A Bayesian discrete choice experiment design consisting of eight sets of 24 (matched pairwise) choice tasks was developed, with each set providing full identification of the included parameters. Mixed logit models were used to estimate health state preferences with respondents' own health included as an additional predictor. Our results indicate that respondents with impaired health worse than or equal to the health state levels under evaluation have approximately 30% smaller health state decrements. This confirms that reference dependency can be observed in general population samples and affirms the relevance of prospect theory in health state valuations. At the same time, the limited number of respondents with severe health impairments does not appear to bias social tariffs as obtained from general population samples. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models

PubMed Central

Grün, Sonja; Helias, Moritz

2017-01-01

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition. PMID:28968396

Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals

NASA Astrophysics Data System (ADS)

Chella, Federico; Pizzella, Vittorio; Zappasodi, Filippo; Nolte, Guido; Marzetti, Laura

2016-05-01

Brain cognitive functions arise through the coordinated activity of several brain regions, which actually form complex dynamical systems operating at multiple frequencies. These systems often consist of interacting subsystems, whose characterization is of importance for a complete understanding of the brain interaction processes. To address this issue, we present a technique, namely the bispectral pairwise interacting source analysis (biPISA), for analyzing systems of cross-frequency interacting brain sources when multichannel electroencephalographic (EEG) or magnetoencephalographic (MEG) data are available. Specifically, the biPISA makes it possible to identify one or many subsystems of cross-frequency interacting sources by decomposing the antisymmetric components of the cross-bispectra between EEG or MEG signals, based on the assumption that interactions are pairwise. Thanks to the properties of the antisymmetric components of the cross-bispectra, biPISA is also robust to spurious interactions arising from mixing artifacts, i.e., volume conduction or field spread, which always affect EEG or MEG functional connectivity estimates. This method is an extension of the pairwise interacting source analysis (PISA), which was originally introduced for investigating interactions at the same frequency, to the study of cross-frequency interactions. The effectiveness of this approach is demonstrated in simulations for up to three interacting source pairs and for real MEG recordings of spontaneous brain activity. Simulations show that the performances of biPISA in estimating the phase difference between the interacting sources are affected by the increasing level of noise rather than by the number of the interacting subsystems. The analysis of real MEG data reveals an interaction between two pairs of sources of central mu and beta rhythms, localizing in the proximity of the left and right central sulci.

Inverse MDS: Inferring Dissimilarity Structure from Multiple Item Arrangements

PubMed Central

Kriegeskorte, Nikolaus; Mur, Marieke

2012-01-01

The pairwise dissimilarities of a set of items can be intuitively visualized by a 2D arrangement of the items, in which the distances reflect the dissimilarities. Such an arrangement can be obtained by multidimensional scaling (MDS). We propose a method for the inverse process: inferring the pairwise dissimilarities from multiple 2D arrangements of items. Perceptual dissimilarities are classically measured using pairwise dissimilarity judgments. However, alternative methods including free sorting and 2D arrangements have previously been proposed. The present proposal is novel (a) in that the dissimilarity matrix is estimated by “inverse MDS” based on multiple arrangements of item subsets, and (b) in that the subsets are designed by an adaptive algorithm that aims to provide optimal evidence for the dissimilarity estimates. The subject arranges the items (represented as icons on a computer screen) by means of mouse drag-and-drop operations. The multi-arrangement method can be construed as a generalization of simpler methods: It reduces to pairwise dissimilarity judgments if each arrangement contains only two items, and to free sorting if the items are categorically arranged into discrete piles. Multi-arrangement combines the advantages of these methods. It is efficient (because the subject communicates many dissimilarity judgments with each mouse drag), psychologically attractive (because dissimilarities are judged in context), and can characterize continuous high-dimensional dissimilarity structures. We present two procedures for estimating the dissimilarity matrix: a simple weighted-aligned-average of the partial dissimilarity matrices and a computationally intensive algorithm, which estimates the dissimilarity matrix by iteratively minimizing the error of MDS-predictions of the subject’s arrangements. The Matlab code for interactive arrangement and dissimilarity estimation is available from the authors upon request. PMID:22848204

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models.

PubMed

Rostami, Vahid; Porta Mana, PierGianLuca; Grün, Sonja; Helias, Moritz

2017-10-01

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition.

Population Expansion and Genetic Structure in Carcharhinus brevipinna in the Southern Indo-Pacific

PubMed Central

Geraghty, Pascal T.; Williamson, Jane E.; Macbeth, William G.; Wintner, Sabine P.; Harry, Alastair V.; Ovenden, Jennifer R.; Gillings, Michael R.

2013-01-01

Background Quantifying genetic diversity and metapopulation structure provides insights into the evolutionary history of a species and helps develop appropriate management strategies. We provide the first assessment of genetic structure in spinner sharks (Carcharhinus brevipinna), a large cosmopolitan carcharhinid, sampled from eastern and northern Australia and South Africa. Methods and Findings Sequencing of the mitochondrial DNA NADH dehydrogenase subunit 4 gene for 430 individuals revealed 37 haplotypes and moderately high haplotype diversity (h = 0.6770 ±0.025). While two metrics of genetic divergence (ΦST and F ST) revealed somewhat different results, subdivision was detected between South Africa and all Australian locations (pairwise ΦST, range 0.02717–0.03508, p values ≤ 0.0013; pairwise F ST South Africa vs New South Wales = 0.04056, p = 0.0008). Evidence for fine-scale genetic structuring was also detected along Australia’s east coast (pairwise ΦST = 0.01328, p < 0.015), and between south-eastern and northern locations (pairwise ΦST = 0.00669, p < 0.04). Conclusions The Indian Ocean represents a robust barrier to contemporary gene flow in C. brevipinna between Australia and South Africa. Gene flow also appears restricted along a continuous continental margin in this species, with data tentatively suggesting the delineation of two management units within Australian waters. Further sampling, however, is required for a more robust evaluation of the latter finding. Evidence indicates that all sampled populations were shaped by a substantial demographic expansion event, with the resultant high genetic diversity being cause for optimism when considering conservation of this commercially-targeted species in the southern Indo-Pacific. PMID:24086462

Pairwise contact energy statistical potentials can help to find probability of point mutations.

PubMed

Saravanan, K M; Suvaithenamudhan, S; Parthasarathy, S; Selvaraj, S

2017-01-01

To adopt a particular fold, a protein requires several interactions between its amino acid residues. The energetic contribution of these residue-residue interactions can be approximated by extracting statistical potentials from known high resolution structures. Several methods based on statistical potentials extracted from unrelated proteins are found to make a better prediction of probability of point mutations. We postulate that the statistical potentials extracted from known structures of similar folds with varying sequence identity can be a powerful tool to examine probability of point mutation. By keeping this in mind, we have derived pairwise residue and atomic contact energy potentials for the different functional families that adopt the (α/β) 8 TIM-Barrel fold. We carried out computational point mutations at various conserved residue positions in yeast Triose phosphate isomerase enzyme for which experimental results are already reported. We have also performed molecular dynamics simulations on a subset of point mutants to make a comparative study. The difference in pairwise residue and atomic contact energy of wildtype and various point mutations reveals probability of mutations at a particular position. Interestingly, we found that our computational prediction agrees with the experimental studies of Silverman et al. (Proc Natl Acad Sci 2001;98:3092-3097) and perform better prediction than i Mutant and Cologne University Protein Stability Analysis Tool. The present work thus suggests deriving pairwise contact energy potentials and molecular dynamics simulations of functionally important folds could help us to predict probability of point mutations which may ultimately reduce the time and cost of mutation experiments. Proteins 2016; 85:54-64. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment

PubMed Central

2014-01-01

Background Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. Results MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Conclusions Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy. PMID:24731387

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment.

PubMed

Cao, Renzhi; Wang, Zheng; Cheng, Jianlin

2014-04-15

Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy.

Reductions in Average Lengths of Stays for Surgical Procedures Between the 2008 and 2014 United States National Inpatient Samples Were Not Associated With Greater Incidences of Use of Postacute Care Facilities.

PubMed

Dexter, Franklin; Epstein, Richard H

2018-03-01

Diagnosis-related group (DRG) based reimbursement creates incentives for reduction in hospital length of stay (LOS). Such reductions might be accomplished by lesser incidences of discharges to home. However, we previously reported that, while controlling for DRG, each 1-day decrease in hospital median LOS was associated with lesser odds of transfer to a postacute care facility (P = .0008). The result, though, was limited to elective admissions, 15 common surgical DRGs, and the 2013 US National Readmission Database. We studied the same potential relationship between decreased LOS and postacute care using different methodology and over 2 different years. The observational study was performed using summary measures from the 2008 and 2014 US National Inpatient Sample, with 3 types of categories (strata): (1) Clinical Classifications Software's classes of procedures (CCS), (2) DRGs including a major operating room procedure during hospitalization, or (3) CCS limiting patients to those with US Medicare as the primary payer. Greater reductions in the mean LOS were associated with smaller percentages of patients with disposition to postacute care. Analyzed using 72 different CCSs, 174 DRGs, or 70 CCSs limited to Medicare patients, each pairwise reduction in the mean LOS by 1 day was associated with an estimated 2.6% ± 0.4%, 2.3% ± 0.3%, or 2.4% ± 0.3% (absolute) pairwise reduction in the mean incidence of use of postacute care, respectively. These 3 results obtained using bivariate weighted least squares linear regression were all P < .0001, as were the corresponding results obtained using unweighted linear regression or the Spearman rank correlation. In the United States, reductions in hospital LOS, averaged over many surgical procedures, are not accomplished through a greater incidence of use of postacute care.

Quantum state matching of qubits via measurement-induced nonlinear transformations

NASA Astrophysics Data System (ADS)

Kálmán, Orsolya; Kiss, Tamás

2018-03-01

We consider the task of deciding whether an unknown qubit state falls in a prescribed neighborhood of a reference state. We assume that several copies of the unknown state are given and apply a unitary operation pairwise on them combined with a postselection scheme conditioned on the measurement result obtained on one of the qubits of the pair. The resulting transformation is a deterministic, nonlinear, chaotic map in the Hilbert space. We derive a class of these transformations capable of orthogonalizing nonorthogonal qubit states after a few iterations. These nonlinear maps orthogonalize states which correspond to the two different convergence regions of the nonlinear map. Based on the analysis of the border (the so-called Julia set) between the two regions of convergence, we show that it is always possible to find a map capable of deciding whether an unknown state is within a neighborhood of fixed radius around a desired quantum state. We analyze which one- and two-qubit operations would physically realize the scheme. It is possible to find a single two-qubit unitary gate for each map or, alternatively, a universal special two-qubit gate together with single-qubit gates in order to carry out the task. We note that it is enough to have a single physical realization of the required gates due to the iterative nature of the scheme.

Accidental degeneracies in nonlinear quantum deformed systems

NASA Astrophysics Data System (ADS)

Aleixo, A. N. F.; Balantekin, A. B.

2011-09-01

We construct a multi-parameter nonlinear deformed algebra for quantum confined systems that includes many other deformed models as particular cases. We demonstrate that such systems exhibit the property of accidental pairwise energy level degeneracies. We also study, as a special case of our multi-parameter deformation formalism, the extension of the Tamm-Dancoff cutoff deformed oscillator and the occurrence of accidental pairwise degeneracy in the energy levels of the deformed system. As an application, we discuss the case of a trigonometric Rosen-Morse potential, which is successfully used in models for quantum confined systems, ranging from electrons in quantum dots to quarks in hadrons.

Benefits of Using Pairwise Trajectory Management in the Central East Pacific

NASA Technical Reports Server (NTRS)

Chartrand, Ryan; Ballard, Kathryn

2017-01-01

Pairwise Trajectory Management (PTM) is a concept that utilizes airborne and ground-based capabilities to enable airborne spacing operations in procedural airspace. This concept makes use of updated ground automation, Automatic Dependent Surveillance-Broadcast (ADS-B) and on board avionics generating real time guidance. An experiment was conducted to examine the potential benefits of implementing PTM in the Central East Pacific oceanic region. An explanation of the experiment and some of the results are included in this paper. The PTM concept allowed for an increase in the average time an aircraft is able to spend at its desired flight level and a reduction in fuel burn.

Thermal Entanglement Between Atoms in the Four-Cavity Linear Chain Coupled by Single-Mode Fibers

NASA Astrophysics Data System (ADS)

Wang, Jun-Biao; Zhang, Guo-Feng

2018-05-01

Natural thermal entanglement between atoms of a linear arranged four coupled cavities system is studied. The results show that there is no thermal pairwise entanglement between atoms if atom-field interaction strength f or fiber-cavity coupling constant J equals to zero, both f and J can induce thermal pairwise entanglement in a certain range. Numerical simulations show that the nearest neighbor concurrence C A B is always greater than alternate concurrence C A C in the same condition. In addition, the effect of temperature T on the entanglement of alternate qubits is much stronger than the nearest neighbor qubits.

N -term pairwise-correlation inequalities, steering, and joint measurability

NASA Astrophysics Data System (ADS)

Karthik, H. S.; Devi, A. R. Usha; Tej, J. Prabhu; Rajagopal, A. K.; Sudha, Narayanan, A.

2017-05-01

Chained inequalities involving pairwise correlations of qubit observables in the equatorial plane are constructed based on the positivity of a sequence of moment matrices. When a jointly measurable set of positive-operator-valued measures (POVMs) is employed in the first measurement of every pair of sequential measurements, the chained pairwise correlations do not violate the classical bound imposed by the moment matrix positivity. We find that incompatibility of the set of POVMs employed in first measurements is only necessary, but not sufficient, in general, for the violation of the inequality. On the other hand, there exists a one-to-one equivalence between the degree of incompatibility (which quantifies the joint measurability) of the equatorial qubit POVMs and the optimal violation of a nonlocal steering inequality, proposed by Jones and Wiseman [S. J. Jones and H. M. Wiseman, Phys. Rev. A 84, 012110 (2011), 10.1103/PhysRevA.84.012110]. To this end, we construct a local analog of this steering inequality in a single-qubit system and show that its violation is a mere reflection of measurement incompatibility of equatorial qubit POVMs, employed in first measurements in the sequential unsharp-sharp scheme.

Programmable Potentials: Approximate N-body potentials from coarse-level logic.

PubMed

Thakur, Gunjan S; Mohr, Ryan; Mezić, Igor

2016-09-27

This paper gives a systematic method for constructing an N-body potential, approximating the true potential, that accurately captures meso-scale behavior of the chemical or biological system using pairwise potentials coming from experimental data or ab initio methods. The meso-scale behavior is translated into logic rules for the dynamics. Each pairwise potential has an associated logic function that is constructed using the logic rules, a class of elementary logic functions, and AND, OR, and NOT gates. The effect of each logic function is to turn its associated potential on and off. The N-body potential is constructed as linear combination of the pairwise potentials, where the "coefficients" of the potentials are smoothed versions of the associated logic functions. These potentials allow a potentially low-dimensional description of complex processes while still accurately capturing the relevant physics at the meso-scale. We present the proposed formalism to construct coarse-grained potential models for three examples: an inhibitor molecular system, bond breaking in chemical reactions, and DNA transcription from biology. The method can potentially be used in reverse for design of molecular processes by specifying properties of molecules that can carry them out.

Tools for Protecting the Privacy of Specific Individuals in Video

NASA Astrophysics Data System (ADS)

Chen, Datong; Chang, Yi; Yan, Rong; Yang, Jie

2007-12-01

This paper presents a system for protecting the privacy of specific individuals in video recordings. We address the following two problems: automatic people identification with limited labeled data, and human body obscuring with preserved structure and motion information. In order to address the first problem, we propose a new discriminative learning algorithm to improve people identification accuracy using limited training data labeled from the original video and imperfect pairwise constraints labeled from face obscured video data. We employ a robust face detection and tracking algorithm to obscure human faces in the video. Our experiments in a nursing home environment show that the system can obtain a high accuracy of people identification using limited labeled data and noisy pairwise constraints. The study result indicates that human subjects can perform reasonably well in labeling pairwise constraints with the face masked data. For the second problem, we propose a novel method of body obscuring, which removes the appearance information of the people while preserving rich structure and motion information. The proposed approach provides a way to minimize the risk of exposing the identities of the protected people while maximizing the use of the captured data for activity/behavior analysis.

Measuring pair-wise molecular interactions in a complex mixture

NASA Astrophysics Data System (ADS)

Chakraborty, Krishnendu; Varma, Manoj M.; Venkatapathi, Murugesan

2016-03-01

Complex biological samples such as serum contain thousands of proteins and other molecules spanning up to 13 orders of magnitude in concentration. Present measurement techniques do not permit the analysis of all pair-wise interactions between the components of such a complex mixture to a given target molecule. In this work we explore the use of nanoparticle tags which encode the identity of the molecule to obtain the statistical distribution of pair-wise interactions using their Localized Surface Plasmon Resonance (LSPR) signals. The nanoparticle tags are chosen such that the binding between two molecules conjugated to the respective nanoparticle tags can be recognized by the coupling of their LSPR signals. This numerical simulation is done by DDA to investigate this approach using a reduced system consisting of three nanoparticles (a gold ellipsoid with aspect ratio 2.5 and short axis 16 nm, and two silver ellipsoids with aspect ratios 3 and 2 and short axes 8 nm and 10 nm respectively) and the set of all possible dimers formed between them. Incident light was circularly polarized and all possible particle and dimer orientations were considered. We observed that minimum peak separation between two spectra is 5 nm while maximum is 184nm.

Random Partition Distribution Indexed by Pairwise Information

PubMed Central

Dahl, David B.; Day, Ryan; Tsai, Jerry W.

2017-01-01

We propose a random partition distribution indexed by pairwise similarity information such that partitions compatible with the similarities are given more probability. The use of pairwise similarities, in the form of distances, is common in some clustering algorithms (e.g., hierarchical clustering), but we show how to use this type of information to define a prior partition distribution for flexible Bayesian modeling. A defining feature of the distribution is that it allocates probability among partitions within a given number of subsets, but it does not shift probability among sets of partitions with different numbers of subsets. Our distribution places more probability on partitions that group similar items yet keeps the total probability of partitions with a given number of subsets constant. The distribution of the number of subsets (and its moments) is available in closed-form and is not a function of the similarities. Our formulation has an explicit probability mass function (with a tractable normalizing constant) so the full suite of MCMC methods may be used for posterior inference. We compare our distribution with several existing partition distributions, showing that our formulation has attractive properties. We provide three demonstrations to highlight the features and relative performance of our distribution. PMID:29276318

[Analysis of variance of repeated data measured by water maze with SPSS].

PubMed

Qiu, Hong; Jin, Guo-qin; Jin, Ru-feng; Zhao, Wei-kang

2007-01-01

To introduce the method of analyzing repeated data measured by water maze with SPSS 11.0, and offer a reference statistical method to clinical and basic medicine researchers who take the design of repeated measures. Using repeated measures and multivariate analysis of variance (ANOVA) process of the general linear model in SPSS and giving comparison among different groups and different measure time pairwise. Firstly, Mauchly's test of sphericity should be used to judge whether there were relations among the repeatedly measured data. If any (P

Programmable Potentials: Approximate N-body potentials from coarse-level logic

NASA Astrophysics Data System (ADS)

Thakur, Gunjan S.; Mohr, Ryan; Mezić, Igor

2016-09-01

This paper gives a systematic method for constructing an N-body potential, approximating the true potential, that accurately captures meso-scale behavior of the chemical or biological system using pairwise potentials coming from experimental data or ab initio methods. The meso-scale behavior is translated into logic rules for the dynamics. Each pairwise potential has an associated logic function that is constructed using the logic rules, a class of elementary logic functions, and AND, OR, and NOT gates. The effect of each logic function is to turn its associated potential on and off. The N-body potential is constructed as linear combination of the pairwise potentials, where the “coefficients” of the potentials are smoothed versions of the associated logic functions. These potentials allow a potentially low-dimensional description of complex processes while still accurately capturing the relevant physics at the meso-scale. We present the proposed formalism to construct coarse-grained potential models for three examples: an inhibitor molecular system, bond breaking in chemical reactions, and DNA transcription from biology. The method can potentially be used in reverse for design of molecular processes by specifying properties of molecules that can carry them out.

Diversity Increases Indirect Interactions, Attenuates the Intensity of Competition, and Promotes Coexistence.

PubMed

Aschehoug, Erik T; Callaway, Ragan M

2015-10-01

A fundamental assumption of coexistence theory is that competition inevitably decreases species diversity. Consequently, in the quest to understand the ecological regulators of diversity, there has been a great deal of focus on processes with the potential to reduce competitive exclusion. However, the notion that competition must decrease diversity is largely based on the outcome of two-species interaction experiments and models, despite the fact that species rarely interact only in pairs in natural systems. In a field experiment, we found that competition among native perennial plants in multispecies assemblages was far weaker than competition between those same species in pairwise arrangements and that indirect interactions appeared to weaken direct competitive effects. These results suggest that community assembly theory based on pairwise approaches may overestimate the strength of competition and likelihood of competitive exclusion in species-rich communities. We also found that Centaurea stoebe, a North American invader, retained strong competitive effects when competing against North American natives in both pairwise and multispecies assemblages. Our experimental results support an emerging body of theory suggesting that complex networks of competing species may generate strong indirect interactions that can maintain diversity and that ecological differentiation may not be necessary to attenuate competition.

Process perspective on image quality evaluation

NASA Astrophysics Data System (ADS)

Leisti, Tuomas; Halonen, Raisa; Kokkonen, Anna; Weckman, Hanna; Mettänen, Marja; Lensu, Lasse; Ritala, Risto; Oittinen, Pirkko; Nyman, Göte

2008-01-01

The psychological complexity of multivariate image quality evaluation makes it difficult to develop general image quality metrics. Quality evaluation includes several mental processes and ignoring these processes and the use of a few test images can lead to biased results. By using a qualitative/quantitative (Interpretation Based Quality, IBQ) methodology, we examined the process of pair-wise comparison in a setting, where the quality of the images printed by laser printer on different paper grades was evaluated. Test image consisted of a picture of a table covered with several objects. Three other images were also used, photographs of a woman, cityscape and countryside. In addition to the pair-wise comparisons, observers (N=10) were interviewed about the subjective quality attributes they used in making their quality decisions. An examination of the individual pair-wise comparisons revealed serious inconsistencies in observers' evaluations on the test image content, but not on other contexts. The qualitative analysis showed that this inconsistency was due to the observers' focus of attention. The lack of easily recognizable context in the test image may have contributed to this inconsistency. To obtain reliable knowledge of the effect of image context or attention on subjective image quality, a qualitative methodology is needed.

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

PubMed

Chang, Chin-Chun; Lin, Po-Yi

2015-03-01

The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Pairwise Trajectory Management (PTM): Concept Overview

NASA Technical Reports Server (NTRS)

Jones, Kenneth M.; Graff, Thomas J.; Chartrand, Ryan C.; Carreno, Victor; Kibler, Jennifer L.

2017-01-01

Pairwise Trajectory Management (PTM) is an Interval Management (IM) concept that utilizes airborne and ground-based capabilities to enable the implementation of airborne pairwise spacing capabilities in oceanic regions. The goal of PTM is to use airborne surveillance and tools to manage an "at or greater than" inter-aircraft spacing. Due to the precision of Automatic Dependent Surveillance-Broadcast (ADS-B) information and the use of airborne spacing guidance, the PTM minimum spacing distance will be less than distances a controller can support with current automation systems that support oceanic operations. Ground tools assist the controller in evaluating the traffic picture and determining appropriate PTM clearances to be issued. Avionics systems provide guidance information that allows the flight crew to conform to the PTM clearance issued by the controller. The combination of a reduced minimum distance and airborne spacing management will increase the capacity and efficiency of aircraft operations at a given altitude or volume of airspace. This paper provides an overview of the proposed application, description of a few key scenarios, high level discussion of expected air and ground equipment and procedure changes, overview of a potential flight crew human-machine interface that would support PTM operations and some initial PTM benefits results.

Programmable Potentials: Approximate N-body potentials from coarse-level logic

PubMed Central

Thakur, Gunjan S.; Mohr, Ryan; Mezić, Igor

2016-01-01

This paper gives a systematic method for constructing an N-body potential, approximating the true potential, that accurately captures meso-scale behavior of the chemical or biological system using pairwise potentials coming from experimental data or ab initio methods. The meso-scale behavior is translated into logic rules for the dynamics. Each pairwise potential has an associated logic function that is constructed using the logic rules, a class of elementary logic functions, and AND, OR, and NOT gates. The effect of each logic function is to turn its associated potential on and off. The N-body potential is constructed as linear combination of the pairwise potentials, where the “coefficients” of the potentials are smoothed versions of the associated logic functions. These potentials allow a potentially low-dimensional description of complex processes while still accurately capturing the relevant physics at the meso-scale. We present the proposed formalism to construct coarse-grained potential models for three examples: an inhibitor molecular system, bond breaking in chemical reactions, and DNA transcription from biology. The method can potentially be used in reverse for design of molecular processes by specifying properties of molecules that can carry them out. PMID:27671683

A Pairwise Naïve Bayes Approach to Bayesian Classification.

PubMed

Asafu-Adjei, Josephine K; Betensky, Rebecca A

2015-10-01

Despite the relatively high accuracy of the naïve Bayes (NB) classifier, there may be several instances where it is not optimal, i.e. does not have the same classification performance as the Bayes classifier utilizing the joint distribution of the examined attributes. However, the Bayes classifier can be computationally intractable due to its required knowledge of the joint distribution. Therefore, we introduce a "pairwise naïve" Bayes (PNB) classifier that incorporates all pairwise relationships among the examined attributes, but does not require specification of the joint distribution. In this paper, we first describe the necessary and sufficient conditions under which the PNB classifier is optimal. We then discuss sufficient conditions for which the PNB classifier, and not NB, is optimal for normal attributes. Through simulation and actual studies, we evaluate the performance of our proposed classifier relative to the Bayes and NB classifiers, along with the HNB, AODE, LBR and TAN classifiers, using normal density and empirical estimation methods. Our applications show that the PNB classifier using normal density estimation yields the highest accuracy for data sets containing continuous attributes. We conclude that it offers a useful compromise between the Bayes and NB classifiers.

Impaired inference in a case of developmental amnesia.

PubMed

D'Angelo, Maria C; Rosenbaum, R Shayna; Ryan, Jennifer D

2016-10-01

Amnesia is associated with impairments in relational memory, which is critically supported by the hippocampus. By adapting the transitivity paradigm, we previously showed that age-related impairments in inference were mitigated when judgments could be predicated on known pairwise relations, however, such advantages were not observed in the adult-onset amnesic case D.A. Here, we replicate and extend this finding in a developmental amnesic case (N.C.), who also shows impaired relational learning and transitive expression. Unlike D.A., N.C.'s damage affected the extended hippocampal system and diencephalic structures, and does not extend to neocortical areas that are affected in D.A. Critically, despite their differences in etiology and affected structures, N.C. and D.A. perform similarly on the task. N.C. showed intact pairwise knowledge, suggesting that he is able to use existing semantic information, but this semantic knowledge was insufficient to support transitive expression. The present results suggest a critical role for regions connected to the hippocampus and/or medial prefrontal cortex in inference beyond learning of pairwise relations. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. © 2016 The Authors. Wiley Periodicals, Inc.

Conservation laws, bilinear forms and solitons for a fifth-order nonlinear Schrödinger equation for the attosecond pulses in an optical fiber

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chai, Jun; Tian, Bo, E-mail: tian_bupt@163.com; Zhen, Hui-Ling

Under investigation in this paper is a fifth-order nonlinear Schrödinger equation, which describes the propagation of attosecond pulses in an optical fiber. Based on the Lax pair, infinitely-many conservation laws are derived. With the aid of auxiliary functions, bilinear forms, one-, two- and three-soliton solutions in analytic forms are generated via the Hirota method and symbolic computation. Soliton velocity varies linearly with the coefficients of the high-order terms. Head-on interaction between the bidirectional two solitons and overtaking interaction between the unidirectional two solitons as well as the bound state are depicted. For the interactions among the three solitons, two head-onmore » and one overtaking interactions, three overtaking interactions, an interaction between a bound state and a single soliton and the bound state are displayed. Graphical analysis shows that the interactions between the two solitons are elastic, and interactions among the three solitons are pairwise elastic. Stability analysis yields the modulation instability condition for the soliton solutions.« less

A Novel Ilarvirus Is Associated with Privet Necrotic Ringspot Disease in the Southern United States.

PubMed

Aboughanem-Sabanadzovic, Nina; Tzanetakis, Ioannis E; Lawrence, Amanda; Stephenson, Ronald C; Sabanadzovic, Sead

2016-01-01

Necrotic ringspot disease (NRSD) is a graft-transmissible disorder of privet (synonym ligustrum), originally reported from Florida and Louisiana more than 50 years ago. In this communication we report an isometric virus isolated from Japanese privet (Ligustrum japonicum) collected in the southern United States displaying symptoms resembling those of NRSD. In mechanical transmission tests, the virus induced systemic infections in several herbaceous hosts. Double-stranded RNA analysis showed a pattern resembling replicative forms of members of the family Bromoviridae. The genome organization along with phylogenetic analyses and serological tests revealed that the virus belongs to subgroup 1 of the genus Ilarvirus. Pairwise comparisons with recognized ilarviruses indicated that the virus is a distinct, and as yet, undescribed member in the taxon, for which we propose the name Privet ringspot virus (PrRSV). Furthermore, the near-perfect association of PrRSV infections with symptoms, and apparent absence of any other virus(es) in studied samples, strongly suggest an important role of this virus in the etiology of NRSD of privet in the southeastern United States.

Joint tumor segmentation and dense deformable registration of brain MR images.

PubMed

Parisot, Sarah; Duffau, Hugues; Chemouny, Stéphane; Paragios, Nikos

2012-01-01

In this paper we propose a novel graph-based concurrent registration and segmentation framework. Registration is modeled with a pairwise graphical model formulation that is modular with respect to the data and regularization term. Segmentation is addressed by adopting a similar graphical model, using image-based classification techniques while producing a smooth solution. The two problems are coupled via a relaxation of the registration criterion in the presence of tumors as well as a segmentation through a registration term aiming the separation between healthy and diseased tissues. Efficient linear programming is used to solve both problems simultaneously. State of the art results demonstrate the potential of our method on a large and challenging low-grade glioma data set.

Switching from usual brand cigarettes to a tobacco-heating cigarette or snus: Part 3. Biomarkers of biological effect

PubMed Central

Ogden, Michael W.; Marano, Kristin M.; Jones, Bobbette A.; Morgan, Walter T.; Stiles, Mitchell F.

2015-01-01

Abstract A randomized, multi-center study of adult cigarette smokers switched to tobacco-heating cigarettes, snus or ultra-low machine yield tobacco-burning cigarettes (50/group) for 24 weeks was conducted. Evaluation of biomarkers of biological effect (e.g. inflammation, lipids, hypercoaguable state) indicated that the majority of consistent and statistically significant improvements over time within each group were observed in markers of inflammation. Consistent and statistically significant differences in pairwise comparisons between product groups were not observed. These findings are relevant to the understanding of biomarkers of biological effect related to cigarette smoking as well as the risk continuum across various tobacco products (ClinicalTrials.gov Identifier: NCT02061917). PMID:26525962

Cover estimation and payload location using Markov random fields

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2014-02-01

Payload location is an approach to find the message bits hidden in steganographic images, but not necessarily their logical order. Its success relies primarily on the accuracy of the underlying cover estimators and can be improved if more estimators are used. This paper presents an approach based on Markov random field to estimate the cover image given a stego image. It uses pairwise constraints to capture the natural two-dimensional statistics of cover images and forms a basis for more sophisticated models. Experimental results show that it is competitive against current state-of-the-art estimators and can locate payload embedded by simple LSB steganography and group-parity steganography. Furthermore, when combined with existing estimators, payload location accuracy improves significantly.

17 Y-STR haplotype diversity in São Paulo state (southeast of Brazil).

PubMed

de Souza, Leandro Fonseca; da Motta, Carlos Henrique Ares Silveira; Moura-Neto, Rodrigo Soares

2018-03-12

A sample of 158 Brazilian males from São Paulo (SP), Brazilian southeast, was typed for 17 Y-STR loci (DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS437, DYS438, DYS439, DYS448, DYS456, DYS458, DYS635, YGATA_H4.1, and DYS385ab). A total of 158 haplotypes were identified, of which all were unique. The haplotype diversity and discrimination capacity were calculated in 1.0 and the genetic diversity was 67.4%. Pairwise haplotype distances showed that the São Paulo population is not significantly different from Rio de Janeiro and Portugal, but is different from African and Native American.

Self Consistent Bathymetric Mapping Using Sub-maps: Survey Results From the TAG Hydrothermal Structure

NASA Astrophysics Data System (ADS)

Roman, C. N.; Reves-Sohn, R.; Singh, H.; Humphris, S.

2005-12-01

The spatial resolution of microbathymetry maps created using robotic vehicles such as ROVs, AUVs and manned submersibles in the deep ocean is currently limited by the accuracy of the vehicle navigation data. Errors in the vehicle position estimate commonly exceed the ranging errors of the acoustic mapping sensor itself, which creates inconsistency in the map making process and produces artifacts that lower resolution and distort map integrity. We present a methodology for producing self-consistent maps and improving vehicle position estimation by exploiting accurate local navigation and utilizing terrain relative measurements. The complete map is broken down into individual "sub-maps'', which are generated using short term Doppler based navigation. The sub-maps are pairwise registered to constrain the vehicle position estimates by matching terrain that has been imaged multiple times. This procedure is implemented using a delayed state Kalman filter to incorporate the sub-map registrations as relative position measurements between previously visited vehicle locations. Archiving of previous positions in a filter state vector allows for continual adjustment of the sub-map locations. The terrain registration is accomplished using a two dimensional correlation and a six degree of freedom point cloud alignment method tailored to bathymetric data. This registration procedure is applicable to fully 3 dimensional complex underwater environments. The complete bathymetric map is then created from the union of all sub-maps that have been aligned in a consistent manner. The method is applied to an SM2000 multibeam survey of the TAG hydrothermal structure on the Mid-Atlantic Ridge at 26(°)N using the Jason II ROV. The survey included numerous crossing tracklines designed to test this algorithm, and the final gridded bathymetry data is sub-meter accurate. The high-resolution map has allowed for the identification of previously unrecognized fracture patterns associated with flow focusing at TAG, as well as imaging of fine-scale features such as individual sulfide talus blocks and ODP re-entry cones.

Single trial classification for the categories of perceived emotional facial expressions: an event-related fMRI study

NASA Astrophysics Data System (ADS)

Song, Sutao; Huang, Yuxia; Long, Zhiying; Zhang, Jiacai; Chen, Gongxiang; Wang, Shuqing

2016-03-01

Recently, several studies have successfully applied multivariate pattern analysis methods to predict the categories of emotions. These studies are mainly focused on self-experienced emotions, such as the emotional states elicited by music or movie. In fact, most of our social interactions involve perception of emotional information from the expressions of other people, and it is an important basic skill for humans to recognize the emotional facial expressions of other people in a short time. In this study, we aimed to determine the discriminability of perceived emotional facial expressions. In a rapid event-related fMRI design, subjects were instructed to classify four categories of facial expressions (happy, disgust, angry and neutral) by pressing different buttons, and each facial expression stimulus lasted for 2s. All participants performed 5 fMRI runs. One multivariate pattern analysis method, support vector machine was trained to predict the categories of facial expressions. For feature selection, ninety masks defined from anatomical automatic labeling (AAL) atlas were firstly generated and each were treated as the input of the classifier; then, the most stable AAL areas were selected according to prediction accuracies, and comprised the final feature sets. Results showed that: for the 6 pair-wise classification conditions, the accuracy, sensitivity and specificity were all above chance prediction, among which, happy vs. neutral , angry vs. disgust achieved the lowest results. These results suggested that specific neural signatures of perceived emotional facial expressions may exist, and happy vs. neutral, angry vs. disgust might be more similar in information representation in the brain.

An emergence of coordinated communication in populations of agents.

PubMed

Kvasnicka, V; Pospichal, J

1999-01-01

The purpose of this article is to demonstrate that coordinated communication spontaneously emerges in a population composed of agents that are capable of specific cognitive activities. Internal states of agents are characterized by meaning vectors. Simple neural networks composed of one layer of hidden neurons perform cognitive activities of agents. An elementary communication act consists of the following: (a) two agents are selected, where one of them is declared the speaker and the other the listener; (b) the speaker codes a selected meaning vector onto a sequence of symbols and sends it to the listener as a message; and finally, (c) the listener decodes this message into a meaning vector and adapts his or her neural network such that the differences between speaker and listener meaning vectors are decreased. A Darwinian evolution enlarged by ideas from the Baldwin effect and Dawkins' memes is simulated by a simple version of an evolutionary algorithm without crossover. The agent fitness is determined by success of the mutual pairwise communications. It is demonstrated that agents in the course of evolution gradually do a better job of decoding received messages (they are closer to meaning vectors of speakers) and all agents gradually start to use the same vocabulary for the common communication. Moreover, if agent meaning vectors contain regularities, then these regularities are manifested also in messages created by agent speakers, that is, similar parts of meaning vectors are coded by similar symbol substrings. This observation is considered a manifestation of the emergence of a grammar system in the common coordinated communication.

The importance of calorimetry for highly-boosted jet substructure

DOE PAGES

Coleman, Evan; Freytsis, Marat; Hinzmann, Andreas; ...

2018-01-09

Here, jet substructure techniques are playing an essential role in exploring the TeV scale at the Large Hadron Collider (LHC), since they facilitate the efficient reconstruction and identification of highly-boosted objects. Both for the LHC and for future colliders, there is a growing interest in using jet substructure methods based only on charged-particle information. The reason is that silicon-based tracking detectors offer excellent granularity and precise vertexing, which can improve the angular resolution on highly-collimated jets and mitigate the impact of pileup. In this paper, we assess how much jet substructure performance degrades by using track-only information, and we demonstratemore » physics contexts in which calorimetry is most beneficial. Specifically, we consider five different hadronic final states - W bosons, Z bosons, top quarks, light quarks, gluons - and test the pairwise discrimination power with a multi-variate combination of substructure observables. In the idealized case of perfect reconstruction, we quantify the loss in discrimination performance when using just charged particles compared to using all detected particles. We also consider the intermediate case of using charged particles plus photons, which provides valuable information about neutral pions. In the more realistic case of a segmented calorimeter, we assess the potential performance gains from improving calorimeter granularity and resolution, comparing a CMS-like detector to more ambitious future detector concepts. Broadly speaking, we find large performance gains from neutral-particle information and from improved calorimetry in cases where jet mass resolution drives the discrimination power, whereas the gains are more modest if an absolute mass scale calibration is not required.« less

The importance of calorimetry for highly-boosted jet substructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Evan; Freytsis, Marat; Hinzmann, Andreas

2017-09-25

Jet substructure techniques are playing an essential role in exploring the TeV scale at the Large Hadron Collider (LHC), since they facilitate the efficient reconstruction and identification of highly-boosted objects. Both for the LHC and for future colliders, there is a growing interest in using jet substructure methods based only on charged-particle information. The reason is that silicon-based tracking detectors offer excellent granularity and precise vertexing, which can improve the angular resolution on highly-collimated jets and mitigate the impact of pileup. In this paper, we assess how much jet substructure performance degrades by using track-only information, and we demonstrate physicsmore » contexts in which calorimetry is most beneficial. Specifically, we consider five different hadronic final states - W bosons, Z bosons, top quarks, light quarks, gluons - and test the pairwise discrimination power with a multi-variate combination of substructure observables. In the idealized case of perfect reconstruction, we quantify the loss in discrimination performance when using just charged particles compared to using all detected particles. We also consider the intermediate case of using charged particles plus photons, which provides valuable information about neutral pions. In the more realistic case of a segmented calorimeter, we assess the potential performance gains from improving calorimeter granularity and resolution, comparing a CMS-like detector to more ambitious future detector concepts. Broadly speaking, we find large performance gains from neutral-particle information and from improved calorimetry in cases where jet mass resolution drives the discrimination power, whereas the gains are more modest if an absolute mass scale calibration is not required.« less

Population-wide distributions of neural activity during perceptual decision-making

PubMed Central

Machens, Christian

2018-01-01

Cortical activity involves large populations of neurons, even when it is limited to functionally coherent areas. Electrophysiological recordings, on the other hand, involve comparatively small neural ensembles, even when modern-day techniques are used. Here we review results which have started to fill the gap between these two scales of inquiry, by shedding light on the statistical distributions of activity in large populations of cells. We put our main focus on data recorded in awake animals that perform simple decision-making tasks and consider statistical distributions of activity throughout cortex, across sensory, associative, and motor areas. We transversally review the complexity of these distributions, from distributions of firing rates and metrics of spike-train structure, through distributions of tuning to stimuli or actions and of choice signals, and finally the dynamical evolution of neural population activity and the distributions of (pairwise) neural interactions. This approach reveals shared patterns of statistical organization across cortex, including: (i) long-tailed distributions of activity, where quasi-silence seems to be the rule for a majority of neurons; that are barely distinguishable between spontaneous and active states; (ii) distributions of tuning parameters for sensory (and motor) variables, which show an extensive extrapolation and fragmentation of their representations in the periphery; and (iii) population-wide dynamics that reveal rotations of internal representations over time, whose traces can be found both in stimulus-driven and internally generated activity. We discuss how these insights are leading us away from the notion of discrete classes of cells, and are acting as powerful constraints on theories and models of cortical organization and population coding. PMID:23123501

The importance of calorimetry for highly-boosted jet substructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Evan; Freytsis, Marat; Hinzmann, Andreas

Here, jet substructure techniques are playing an essential role in exploring the TeV scale at the Large Hadron Collider (LHC), since they facilitate the efficient reconstruction and identification of highly-boosted objects. Both for the LHC and for future colliders, there is a growing interest in using jet substructure methods based only on charged-particle information. The reason is that silicon-based tracking detectors offer excellent granularity and precise vertexing, which can improve the angular resolution on highly-collimated jets and mitigate the impact of pileup. In this paper, we assess how much jet substructure performance degrades by using track-only information, and we demonstratemore » physics contexts in which calorimetry is most beneficial. Specifically, we consider five different hadronic final states - W bosons, Z bosons, top quarks, light quarks, gluons - and test the pairwise discrimination power with a multi-variate combination of substructure observables. In the idealized case of perfect reconstruction, we quantify the loss in discrimination performance when using just charged particles compared to using all detected particles. We also consider the intermediate case of using charged particles plus photons, which provides valuable information about neutral pions. In the more realistic case of a segmented calorimeter, we assess the potential performance gains from improving calorimeter granularity and resolution, comparing a CMS-like detector to more ambitious future detector concepts. Broadly speaking, we find large performance gains from neutral-particle information and from improved calorimetry in cases where jet mass resolution drives the discrimination power, whereas the gains are more modest if an absolute mass scale calibration is not required.« less

Phase Transition for the Maki-Thompson Rumour Model on a Small-World Network

NASA Astrophysics Data System (ADS)

Agliari, Elena; Pachon, Angelica; Rodriguez, Pablo M.; Tavani, Flavia

2017-11-01

We consider the Maki-Thompson model for the stochastic propagation of a rumour within a population. In this model the population is made up of "spreaders", "ignorants" and "stiflers"; any spreader attempts to pass the rumour to the other individuals via pair-wise interactions and in case the other individual is an ignorant, it becomes a spreader, while in the other two cases the initiating spreader turns into a stifler. In a finite population the process will eventually reach an equilibrium situation where individuals are either stiflers or ignorants. We extend the original hypothesis of homogenously mixed population by allowing for a small-world network embedding the model, in such a way that interactions occur only between nearest-neighbours. This structure is realized starting from a k-regular ring and by inserting, in the average, c additional links in such a way that k and c are tuneable parameters for the population architecture. We prove that this system exhibits a transition between regimes of localization (where the final number of stiflers is at most logarithmic in the population size) and propagation (where the final number of stiflers grows algebraically with the population size) at a finite value of the network parameter c. A quantitative estimate for the critical value of c is obtained via extensive numerical simulations.

Learning to rank atlases for multiple-atlas segmentation.

PubMed

Sanroma, Gerard; Wu, Guorong; Gao, Yaozong; Shen, Dinggang

2014-10-01

Recently, multiple-atlas segmentation (MAS) has achieved a great success in the medical imaging area. The key assumption is that multiple atlases have greater chances of correctly labeling a target image than a single atlas. However, the problem of atlas selection still remains unexplored. Traditionally, image similarity is used to select a set of atlases. Unfortunately, this heuristic criterion is not necessarily related to the final segmentation performance. To solve this seemingly simple but critical problem, we propose a learning-based atlas selection method to pick up the best atlases that would lead to a more accurate segmentation. Our main idea is to learn the relationship between the pairwise appearance of observed instances (i.e., a pair of atlas and target images) and their final labeling performance (e.g., using the Dice ratio). In this way, we select the best atlases based on their expected labeling accuracy. Our atlas selection method is general enough to be integrated with any existing MAS method. We show the advantages of our atlas selection method in an extensive experimental evaluation in the ADNI, SATA, IXI, and LONI LPBA40 datasets. As shown in the experiments, our method can boost the performance of three widely used MAS methods, outperforming other learning-based and image-similarity-based atlas selection methods.

Discrete-state representation of ion permeation coupled to fast gating in a model of ClC chloride channels: comparison to multi-ion continuous space Brownian dynamics simulations.

PubMed

Coalson, Rob D; Cheng, Mary Hongying

2010-01-28

A discrete-state model of chloride ion motion in a ClC chloride channel is constructed, following a previously developed multi-ion continuous space model of the same system (Cheng, M. H.; Mamonov, A. B.; Dukes, J. W.; Coalson, R. D. J. Phys. Chem. B 2007, 111, 5956) that included a simplistic representation of the fast gate in this channel. The reducibility of the many-body continuous space to the eight discrete-state model considered in the present work is examined in detail by performing three-dimensional Brownian dynamics simulations of each allowed state-to-state transition in order to extract the appropriate rate constant for this process, and then inserting the pairwise rate constants thereby obtained into an appropriate set of kinetic master equations. Experimental properties of interest, including the rate of Cl(-) ion permeation through the open channel and the average rate of closing of the fast gate as a function of bulk Cl(-) ion concentrations in the intracellular and extracellular electrolyte reservoirs are computed. Good agreement is found between the results obtained via the eight discrete-state model versus the multi-ion continuous space model, thereby encouraging continued development of the discrete-state model to include more complex behaviors observed experimentally in these channels.

Auditory Responses and Stimulus-Specific Adaptation in Rat Auditory Cortex are Preserved Across NREM and REM Sleep

PubMed Central

Nir, Yuval; Vyazovskiy, Vladyslav V.; Cirelli, Chiara; Banks, Matthew I.; Tononi, Giulio

2015-01-01

Sleep entails a disconnection from the external environment. By and large, sensory stimuli do not trigger behavioral responses and are not consciously perceived as they usually are in wakefulness. Traditionally, sleep disconnection was ascribed to a thalamic “gate,” which would prevent signal propagation along ascending sensory pathways to primary cortical areas. Here, we compared single-unit and LFP responses in core auditory cortex as freely moving rats spontaneously switched between wakefulness and sleep states. Despite robust differences in baseline neuronal activity, both the selectivity and the magnitude of auditory-evoked responses were comparable across wakefulness, Nonrapid eye movement (NREM) and rapid eye movement (REM) sleep (pairwise differences <8% between states). The processing of deviant tones was also compared in sleep and wakefulness using an oddball paradigm. Robust stimulus-specific adaptation (SSA) was observed following the onset of repetitive tones, and the strength of SSA effects (13–20%) was comparable across vigilance states. Thus, responses in core auditory cortex are preserved across sleep states, suggesting that evoked activity in primary sensory cortices is driven by external physical stimuli with little modulation by vigilance state. We suggest that sensory disconnection during sleep occurs at a stage later than primary sensory areas. PMID:24323498

Global-to-local incompatibility, monogamy of entanglement, and ground-state dimerization: Theory and observability of quantum frustration in systems with competing interactions

NASA Astrophysics Data System (ADS)

Giampaolo, S. M.; Hiesmayr, B. C.; Illuminati, F.

2015-10-01

Frustration in quantum many-body systems is quantified by the degree of incompatibility between the local and global orders associated, respectively, with the ground states of the local interaction terms and the global ground state of the total many-body Hamiltonian. This universal measure is bounded from below by the ground-state bipartite block entanglement. For many-body Hamiltonians that are sums of two-body interaction terms, a further inequality relates quantum frustration to the pairwise entanglement between the constituents of the local interaction terms. This additional bound is a consequence of the limits imposed by monogamy on entanglement shareability. We investigate the behavior of local pair frustration in quantum spin models with competing interactions on different length scales and show that valence bond solids associated with exact ground state dimerization correspond to a transition from generic frustration, i.e., geometric, common to classical and quantum systems alike, to genuine quantum frustration, i.e., solely due to the noncommutativity of the different local interaction terms. We discuss how such frustration transitions separating genuinely quantum orders from classical-like ones are detected by observable quantities such as the static structure factor and the interferometric visibility.

Spectral simplicity of apparent complexity. II. Exact complexities and complexity spectra

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Crutchfield, James P.

2018-03-01

The meromorphic functional calculus developed in Part I overcomes the nondiagonalizability of linear operators that arises often in the temporal evolution of complex systems and is generic to the metadynamics of predicting their behavior. Using the resulting spectral decomposition, we derive closed-form expressions for correlation functions, finite-length Shannon entropy-rate approximates, asymptotic entropy rate, excess entropy, transient information, transient and asymptotic state uncertainties, and synchronization information of stochastic processes generated by finite-state hidden Markov models. This introduces analytical tractability to investigating information processing in discrete-event stochastic processes, symbolic dynamics, and chaotic dynamical systems. Comparisons reveal mathematical similarities between complexity measures originally thought to capture distinct informational and computational properties. We also introduce a new kind of spectral analysis via coronal spectrograms and the frequency-dependent spectra of past-future mutual information. We analyze a number of examples to illustrate the methods, emphasizing processes with multivariate dependencies beyond pairwise correlation. This includes spectral decomposition calculations for one representative example in full detail.

Model for calculation of electrostatic contribution into protein stability

NASA Astrophysics Data System (ADS)

Kundrotas, Petras; Karshikoff, Andrey

2003-03-01

Existing models of the denatured state of proteins consider only one possible spatial distribution of protein charges and therefore are applicable to a limited number of cases. In this presentation a more general framework for the modeling of the denatured state is proposed. It is based on the assumption that the titratable groups of an unfolded protein can adopt a quasi-random distribution, restricted by the protein sequence. The model was tested on two proteins, barnase and N-terminal domain of the ribosomal protein L9. The calculated free energy of denaturation, Δ G( pH), reproduces the experimental data essentially better than the commonly used null approximation (NA). It was demonstrated that the seemingly good agreement with experimental data obtained by NA originates from the compensatory effect between the pair-wise electrostatic interactions and the desolvation energy of the individual sites. It was also found that the ionization properties of denatured proteins are influenced by the protein sequence.

Hydrodynamics of isotropic and liquid crystalline active polymer solutions.

PubMed

Ahmadi, Aphrodite; Marchetti, M C; Liverpool, T B

2006-12-01

We describe the large-scale collective behavior of solutions of polar biofilaments and stationary and mobile crosslinkers. Both mobile and stationary crosslinkers induce filament alignment promoting either polar or nematic order. In addition, mobile crosslinkers, such as clusters of motor proteins, exchange forces and torques among the filaments and render the homogeneous states unstable via filament bundling. We start from a Smoluchowski equation for rigid filaments in solutions, where pairwise crosslink-mediated interactions among the filaments yield translational and rotational currents. The large-scale properties of the system are described in terms of continuum equations for filament and motor densities, polarization, and alignment tensor obtained by coarse-graining the Smoluchovski equation. The possible homogeneous and inhomogeneous states of the systems are obtained as stable solutions of the dynamical equations and are characterized in terms of experimentally accessible parameters. We make contact with work by other authors and show that our model allows for an estimate of the various parameters in the hydrodynamic equations in terms of physical properties of the crosslinkers.

Distance-informed metric learning for Alzheimer's disease staging.

PubMed

Shi, Bibo; Wang, Zhewei; Liu, Jundong

2014-01-01

Identifying intermediate biomarkers of Alzheimer's disease (AD) is of great importance for diagnosis and prognosis of the disease. In this study, we develop a new AD staging method to classify patients into Normal Controls (NC), Mild Cognitive Impairment (MCI), and AD groups. Our solution employs a novel metric learning technique that improves classification rates through the guidance of some weak supervisory information in AD progression. More specifically, those information are in the form of pairwise constraints that specify the relative Mini Mental State Examination (MMSE) score disparity of two subjects, depending on whether they are in the same group or not. With the imposed constraints, the common knowledge that MCI generally sits in between of NC and AD can be integrated into the classification distance metric. Subjects from the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; 56 AD, 104 MCI, 161 controls) were used to demonstrate the improvements made comparing with two state-of-the-art metric learning solutions: large margin nearest neighbors (LMNN) and relevant component analysis (RCA).

Phase diagrams for the spatial public goods game with pool punishment

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Szabó, György; Perc, Matjaž

2011-03-01

The efficiency of institutionalized punishment is studied by evaluating the stationary states in the spatial public goods game comprising unconditional defectors, cooperators, and cooperating pool punishers as the three competing strategies. Fines and costs of pool punishment are considered as the two main parameters determining the stationary distributions of strategies on the square lattice. Each player collects a payoff from five five-person public goods games, and the evolution of strategies is subsequently governed by imitation based on pairwise comparisons at a low level of noise. The impact of pool punishment on the evolution of cooperation in structured populations is significantly different from that reported previously for peer punishment. Representative phase diagrams reveal remarkably rich behavior, depending also on the value of the synergy factor that characterizes the efficiency of investments payed into the common pool. Besides traditional single- and two-strategy stationary states, a rock-paper-scissors type of cyclic dominance can emerge in strikingly different ways.

Limiting similarity and Darwin's naturalization hypothesis: understanding the drivers of biotic resistance against invasive plant species.

PubMed

Yannelli, F A; Koch, C; Jeschke, J M; Kollmann, J

2017-03-01

Several hypotheses have been proposed to explain biotic resistance of a recipient plant community based on reduced niche opportunities for invasive alien plant species. The limiting similarity hypothesis predicts that invasive species are less likely to establish in communities of species holding similar functional traits. Likewise, Darwin's naturalization hypothesis states that invasive species closely related to the native community would be less successful. We tested both using the invasive alien Ambrosia artemisiifolia L. and Solidago gigantea Aiton, and grassland species used for ecological restoration in central Europe. We classified all plant species into groups based on functional traits obtained from trait databases and calculated the phylogenetic distance among them. In a greenhouse experiment, we submitted the two invasive species at two propagule pressures to competition with communities of ten native species from the same functional group. In another experiment, they were submitted to pairwise competition with native species selected from each functional group. At the community level, highest suppression for both invasive species was observed at low propagule pressure and not explained by similarity in functional traits. Moreover, suppression decreased asymptotically with increasing phylogenetic distance to species of the native community. When submitted to pairwise competition, suppression for both invasive species was also better explained by phylogenetic distance. Overall, our results support Darwin's naturalization hypothesis but not the limiting similarity hypothesis based on the selected traits. Biotic resistance of native communities against invasive species at an early stage of establishment is enhanced by competitive traits and phylogenetic relatedness.

Estimation of Salivary Parameters among Autoimmune Thyroiditis Patients.

PubMed

Syed, Yasmeen Amthul; Reddy, Bh Satheesh; Ramamurthy, T K; Rajendra, Kavitha; Nerella, Narendra Kumar; Krishnan, Meenakshi; Ramesh, M V; Mohammed, Rezwana Begum

2017-07-01

Saliva is a complex secretion that protects and lubricates the oral cavity. Various systemic diseases and their treatment alter the salivary gland function; one such disease is Autoimmune Thyroid Disease (AITD). AITD has been postulated to exert its hormonal influence on the salivary glands, leading to reduced salivary output. There's a paucity of literature, verifying the stated conjunction in human subjects. The aim was to investigate the salivary profile in AITD patients and its comparison with controls. Descriptive cross-sectional comparative study was conducted using convenience sampling method for screening the presence of thyroid disorders. Two groups comprising of 30 patients in each group diagnosed with autoimmune hypothyroiditis (n=30) and hyperthyroiditis (n=30) respectively and thirty healthy volunteers who were age and sex matched were included as controls. Saliva was collected and evaluated for Unstimulated Salivary Flow Rate (USSFR), pH and buffer capacity. ANOVA and Tukey post-hoc test was performed to find the statistical significance and for pairwise comparison. Statistically significant difference was observed between autoimmune hypothyroiditis, autoimmune hyperthyroiditis and control group with respect to USSFR (p<0.007), pH (p<0.001) and buffer capacity (p<0.001). On pairwise comparisons statistically significant difference was observed between autoimmune hypothyroiditis and autoimmune hyperthyroiditis with respect to controls. We conclude that significant involvement of salivary glands may occur in cases of AITD. Our study showed significant reduction of sialometric values in AITD patients when compared to controls. A strong clinical suspicion of thyroid diseases should be considered when there is chronic hyposalivation; hence thyroid profile must also be done, if the known causes have been excluded.

Learning multiple relative attributes with humans in the loop.

PubMed

Qian, Buyue; Wang, Xiang; Cao, Nan; Jiang, Yu-Gang; Davidson, Ian

2014-12-01

Semantic attributes have been recognized as a more spontaneous manner to describe and annotate image content. It is widely accepted that image annotation using semantic attributes is a significant improvement to the traditional binary or multiclass annotation due to its naturally continuous and relative properties. Though useful, existing approaches rely on an abundant supervision and high-quality training data, which limit their applicability. Two standard methods to overcome small amounts of guidance and low-quality training data are transfer and active learning. In the context of relative attributes, this would entail learning multiple relative attributes simultaneously and actively querying a human for additional information. This paper addresses the two main limitations in existing work: 1) it actively adds humans to the learning loop so that minimal additional guidance can be given and 2) it learns multiple relative attributes simultaneously and thereby leverages dependence amongst them. In this paper, we formulate a joint active learning to rank framework with pairwise supervision to achieve these two aims, which also has other benefits such as the ability to be kernelized. The proposed framework optimizes over a set of ranking functions (measuring the strength of the presence of attributes) simultaneously and dependently on each other. The proposed pairwise queries take the form of which one of these two pictures is more natural? These queries can be easily answered by humans. Extensive empirical study on real image data sets shows that our proposed method, compared with several state-of-the-art methods, achieves superior retrieval performance while requires significantly less human inputs.

Method for stationarity-segmentation of spike train data with application to the Pearson cross-correlation.

PubMed

Quiroga-Lombard, Claudio S; Hass, Joachim; Durstewitz, Daniel

2013-07-01

Correlations among neurons are supposed to play an important role in computation and information coding in the nervous system. Empirically, functional interactions between neurons are most commonly assessed by cross-correlation functions. Recent studies have suggested that pairwise correlations may indeed be sufficient to capture most of the information present in neural interactions. Many applications of correlation functions, however, implicitly tend to assume that the underlying processes are stationary. This assumption will usually fail for real neurons recorded in vivo since their activity during behavioral tasks is heavily influenced by stimulus-, movement-, or cognition-related processes as well as by more general processes like slow oscillations or changes in state of alertness. To address the problem of nonstationarity, we introduce a method for assessing stationarity empirically and then "slicing" spike trains into stationary segments according to the statistical definition of weak-sense stationarity. We examine pairwise Pearson cross-correlations (PCCs) under both stationary and nonstationary conditions and identify another source of covariance that can be differentiated from the covariance of the spike times and emerges as a consequence of residual nonstationarities after the slicing process: the covariance of the firing rates defined on each segment. Based on this, a correction of the PCC is introduced that accounts for the effect of segmentation. We probe these methods both on simulated data sets and on in vivo recordings from the prefrontal cortex of behaving rats. Rather than for removing nonstationarities, the present method may also be used for detecting significant events in spike trains.

Efficient conformational space exploration in ab initio protein folding simulation.

PubMed

Ullah, Ahammed; Ahmed, Nasif; Pappu, Subrata Dey; Shatabda, Swakkhar; Ullah, A Z M Dayem; Rahman, M Sohel

2015-08-01

Ab initio protein folding simulation largely depends on knowledge-based energy functions that are derived from known protein structures using statistical methods. These knowledge-based energy functions provide us with a good approximation of real protein energetics. However, these energy functions are not very informative for search algorithms and fail to distinguish the types of amino acid interactions that contribute largely to the energy function from those that do not. As a result, search algorithms frequently get trapped into the local minima. On the other hand, the hydrophobic-polar (HP) model considers hydrophobic interactions only. The simplified nature of HP energy function makes it limited only to a low-resolution model. In this paper, we present a strategy to derive a non-uniform scaled version of the real 20×20 pairwise energy function. The non-uniform scaling helps tackle the difficulty faced by a real energy function, whereas the integration of 20×20 pairwise information overcomes the limitations faced by the HP energy function. Here, we have applied a derived energy function with a genetic algorithm on discrete lattices. On a standard set of benchmark protein sequences, our approach significantly outperforms the state-of-the-art methods for similar models. Our approach has been able to explore regions of the conformational space which all the previous methods have failed to explore. Effectiveness of the derived energy function is presented by showing qualitative differences and similarities of the sampled structures to the native structures. Number of objective function evaluation in a single run of the algorithm is used as a comparison metric to demonstrate efficiency.

Pairwise comparisons and visual perceptions of equal area polygons.

PubMed

Adamic, P; Babiy, V; Janicki, R; Kakiashvili, T; Koczkodaj, W W; Tadeusiewicz, R

2009-02-01

The number of studies related to visual perception has been plentiful in recent years. Participants rated the areas of five randomly generated shapes of equal area, using a reference unit area that was displayed together with the shapes. Respondents were 179 university students from Canada and Poland. The average error estimated by respondents using the unit square was 25.75%. The error was substantially decreased to 5.51% when the shapes were compared to one another in pairs. This gain of 20.24% for this two-dimensional experiment was substantially better than the 11.78% gain reported in the previous one-dimensional experiments. This is the first statistically sound two-dimensional experiment demonstrating that pairwise comparisons improve accuracy.

C–IBI: Targeting cumulative coordination within an iterative protocol to derive coarse-grained models of (multi-component) complex fluids

DOE PAGES

de Oliveira, Tiago E.; Netz, Paulo A.; Kremer, Kurt; ...

2016-05-03

We present a coarse-graining strategy that we test for aqueous mixtures. The method uses pair-wise cumulative coordination as a target function within an iterative Boltzmann inversion (IBI) like protocol. We name this method coordination iterative Boltzmann inversion (C–IBI). While the underlying coarse-grained model is still structure based and, thus, preserves pair-wise solution structure, our method also reproduces solvation thermodynamics of binary and/or ternary mixtures. In addition, we observe much faster convergence within C–IBI compared to IBI. To validate the robustness, we apply C–IBI to study test cases of solvation thermodynamics of aqueous urea and a triglycine solvation in aqueous urea.

Relay entanglement and clusters of correlated spins

NASA Astrophysics Data System (ADS)

Doronin, S. I.; Zenchuk, A. I.

2018-06-01

Considering a spin-1/2 chain, we suppose that the entanglement passes from a given pair of particles to another one, thus establishing the relay transfer of entanglement along the chain. Therefore, we introduce the relay entanglement as a sum of all pairwise entanglements in a spin chain. For more detailed studying the effects of remote pairwise entanglements, we use the partial sums collecting entanglements between the spins separated by up to a certain number of nodes. The problem of entangled cluster formation is considered, and the geometric mean entanglement is introduced as a characteristic of quantum correlations in a cluster. Generally, the lifetime of a cluster decreases with an increase in its size.

Broadband continuous wave source localization via pair-wise, cochleagram processing

NASA Astrophysics Data System (ADS)

Nosal, Eva-Marie; Frazer, L. Neil

2005-04-01

A pair-wise processor has been developed for the passive localization of broadband continuous-wave underwater sources. The algorithm uses sparse hydrophone arrays and does not require previous knowledge of the source signature. It is applicable in multiple source situations. A spectrogram/cochleagram version of the algorithm has been developed in order to utilize higher frequencies at longer ranges where signal incoherence, and limited computational resources, preclude the use of full waveforms. Simulations demonstrating the robustness of the algorithm with respect to noise and environmental mismatch will be presented, together with initial results from the analysis of humpback whale song recorded at the Pacific Missile Range Facility off Kauai. [Work supported by MHPCC and ONR.

Effect of pairwise additivity on finite-temperature behavior of classical ideal gas

NASA Astrophysics Data System (ADS)

Shekaari, Ashkan; Jafari, Mahmoud

2018-05-01

Finite-temperature molecular dynamics simulations have been applied to inquire into the effect of pairwise additivity on the behavior of classical ideal gas within the temperature range of T = 250-4000 K via applying a variety of pair potentials and then examining the temperature dependence of a number of thermodynamical properties. Examining the compressibility factor reveals the most deviation from ideal-gas behavior for the Lennard-Jones system mainly due to the presence of both the attractive and repulsive terms. The systems with either attractive or repulsive intermolecular potentials are found to present no resemblance to real gases, but the most similarity to the ideal one as temperature rises.

Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects.

PubMed

Rashid, Barnaly; Damaraju, Eswar; Pearlson, Godfrey D; Calhoun, Vince D

2014-01-01

Schizophrenia (SZ) and bipolar disorder (BP) share significant overlap in clinical symptoms, brain characteristics, and risk genes, and both are associated with dysconnectivity among large-scale brain networks. Resting state functional magnetic resonance imaging (rsfMRI) data facilitates studying macroscopic connectivity among distant brain regions. Standard approaches to identifying such connectivity include seed-based correlation and data-driven clustering methods such as independent component analysis (ICA) but typically focus on average connectivity. In this study, we utilize ICA on rsfMRI data to obtain intrinsic connectivity networks (ICNs) in cohorts of healthy controls (HCs) and age matched SZ and BP patients. Subsequently, we investigated difference in functional network connectivity, defined as pairwise correlations among the timecourses of ICNs, between HCs and patients. We quantified differences in both static (average) and dynamic (windowed) connectivity during the entire scan duration. Disease-specific differences were identified in connectivity within different dynamic states. Notably, results suggest that patients make fewer transitions to some states (states 1, 2, and 4) compared to HCs, with most such differences confined to a single state. SZ patients showed more differences from healthy subjects than did bipolars, including both hyper and hypo connectivity in one common connectivity state (dynamic state 3). Also group differences between SZ and bipolar patients were identified in patterns (states) of connectivity involving the frontal (dynamic state 1) and frontal-parietal regions (dynamic state 3). Our results provide new information about these illnesses and strongly suggest that state-based analyses are critical to avoid averaging together important factors that can help distinguish these clinical groups.

Polyp morphology: an interobserver evaluation for the Paris classification among international experts.

PubMed

van Doorn, Sascha C; Hazewinkel, Y; East, James E; van Leerdam, Monique E; Rastogi, Amit; Pellisé, Maria; Sanduleanu-Dascalescu, Silvia; Bastiaansen, Barbara A J; Fockens, Paul; Dekker, Evelien

2015-01-01

The Paris classification is an international classification system for describing polyp morphology. Thus far, the validity and reproducibility of this classification have not been assessed. We aimed to determine the interobserver agreement for the Paris classification among seven Western expert endoscopists. A total of 85 short endoscopic video clips depicting polyps were created and assessed by seven expert endoscopists according to the Paris classification. After a digital training module, the same 85 polyps were assessed again. We calculated the interobserver agreement with a Fleiss kappa and as the proportion of pairwise agreement. The interobserver agreement of the Paris classification among seven experts was moderate with a Fleiss kappa of 0.42 and a mean pairwise agreement of 67%. The proportion of lesions assessed as "flat" by the experts ranged between 13 and 40% (P<0.001). After the digital training, the interobserver agreement did not change (kappa 0.38, pairwise agreement 60%). Our study is the first to validate the Paris classification for polyp morphology. We demonstrated only a moderate interobserver agreement among international Western experts for this classification system. Our data suggest that, in its current version, the use of this classification system in daily practice is questionable and it is unsuitable for comparative endoscopic research. We therefore suggest introduction of a simplification of the classification system.

When do correlations increase with firing rates in recurrent networks?

PubMed Central

2017-01-01

A central question in neuroscience is to understand how noisy firing patterns are used to transmit information. Because neural spiking is noisy, spiking patterns are often quantified via pairwise correlations, or the probability that two cells will spike coincidentally, above and beyond their baseline firing rate. One observation frequently made in experiments, is that correlations can increase systematically with firing rate. Theoretical studies have determined that stimulus-dependent correlations that increase with firing rate can have beneficial effects on information coding; however, we still have an incomplete understanding of what circuit mechanisms do, or do not, produce this correlation-firing rate relationship. Here, we studied the relationship between pairwise correlations and firing rates in recurrently coupled excitatory-inhibitory spiking networks with conductance-based synapses. We found that with stronger excitatory coupling, a positive relationship emerged between pairwise correlations and firing rates. To explain these findings, we used linear response theory to predict the full correlation matrix and to decompose correlations in terms of graph motifs. We then used this decomposition to explain why covariation of correlations with firing rate—a relationship previously explained in feedforward networks driven by correlated input—emerges in some recurrent networks but not in others. Furthermore, when correlations covary with firing rate, this relationship is reflected in low-rank structure in the correlation matrix. PMID:28448499

Correlations and Functional Connections in a Population of Grid Cells

PubMed Central

Roudi, Yasser

2015-01-01

We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern. PMID:25714908

Will kinematic Sunyaev-Zel'dovich measurements enhance the science return from galaxy redshift surveys?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sugiyama, Naonori S.; Okumura, Teppei; Spergel, David N., E-mail: nao.s.sugiyama@gmail.com, E-mail: tokumura@asiaa.sinica.edu.tw, E-mail: dns@astro.princeton.edu

2017-01-01

Yes. Future CMB experiments such as Advanced ACTPol and CMB-S4 should achieve measurements with S/N of > 0.1 for the typical host halo of galaxies in redshift surveys. These measurements will provide complementary measurements of the growth rate of large scale structure f and the expansion rate of the Universe H to galaxy clustering measurements. This paper emphasizes that there is significant information in the anisotropy of the relative pairwise kSZ measurements. We expand the relative pairwise kSZ power spectrum in Legendre polynomials and consider up to its octopole. Assuming that the noise in the filtered maps is uncorrelated betweenmore » the positions of galaxies in the survey, we derive a simple analytic form for the power spectrum covariance of the relative pairwise kSZ temperature in redshift space. While many previous studies have assumed optimistically that the optical depth of the galaxies τ{sub T} in the survey is known, we marginalize over τ{sub T}, to compute constraints on the growth rate f and the expansion rate H . For realistic survey parameters, we find that combining kSZ and galaxy redshift survey data reduces the marginalized 1-σ errors on H and f to ∼50-70% compared to the galaxy-only analysis.« less

Will kinematic Sunyaev-Zel'dovich measurements enhance the science return from galaxy redshift surveys?

NASA Astrophysics Data System (ADS)

Sugiyama, Naonori S.; Okumura, Teppei; Spergel, David N.

2017-01-01

Yes. Future CMB experiments such as Advanced ACTPol and CMB-S4 should achieve measurements with S/N of > 0.1 for the typical host halo of galaxies in redshift surveys. These measurements will provide complementary measurements of the growth rate of large scale structure f and the expansion rate of the Universe H to galaxy clustering measurements. This paper emphasizes that there is significant information in the anisotropy of the relative pairwise kSZ measurements. We expand the relative pairwise kSZ power spectrum in Legendre polynomials and consider up to its octopole. Assuming that the noise in the filtered maps is uncorrelated between the positions of galaxies in the survey, we derive a simple analytic form for the power spectrum covariance of the relative pairwise kSZ temperature in redshift space. While many previous studies have assumed optimistically that the optical depth of the galaxies τT in the survey is known, we marginalize over τT, to compute constraints on the growth rate f and the expansion rate H. For realistic survey parameters, we find that combining kSZ and galaxy redshift survey data reduces the marginalized 1-σ errors on H and f to ~50-70% compared to the galaxy-only analysis.

Galilean-invariant Nosé-Hoover-type thermostats.

PubMed

Pieprzyk, S; Heyes, D M; Maćkowiak, Sz; Brańka, A C

2015-03-01

A new pairwise Nosé-Hoover type thermostat for molecular dynamics (MD) simulations which is similar in construction to the pair-velocity thermostat of Allen and Schmid, [Mol. Simul. 33, 21 (2007)] (AS) but is based on the configurational thermostat is proposed and tested. Both thermostats generate the canonical velocity distribution, are Galilean invariant, and conserve linear and angular momentum. The unique feature of the pairwise thermostats is an unconditional conservation of the total angular momentum, which is important for thermalizing isolated systems and those nonequilibrium bulk systems manifesting local rotating currents. These thermostats were benchmarked against the corresponding Nosé-Hoover (NH) and Braga-Travis prescriptions, being based on the kinetic and configurational definitions of temperature, respectively. Some differences between the shear-rate-dependent shear viscosity from Sllod nonequilibrium MD are observed at high shear rates using the different thermostats. The thermostats based on the configurational temperature produced very similar monotically decaying shear viscosity (shear thinning) with increasing shear rate, while the NH method showed discontinuous shear thinning into a string phase, and the AS method produced a continuous increase of viscosity (shear thickening), after a shear thinning region at lower shear rates. Both pairwise additive thermostats are neither purely kinetic nor configurational in definition, and possible directions for further improvement in certain aspects are discussed.

Population and forensic genetic analyses of mitochondrial DNA control region variation from six major provinces in the Korean population.

PubMed

Hong, Seung Beom; Kim, Ki Cheol; Kim, Wook

2015-07-01

We generated complete mitochondrial DNA (mtDNA) control region sequences from 704 unrelated individuals residing in six major provinces in Korea. In addition to our earlier survey of the distribution of mtDNA haplogroup variation, a total of 560 different haplotypes characterized by 271 polymorphic sites were identified, of which 473 haplotypes were unique. The gene diversity and random match probability were 0.9989 and 0.0025, respectively. According to the pairwise comparison of the 704 control region sequences, the mean number of pairwise differences between individuals was 13.47±6.06. Based on the result of mtDNA control region sequences, pairwise FST genetic distances revealed genetic homogeneity of the Korean provinces on a peninsular level, except in samples from Jeju Island. This result indicates there may be a need to formulate a local mtDNA database for Jeju Island, to avoid bias in forensic parameter estimates caused by genetic heterogeneity of the population. Thus, the present data may help not only in personal identification but also in determining maternal lineages to provide an expanded and reliable Korean mtDNA database. These data will be available on the EMPOP database via accession number EMP00661. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Galilean-invariant Nosé-Hoover-type thermostats

NASA Astrophysics Data System (ADS)

Pieprzyk, S.; Heyes, D. M.; Maćkowiak, Sz.; Brańka, A. C.

2015-03-01

A new pairwise Nosé-Hoover type thermostat for molecular dynamics (MD) simulations which is similar in construction to the pair-velocity thermostat of Allen and Schmid, [Mol. Simul. 33, 21 (2007), 10.1080/08927020601052856] (AS) but is based on the configurational thermostat is proposed and tested. Both thermostats generate the canonical velocity distribution, are Galilean invariant, and conserve linear and angular momentum. The unique feature of the pairwise thermostats is an unconditional conservation of the total angular momentum, which is important for thermalizing isolated systems and those nonequilibrium bulk systems manifesting local rotating currents. These thermostats were benchmarked against the corresponding Nosé-Hoover (NH) and Braga-Travis prescriptions, being based on the kinetic and configurational definitions of temperature, respectively. Some differences between the shear-rate-dependent shear viscosity from Sllod nonequilibrium MD are observed at high shear rates using the different thermostats. The thermostats based on the configurational temperature produced very similar monotically decaying shear viscosity (shear thinning) with increasing shear rate, while the NH method showed discontinuous shear thinning into a string phase, and the AS method produced a continuous increase of viscosity (shear thickening), after a shear thinning region at lower shear rates. Both pairwise additive thermostats are neither purely kinetic nor configurational in definition, and possible directions for further improvement in certain aspects are discussed.

Enhanced identification of synergistic and antagonistic emergent interactions among three or more drugs

PubMed Central

White, Cynthia; Mao, Zhiyuan; Savage, Van M.

2016-01-01

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions—ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions. PMID:27278366

Pairwise Trajectory Management (PTM): Concept Description and Documentation

NASA Technical Reports Server (NTRS)

Jones, Kenneth M.; Graff, Thomas J.; Carreno, Victor; Chartrand, Ryan C.; Kibler, Jennifer L.

2018-01-01

Pairwise Trajectory Management (PTM) is an Interval Management (IM) concept that utilizes airborne and ground-based capabilities to enable the implementation of airborne pairwise spacing capabilities in oceanic regions. The goal of PTM is to use airborne surveillance and tools to manage an "at or greater than" inter-aircraft spacing. Due to the accuracy of Automatic Dependent Surveillance-Broadcast (ADS-B) information and the use of airborne spacing guidance, the minimum PTM spacing distance will be less than distances a controller can support with current automation systems that support oceanic operations. Ground tools assist the controller in evaluating the traffic picture and determining appropriate PTM clearances to be issued. Avionics systems provide guidance information that allows the flight crew to conform to the PTM clearance issued by the controller. The combination of a reduced minimum distance and airborne spacing management will increase the capacity and efficiency of aircraft operations at a given altitude or volume of airspace. This document provides an overview of the proposed application, a description of several key scenarios, a high level discussion of expected air and ground equipment and procedure changes, a description of a NASA human-machine interface (HMI) prototype for the flight crew that would support PTM operations, and initial benefits analysis results. Additionally, included as appendices, are the following documents: the PTM Operational Services and Environment Definition (OSED) document and a companion "Future Considerations for the Pairwise Trajectory Management (PTM) Concept: Potential Future Updates for the PTM OSED" paper, a detailed description of the PTM algorithm and PTM Limit Mach rules, initial PTM safety requirements and safety assessment documents, a detailed description of the design, development, and initial evaluations of the proposed flight crew HMI, an overview of the methodology and results of PTM pilot training requirements focus group and human-in-the-loop testing activities, and the PTM Pilot Guide.

Evolutionary relationships can be more important than abiotic conditions in predicting the outcome of plant-plant interactions

PubMed Central

Soliveres, Santiago; Torices, Rubén; Maestre, Fernando T.

2015-01-01

Positive and negative plant-plant interactions are major processes shaping plant communities. They are affected by environmental conditions and evolutionary relationships among the interacting plants. However, the generality of these factors as drivers of pairwise plant interactions and their combined effects remain virtually unknown. We conducted an observational study to assess how environmental conditions (altitude, temperature, irradiance and rainfall), the dispersal mechanism of beneficiary species and evolutionary relationships affected the co-occurrence of pairwise interactions in 11 Stipa tenacissima steppes located along an environmental gradient in Spain. We studied 197 pairwise plant-plant interactions involving the two major nurse plants (the resprouting shrub Quercus coccifera and the tussock grass S. tenacissima) found in these communities. The relative importance of the studied factors varied with the nurse species considered. None of the factors studied were good predictors of the co-ocurrence between S. tenacissima and its neighbours. However, both the dispersal mechanism of the beneficiary species and the phylogenetic distance between interacting species were crucial factors affecting the co-occurrence between Q. coccifera and its neighbours, while climatic conditions (irradiance) played a secondary role. Values of phylogenetic distance between 207-272.8 Myr led to competition, while values outside this range or fleshy-fruitness in the beneficiary species led to positive interactions. The low importance of environmental conditions as a general driver of pairwise interactions was caused by the species-specific response to changes in either rainfall or radiation. This result suggests that factors other than climatic conditions must be included in theoretical models aimed to generally predict the outcome of plant-plant interactions. Our study helps to improve current theory on plant-plant interactions and to understand how these interactions can respond to expected modifications in species composition and climate associated to ongoing global environmental change. PMID:25914426

Effectiveness of oral hydration in preventing contrast-induced acute kidney injury in patients undergoing coronary angiography or intervention: a pairwise and network meta-analysis.

PubMed

Zhang, Weidai; Zhang, Jiawei; Yang, Baojun; Wu, Kefei; Lin, Hanfei; Wang, Yanping; Zhou, Lihong; Wang, Huatao; Zeng, Chujuan; Chen, Xiao; Wang, Zhixing; Zhu, Junxing; Songming, Chen

2018-06-01

The effectiveness of oral hydration in preventing contrast-induced acute kidney injury (CI-AKI) in patients undergoing coronary angiography or intervention has not been well established. This study aims to evaluate the efficacy of oral hydration compared with intravenous hydration and other frequently used hydration strategies. PubMed, Embase, Web of Science, and the Cochrane central register of controlled trials were searched from inception to 8 October 2017. To be eligible for analysis, studies had to evaluate the relative efficacy of different prophylactic hydration strategies. We selected and assessed the studies that fulfilled the inclusion criteria and carried out a pairwise and network meta-analysis using RevMan5.2 and Aggregate Data Drug Information System 1.16.8 software. A total of four studies (538 participants) were included in our pairwise meta-analysis and 1754 participants from eight studies with four frequently used hydration strategies were included in a network meta-analysis. Pairwise meta-analysis indicated that oral hydration was as effective as intravenous hydration for the prevention of CI-AKI (5.88 vs. 8.43%; odds ratio: 0.73; 95% confidence interval: 0.36-1.47; P>0.05), with no significant heterogeneity between studies. Network meta-analysis showed that there was no significant difference in the prevention of CI-AKI. However, the rank probability plot suggested that oral plus intravenous hydration had a higher probability (51%) of being the best strategy, followed by diuretic plus intravenous hydration (39%) and oral hydration alone (10%). Intravenous hydration alone was the strategy with the highest probability (70%) of being the worst hydration strategy. Our study shows that oral hydration is not inferior to intravenous hydration for the prevention of CI-AKI in patients with normal or mild-to-moderate renal dysfunction undergoing coronary angiography or intervention.

Measurement of the pairwise kinematic Sunyaev-Zeldovich effect with Planck and BOSS data

NASA Astrophysics Data System (ADS)

Li, Yi-Chao; Ma, Yin-Zhe; Remazeilles, Mathieu; Moodley, Kavilan

2018-01-01

We present a new measurement of the kinetic Sunyaev-Zeldovich effect (kSZ) using Planck cosmic microwave background (CMB) and Baryon Oscillation Spectroscopic Survey (BOSS) data. Using the "LowZ North/South" galaxy catalogue from BOSS DR12, and the group catalogue from BOSS DR13, we evaluate the mean pairwise kSZ temperature associated with BOSS galaxies. We construct a "Central Galaxies Catalogue" (CGC) which consists of isolated galaxies from the original BOSS data set, and apply the aperture photometry (AP) filter to suppress the primary CMB contribution. By constructing a halo model to fit the pairwise kSZ function, we constrain the mean optical depth to be τ ¯=(0.53 ±0.32 )×10-4(1.65 σ ) for LowZ North CGC, τ ¯ =(0.30 ±0.57 )×10-4(0.53 σ ) for LowZ South CGC, and τ ¯ =(0.43 ±0.28 )×10-4(1.53 σ ) for DR13 Group. In addition, we vary the radius of the AP filter and find that the AP size of 7 arcmin gives the maximum detection for τ ¯. We also investigate the dependence of the signal with halo mass and find τ ¯ =(0.32 ±0.36 )×10-4(0.8 σ ) and τ ¯ =(0.67 ±0.46 )×10-4(1.4 σ ) for DR13 Group with halo mass restricted to, respectively, less and greater than its median halo mass, 1 012 h-1M⊙ . For the LowZ North CGC sample restricted to Mh≳1014 h-1M⊙ there is no detection of the kSZ signal because these high mass halos are associated with the high-redshift galaxies of the LowZ North catalogue, which have limited contribution to the pairwise kSZ signals.

PWC - PAIRWISE COMPARISON SOFTWARE: SOFTWARE PROGRAM FOR PAIRWISE COMPARISON TASK FOR PSYCHOMETRIC SCALING AND COGNITIVE RESEARCH

NASA Technical Reports Server (NTRS)

Ricks, W. R.

1994-01-01

PWC is used for pair-wise comparisons in both psychometric scaling techniques and cognitive research. The cognitive tasks and processes of a human operator of automated systems are now prominent considerations when defining system requirements. Recent developments in cognitive research have emphasized the potential utility of psychometric scaling techniques, such as multidimensional scaling, for representing human knowledge and cognitive processing structures. Such techniques involve collecting measurements of stimulus-relatedness from human observers. When data are analyzed using this scaling approach, an n-dimensional representation of the stimuli is produced. This resulting representation is said to describe the subject's cognitive or perceptual view of the stimuli. PWC applies one of the many techniques commonly used to acquire the data necessary for these types of analyses: pair-wise comparisons. PWC administers the task, collects the data from the test subject, and formats the data for analysis. It therefore addresses many of the limitations of the traditional "pen-and-paper" methods. By automating the data collection process, subjects are prevented from going back to check previous responses, the possibility of erroneous data transfer is eliminated, and the burden of the administration and taking of the test is eased. By using randomization, PWC ensures that subjects see the stimuli pairs presented in random order, and that each subject sees pairs in a different random order. PWC is written in Turbo Pascal v6.0 for IBM PC compatible computers running MS-DOS. The program has also been successfully compiled with Turbo Pascal v7.0. A sample executable is provided. PWC requires 30K of RAM for execution. The standard distribution medium for this program is a 5.25 inch 360K MS-DOS format diskette. Two electronic versions of the documentation are included on the diskette: one in ASCII format and one in MS Word for Windows format. PWC was developed in 1993.

Genetic association with low concentrations of high density lipoprotein-cholesterol in a pediatric population of the Middle East and North Africa: the CASPIAN-III study.

PubMed

Kelishadi, Roya; Haghjooy Javanmard, Shaghayegh; Tajadini, Mohammad Hasan; Mansourian, Marjan; Motlagh, Mohammad Esmaeil; Ardalan, Gelayol; Ban, Matthew

2014-11-01

Depressed high-density lipoprotein cholesterol (HDL-C) is prevalent the Middle East and North Africa. Some studies have documented associations between HDL-C and several single nucleotide polymorphisms (SNPs) in candidate gene polymorphisms. We investigated the associations between SNP genotypes and HDL-C levels in Iranian students, aged 10-18 years. Genotyping was performed in 750 randomly selected participants among those with low HDL-C levels (below 5th percentile), intermediate HDL-C levels (5-95th) and high HDL-C levels (above the 95th percentile). Minor allele frequencies (MAFs) of the SNPs of interest were compared between the three HDL-C groups. The vast majority of pairwise comparisons of MAFs between HDL-C groups were significant. Pairwise comparisons between low and high HDL-C groups showed significant between-group differences in MAFs for all SNPs, except for APOC3 rs5128. Pairwise comparisons between low and intermediate HDL-C groups showed significant between-group differences in MAFs for all SNPs, except for APOC3 rs5128 and APOA1 rs2893157. Pairwise comparisons between intermediate and high HDL-C groups showed significant between-group differences in MAFs for all SNPs, except for ABCA1 APOC3 rs5128 and APOA1 rs2893157. After adjustment for confounding factors, including age, sex, body mass index, low physical activity, consumption of saturated fats, and socioeconomic status, ABCA1 r1587K and CETP A373P significantly increased the risk of depressed HDL-C, and CETP Taq1 had a protective role. This study replicated several associations between HDL-C levels and candidate gene SNPs from genome-wide associations with HDL-C in Iranians from the pediatric age group. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign

PubMed Central

2007-01-01

Background Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA structure prediction. Results The proposed technique eliminates manual parameter selection in Dynalign and provides significant computational time savings in comparison to prior constraints in Dynalign while simultaneously providing a small improvement in the structural prediction accuracy. Savings are also realized in memory. In experiments over a 5S RNA dataset with average sequence length of approximately 120 nucleotides, the method reduces computation by a factor of 2. The method performs favorably in comparison to other programs for pairwise RNA structure prediction: yielding better accuracy, on average, and requiring significantly lesser computational resources. Conclusion Probabilistic analysis can be utilized in order to automate the determination of alignment constraints for pairwise RNA structure prediction methods in a principled fashion. These constraints can reduce the computational and memory requirements of these methods while maintaining or improving their accuracy of structural prediction. This extends the practical reach of these methods to longer length sequences. The revised Dynalign code is freely available for download. PMID:17445273

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

Attraction between Opposing Planar Dipolar Polymer Brushes

DOE PAGES

Mahalik, J. P.; Sumpter, Bobby G.; Kumar, Rajeev

2017-08-01

In this paper, we use a field theory approach to study the effects of permanent dipoles on interpenetration and free energy changes as a function of distance between two identical planar polymer brushes. Melts (i.e., solvent-free) and solvated brushes made up of polymers grafted on nonadsorbing substrates are studied. In particular, the weak coupling limit of the dipolar interactions is considered, which leads to concentration-dependent pairwise interactions, and the effects of orientational order are neglected. It is predicted that a gradual increase in the dipole moment of the polymer segments can lead to attractive interactions between the brushes at intermediatemore » separation distances. Finally, because classical theory of polymer brushes based on the strong stretching limit (SSL) and the standard self-consistent field theory (SCFT) simulations using the Flory’s χ parameter always predicts repulsive interactions at all separations, our work highlights the importance of dipolar interactions in tailoring and accurately predicting forces between polar polymeric interfaces in contact with each other.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mahalik, J. P.; Sumpter, Bobby G.; Kumar, Rajeev

In this paper, we use a field theory approach to study the effects of permanent dipoles on interpenetration and free energy changes as a function of distance between two identical planar polymer brushes. Melts (i.e., solvent-free) and solvated brushes made up of polymers grafted on nonadsorbing substrates are studied. In particular, the weak coupling limit of the dipolar interactions is considered, which leads to concentration-dependent pairwise interactions, and the effects of orientational order are neglected. It is predicted that a gradual increase in the dipole moment of the polymer segments can lead to attractive interactions between the brushes at intermediatemore » separation distances. Finally, because classical theory of polymer brushes based on the strong stretching limit (SSL) and the standard self-consistent field theory (SCFT) simulations using the Flory’s χ parameter always predicts repulsive interactions at all separations, our work highlights the importance of dipolar interactions in tailoring and accurately predicting forces between polar polymeric interfaces in contact with each other.« less

Learning planar Ising models

DOE PAGES

Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael; ...

2016-12-01

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less

Learning planar Ising models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael

Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less

The interactive evolution of human communication systems.

PubMed

Fay, Nicolas; Garrod, Simon; Roberts, Leo; Swoboda, Nik

2010-04-01

This paper compares two explanations of the process by which human communication systems evolve: iterated learning and social collaboration. It then reports an experiment testing the social collaboration account. Participants engaged in a graphical communication task either as a member of a community, where they interacted with seven different partners drawn from the same pool, or as a member of an isolated pair, where they interacted with the same partner across the same number of games. Participants' horizontal, pair-wise interactions led "bottom up" to the creation of an effective and efficient shared sign system in the community condition. Furthermore, the community-evolved sign systems were as effective and efficient as the local sign systems developed by isolated pairs. Finally, and as predicted by a social collaboration account, and not by an iterated learning account, interaction was critical to the creation of shared sign systems, with different isolated pairs establishing different local sign systems and different communities establishing different global sign systems. Copyright © 2010 Cognitive Science Society, Inc.

Selection of Malaysia School Youth Cadet Corps leader by using analytical hierarchy process: A case study at SMK Ahmad Boestamam

NASA Astrophysics Data System (ADS)

Mohamed, Nurul Huda; Ahmat, Norhayati; Mohamed, Nurul Akmal; Razmi, Syazwani Che; Mohamed, Nurul Farihan

2017-05-01

This research is a case study to identify the best criteria that a person should have as the leader of Malaysia School Youth Cadet Corps (Kadet Remaja Sekolah (KRS)) at SMK Ahmad Boestamam, Sitiawan in order to select the most appropriate person to hold the position. The approach used in this study is Analytical Hierarchy Process (AHP) which include pairwise comparison to compare the criteria and also the candidates. There are four criteria namely charisma, interpersonal communication, personality and physical. Four candidates (1, 2, 3 and 4) are being considered in this study. Purposive sampling and questionnaires are used as instruments to obtain the data which are then analyzed by using the AHP method. The final output indicates that Candidate 1 has the highest score, followed by Candidate 2, Candidate 4 and Candidate 3. It shows that this method is very helpful in the multi-criteria decision making when there are several options available.

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

DOE PAGES

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.; ...

2015-10-09

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

The Formation of the Earth-Moon System and the Planets

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Young, Richard E. (Technical Monitor)

1998-01-01

An overview of current theories of star and planet formation, with emphasis on terrestrial planet accretion and the formation of the Earth-Moon system is presented. These models are based upon observations of the Solar System and of young stars and their environments. They predict that rocky planets should form around most single stars, although it is possible that in some cases such planets are lost to orbital decay within the protoplanetary disk. The frequency of formation of gas giant planets is more difficult to predict theoretically. Terrestrial planets are believed to grow via pairwise accretion until the spacing of planetary orbits becomes large enough that the configuration is stable for the age of the system. Giant impacts during the final stages of growth can produce large planetary satellites, such as Earth's Moon. Giant planets begin their growth like terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates.

Efficient Multiple Kernel Learning Algorithms Using Low-Rank Representation.

PubMed

Niu, Wenjia; Xia, Kewen; Zu, Baokai; Bai, Jianchuan

2017-01-01

Unlike Support Vector Machine (SVM), Multiple Kernel Learning (MKL) allows datasets to be free to choose the useful kernels based on their distribution characteristics rather than a precise one. It has been shown in the literature that MKL holds superior recognition accuracy compared with SVM, however, at the expense of time consuming computations. This creates analytical and computational difficulties in solving MKL algorithms. To overcome this issue, we first develop a novel kernel approximation approach for MKL and then propose an efficient Low-Rank MKL (LR-MKL) algorithm by using the Low-Rank Representation (LRR). It is well-acknowledged that LRR can reduce dimension while retaining the data features under a global low-rank constraint. Furthermore, we redesign the binary-class MKL as the multiclass MKL based on pairwise strategy. Finally, the recognition effect and efficiency of LR-MKL are verified on the datasets Yale, ORL, LSVT, and Digit. Experimental results show that the proposed LR-MKL algorithm is an efficient kernel weights allocation method in MKL and boosts the performance of MKL largely.

Genic insights from integrated human proteomics in GeneCards.

PubMed

Fishilevich, Simon; Zimmerman, Shahar; Kohn, Asher; Iny Stein, Tsippi; Olender, Tsviya; Kolker, Eugene; Safran, Marilyn; Lancet, Doron

2016-01-01

GeneCards is a one-stop shop for searchable human gene annotations (http://www.genecards.org/). Data are automatically mined from ∼120 sources and presented in an integrated web card for every human gene. We report the application of recent advances in proteomics to enhance gene annotation and classification in GeneCards. First, we constructed the Human Integrated Protein Expression Database (HIPED), a unified database of protein abundance in human tissues, based on the publically available mass spectrometry (MS)-based proteomics sources ProteomicsDB, Multi-Omics Profiling Expression Database, Protein Abundance Across Organisms and The MaxQuant DataBase. The integrated database, residing within GeneCards, compares favourably with its individual sources, covering nearly 90% of human protein-coding genes. For gene annotation and comparisons, we first defined a protein expression vector for each gene, based on normalized abundances in 69 normal human tissues. This vector is portrayed in the GeneCards expression section as a bar graph, allowing visual inspection and comparison. These data are juxtaposed with transcriptome bar graphs. Using the protein expression vectors, we further defined a pairwise metric that helps assess expression-based pairwise proximity. This new metric for finding functional partners complements eight others, including sharing of pathways, gene ontology (GO) terms and domains, implemented in the GeneCards Suite. In parallel, we calculated proteome-based differential expression, highlighting a subset of tissues that overexpress a gene and subserving gene classification. This textual annotation allows users of VarElect, the suite's next-generation phenotyper, to more effectively discover causative disease variants. Finally, we define the protein-RNA expression ratio and correlation as yet another attribute of every gene in each tissue, adding further annotative information. The results constitute a significant enhancement of several GeneCards sections and help promote and organize the genome-wide structural and functional knowledge of the human proteome. Database URL:http://www.genecards.org/. © The Author(s) 2016. Published by Oxford University Press.

Spatial analysis of ecosystem service relationships to improve targeting of payments for hydrological services

PubMed Central

Manson, Robert H.; Ricketts, Taylor H.; Geissert, Daniel

2018-01-01

Payment for hydrological services (PHS) are popular tools for conserving ecosystems and their water-related services. However, improving the spatial targeting and impacts of PHS, as well as their ability to foster synergies with other ecosystem services (ES), remain challenging. We aimed at using spatial analyses to evaluate the targeting performance of México’s National PHS program in central Veracruz. We quantified the effectiveness of areas targeted for PHS in actually covering areas of high HS provision and social priority during 2003–2013. First, we quantified provisioning and spatial distributions of two target (water yield and soil retention), and one non-target ES (carbon storage) using InVEST. Subsequently, pairwise relationships among ES were quantified by using spatial correlation and overlap analyses. Finally, we evaluated targeting by: (i) prioritizing areas of individual and overlapping ES; (ii) quantifying spatial co-occurrences of these priority areas with those targeted by PHS; (iii) evaluating the extent to which PHS directly contribute to HS delivery; and (iv), testing if PHS targeted areas disproportionately covered areas with high ecological and social priority. We found that modelled priority areas exhibited non-random distributions and distinct spatial patterns. Our results show significant pairwise correlations between all ES suggesting synergistic relationships. However, our analysis showed a significantly lower overlap than expected and thus significant mismatches between PHS targeted areas and all types of priority areas. These findings suggest that the targeting of areas with high HS provisioning and social priority by Mexico’s PHS program could be improved significantly. This study underscores: (1) the importance of using maps of HS provisioning as main targeting criteria in PHS design to channel payments towards areas that require future conservation, and (2) the need for future research that helps balance ecological and socioeconomic targeting criteria. PMID:29462205

Interactive collision detection for deformable models using streaming AABBs.

PubMed

Zhang, Xinyu; Kim, Young J

2007-01-01

We present an interactive and accurate collision detection algorithm for deformable, polygonal objects based on the streaming computational model. Our algorithm can detect all possible pairwise primitive-level intersections between two severely deforming models at highly interactive rates. In our streaming computational model, we consider a set of axis aligned bounding boxes (AABBs) that bound each of the given deformable objects as an input stream and perform massively-parallel pairwise, overlapping tests onto the incoming streams. As a result, we are able to prevent performance stalls in the streaming pipeline that can be caused by expensive indexing mechanism required by bounding volume hierarchy-based streaming algorithms. At runtime, as the underlying models deform over time, we employ a novel, streaming algorithm to update the geometric changes in the AABB streams. Moreover, in order to get only the computed result (i.e., collision results between AABBs) without reading back the entire output streams, we propose a streaming en/decoding strategy that can be performed in a hierarchical fashion. After determining overlapped AABBs, we perform a primitive-level (e.g., triangle) intersection checking on a serial computational model such as CPUs. We implemented the entire pipeline of our algorithm using off-the-shelf graphics processors (GPUs), such as nVIDIA GeForce 7800 GTX, for streaming computations, and Intel Dual Core 3.4G processors for serial computations. We benchmarked our algorithm with different models of varying complexities, ranging from 15K up to 50K triangles, under various deformation motions, and the timings were obtained as 30 approximately 100 FPS depending on the complexity of models and their relative configurations. Finally, we made comparisons with a well-known GPU-based collision detection algorithm, CULLIDE [4] and observed about three times performance improvement over the earlier approach. We also made comparisons with a SW-based AABB culling algorithm [2] and observed about two times improvement.

Three-Dimensional Smoothed Particle Hydrodynamics Modeling of Preferential Flow Dynamics at Fracture Intersections on a High-Performance Computing Platform

NASA Astrophysics Data System (ADS)

Kordilla, J.; Bresinsky, L. T.

2017-12-01

The physical mechanisms that govern preferential flow dynamics in unsaturated fractured rock formations are complex and not well understood. Fracture intersections may act as an integrator of unsaturated flow, leading to temporal delay, intermittent flow and partitioning dynamics. In this work, a three-dimensional Pairwise-Force Smoothed Particle Hydrodynamics (PF-SPH) model is being applied in order to simulate gravity-driven multiphase flow at synthetic fracture intersections. SPH, as a meshless Lagrangian method, is particularly suitable for modeling deformable interfaces, such as three-phase contact dynamics of droplets, rivulets and free-surface films. The static and dynamic contact angle can be recognized as the most important parameter of gravity-driven free-surface flow. In SPH, surface tension and adhesion naturally emerges from the implemented pairwise fluid-fluid (sff) and solid-fluid (ssf) interaction force. The model was calibrated to a contact angle of 65°, which corresponds to the wetting properties of water on Poly(methyl methacrylate). The accuracy of the SPH simulations were validated against an analytical solution of Poiseuille flow between two parallel plates and against laboratory experiments. Using the SPH model, the complex flow mode transitions from droplet to rivulet flow of an experimental study were reproduced. Additionally, laboratory dimensionless scaling experiments of water droplets were successfully replicated in SPH. Finally, SPH simulations were used to investigate the partitioning dynamics of single droplets into synthetic horizontal fractures with various apertures (Δdf = 0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0 mm) and offsets (Δdoff = -1.5, -1.0, -0.5, 0, 1.0, 2.0, 3.0 mm). Fluid masses were measured in the domains R1, R2 and R3. The perfect conditions of ideally smooth surfaces and the SPH inherent advantage of particle tracking allow the recognition of small scale partitioning mechanisms and its importance for bulk flow behavior.

A molecular-field-based similarity study of non-nucleoside HIV-1 reverse transcriptase inhibitors

NASA Astrophysics Data System (ADS)

Mestres, Jordi; Rohrer, Douglas C.; Maggiora, Gerald M.

1999-01-01

This article describes a molecular-field-based similarity method for aligning molecules by matching their steric and electrostatic fields and an application of the method to the alignment of three structurally diverse non-nucleoside HIV-1 reverse transcriptase inhibitors. A brief description of the method, as implemented in the program MIMIC, is presented, including a discussion of pairwise and multi-molecule similarity-based matching. The application provides an example that illustrates how relative binding orientations of molecules can be determined in the absence of detailed structural information on their target protein. In the particular system studied here, availability of the X-ray crystal structures of the respective ligand-protein complexes provides a means for constructing an 'experimental model' of the relative binding orientations of the three inhibitors. The experimental model is derived by using MIMIC to align the steric fields of the three protein P66 subunit main chains, producing an overlay with a 1.41 Å average rms distance between the corresponding Cα's in the three chains. The inter-chain residue similarities for the backbone structures show that the main-chain conformations are conserved in the region of the inhibitor-binding site, with the major deviations located primarily in the 'finger' and RNase H regions. The resulting inhibitor structure overlay provides an experimental-based model that can be used to evaluate the quality of the direct a priori inhibitor alignment obtained using MIMIC. It is found that the 'best' pairwise alignments do not always correspond to the experimental model alignments. Therefore, simply combining the best pairwise alignments will not necessarily produce the optimal multi-molecule alignment. However, the best simultaneous three-molecule alignment was found to reproduce the experimental inhibitor alignment model. A pairwise consistency index has been derived which gauges the quality of combining the pairwise alignments and aids in efficiently forming the optimal multi-molecule alignment analysis. Two post-alignment procedures are described that provide information on feature-based and field-based pharmacophoric patterns. The former corresponds to traditional pharmacophore models and is derived from the contribution of individual atoms to the total similarity. The latter is based on molecular regions rather than atoms and is constructed by computing the percent contribution to the similarity of individual points in a regular lattice surrounding the molecules, which when contoured and colored visually depict regions of highly conserved similarity. A discussion of how the information provided by each of the procedures is useful in drug design is also presented.

Lg-Wave Cross Correlation and Epicentral Double-Difference Location in and near China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schaff, David P.; Richards, Paul G.; Slinkard, Megan

In this paper, we perform epicentral relocations for a broad area using cross-correlation measurements made on Lg waves recorded at regional distances on a sparse station network. Using a two-step procedure (pairwise locations and cluster locations), we obtain final locations for 5623 events—3689 for all of China from 1985 to 2005 and 1934 for the Wenchuan area from May to August 2008. These high-quality locations comprise 20% of a starting catalog for all of China and 25% of a catalog for Wenchuan. Of the 1934 events located for Wenchuan, 1662 (86%) were newly detected. The final locations explain the residualsmore » 89 times better than the catalog locations for all of China (3.7302–0.0417 s) and 32 times better than the catalog locations for Wenchuan (0.8413–0.0267 s). The average semimajor axes of the 95% confidence ellipses are 420 m for all of China and 370 m for Wenchuan. The average azimuthal gaps are 205° for all of China and 266° for Wenchuan. 98% of the station distances for all of China are over 200 km. The mean and maximum station distances are 898 and 2174 km. The robustness of our location estimates and various trade-offs and sensitivities is explored with different inversion parameters for the location, such as starting locations for iterative solutions and which singular values to include. Finally, our results provide order-of-magnitude improvements in locations for event clusters, using waveforms from a very sparse far-regional network for which data are openly available.« less

Lg-Wave Cross Correlation and Epicentral Double-Difference Location in and near China

DOE PAGES

Schaff, David P.; Richards, Paul G.; Slinkard, Megan; ...

2018-03-20

In this paper, we perform epicentral relocations for a broad area using cross-correlation measurements made on Lg waves recorded at regional distances on a sparse station network. Using a two-step procedure (pairwise locations and cluster locations), we obtain final locations for 5623 events—3689 for all of China from 1985 to 2005 and 1934 for the Wenchuan area from May to August 2008. These high-quality locations comprise 20% of a starting catalog for all of China and 25% of a catalog for Wenchuan. Of the 1934 events located for Wenchuan, 1662 (86%) were newly detected. The final locations explain the residualsmore » 89 times better than the catalog locations for all of China (3.7302–0.0417 s) and 32 times better than the catalog locations for Wenchuan (0.8413–0.0267 s). The average semimajor axes of the 95% confidence ellipses are 420 m for all of China and 370 m for Wenchuan. The average azimuthal gaps are 205° for all of China and 266° for Wenchuan. 98% of the station distances for all of China are over 200 km. The mean and maximum station distances are 898 and 2174 km. The robustness of our location estimates and various trade-offs and sensitivities is explored with different inversion parameters for the location, such as starting locations for iterative solutions and which singular values to include. Finally, our results provide order-of-magnitude improvements in locations for event clusters, using waveforms from a very sparse far-regional network for which data are openly available.« less

Toward the optimization of normalized graph Laplacian.

PubMed

Xie, Bo; Wang, Meng; Tao, Dacheng

2011-04-01

Normalized graph Laplacian has been widely used in many practical machine learning algorithms, e.g., spectral clustering and semisupervised learning. However, all of them use the Euclidean distance to construct the graph Laplacian, which does not necessarily reflect the inherent distribution of the data. In this brief, we propose a method to directly optimize the normalized graph Laplacian by using pairwise constraints. The learned graph is consistent with equivalence and nonequivalence pairwise relationships, and thus it can better represent similarity between samples. Meanwhile, our approach, unlike metric learning, automatically determines the scale factor during the optimization. The learned normalized Laplacian matrix can be directly applied in spectral clustering and semisupervised learning algorithms. Comprehensive experiments demonstrate the effectiveness of the proposed approach.

On the use of star-shaped genealogies in inference of coalescence times.

PubMed Central

Rosenberg, Noah A; Hirsh, Aaron E

2003-01-01

Genealogies from rapidly growing populations have approximate "star" shapes. We study the degree to which this approximation holds in the context of estimating the time to the most recent common ancestor (T(MRCA)) of a set of lineages. In an exponential growth scenario, we find that unless the product of population size (N) and growth rate (r) is at least approximately 10(5), the "pairwise comparison estimator" of T(MRCA) that derives from the star genealogy assumption has bias of 10-50%. Thus, the estimator is appropriate only for large populations that have grown very rapidly. The "tree-length estimator" of T(MRCA) is more biased than the pairwise comparison estimator, having low bias only for extremely large values of Nr. PMID:12930771

Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marre, O.; El Boustani, S.; Fregnac, Y.

We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogatesmore » that reproduce the spatial and temporal correlations of a given data set.« less

Time-Frequency Analysis Reveals Pairwise Interactions in Insect Swarms

NASA Astrophysics Data System (ADS)

Puckett, James G.; Ni, Rui; Ouellette, Nicholas T.

2015-06-01

The macroscopic emergent behavior of social animal groups is a classic example of dynamical self-organization, and is thought to arise from the local interactions between individuals. Determining these interactions from empirical data sets of real animal groups, however, is challenging. Using multicamera imaging and tracking, we studied the motion of individual flying midges in laboratory mating swarms. By performing a time-frequency analysis of the midge trajectories, we show that the midge behavior can be segmented into two distinct modes: one that is independent and composed of low-frequency maneuvers, and one that consists of higher-frequency nearly harmonic oscillations conducted in synchrony with another midge. We characterize these pairwise interactions, and make a hypothesis as to their biological function.

Market Competitiveness Evaluation of Mechanical Equipment with a Pairwise Comparisons Hierarchical Model.

PubMed

Hou, Fujun

2016-01-01

This paper provides a description of how market competitiveness evaluations concerning mechanical equipment can be made in the context of multi-criteria decision environments. It is assumed that, when we are evaluating the market competitiveness, there are limited number of candidates with some required qualifications, and the alternatives will be pairwise compared on a ratio scale. The qualifications are depicted as criteria in hierarchical structure. A hierarchical decision model called PCbHDM was used in this study based on an analysis of its desirable traits. Illustration and comparison shows that the PCbHDM provides a convenient and effective tool for evaluating the market competitiveness of mechanical equipment. The researchers and practitioners might use findings of this paper in application of PCbHDM.

Memory-efficient dynamic programming backtrace and pairwise local sequence alignment.

PubMed

Newberg, Lee A

2008-08-15

A backtrace through a dynamic programming algorithm's intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward-backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values from these checkpoints on an as-needed basis. Here we present an optimal checkpointing strategy, and demonstrate its utility with pairwise local sequence alignment of sequences of length 10,000. Sample C++-code for optimal backtrace is available in the Supplementary Materials. Supplementary data is available at Bioinformatics online.

STRUCTURAL DIVERSITY IN SOLID STATE CHEMISTRY:A Story of Squares and Triangles

NASA Astrophysics Data System (ADS)

Lee, Stephen

1996-10-01

A simple method for calculating the electronic energy of extended solids is discussed in this review. This method is based on the Huckel or tight-binding theory in which an explicit pairwise repulsion is added to the generally attractive forces of the partially filled valence electron bands. An expansion based on the power moments of the electronic density of states is discussed, and the structural energy difference theorem is reviewed. The repulsive energy is found to vary linearly with the second power moment of the electronic density of states. These results are then used to show why there is such a diversity of structure in the solid state. The elemental structures of the main group are rationalized by the above methods. It is the third and fourth power moments (which correspond in part to triangles and squares of bonded atoms) that account for much of the elemental structures of the main group elements of the periodic table. This serves as an introduction to further rationalizations of transition for noble metal alloy, binary and ternary telluride and selenide, and other intermetallic structures.Thus a cohesive picture of both covalent and metallic bonding is presented in this review, illustrating the importance of atomic orbitals and their overlap integrals.

Anomalous waterlike behavior in spherically-symmetric water models optimized with the relative entropy.

PubMed

Chaimovich, Aviel; Shell, M Scott

2009-03-28

Recent efforts have attempted to understand many of liquid water's anomalous properties in terms of effective spherically-symmetric pairwise molecular interactions entailing two characteristic length scales (so-called "core-softened" potentials). In this work, we examine the extent to which such simple descriptions of water are representative of the true underlying interactions by extracting coarse-grained potential functions that are optimized to reproduce the behavior of an all-atom model. To perform this optimization, we use a novel procedure based upon minimizing the relative entropy, a quantity that measures the extent to which a coarse-grained configurational ensemble overlaps with a reference all-atom one. We show that the optimized spherically-symmetric water models exhibit notable variations with the state conditions at which they were optimized, reflecting in particular the shifting accessibility of networked hydrogen bonding interactions. Moreover, we find that water's density and diffusivity anomalies are only reproduced when the effective coarse-grained potentials are allowed to vary with state. Our results therefore suggest that no state-independent spherically-symmetric potential can fully capture the interactions responsible for water's unique behavior; rather, the particular way in which the effective interactions vary with temperature and density contributes significantly to anomalous properties.

Reaching Agreement in Quantum Hybrid Networks.

PubMed

Shi, Guodong; Li, Bo; Miao, Zibo; Dower, Peter M; James, Matthew R

2017-07-20

We consider a basic quantum hybrid network model consisting of a number of nodes each holding a qubit, for which the aim is to drive the network to a consensus in the sense that all qubits reach a common state. Projective measurements are applied serving as control means, and the measurement results are exchanged among the nodes via classical communication channels. In this way the quantum-opeartion/classical-communication nature of hybrid quantum networks is captured, although coherent states and joint operations are not taken into consideration in order to facilitate a clear and explicit analysis. We show how to carry out centralized optimal path planning for this network with all-to-all classical communications, in which case the problem becomes a stochastic optimal control problem with a continuous action space. To overcome the computation and communication obstacles facing the centralized solutions, we also develop a distributed Pairwise Qubit Projection (PQP) algorithm, where pairs of nodes meet at a given time and respectively perform measurements at their geometric average. We show that the qubit states are driven to a consensus almost surely along the proposed PQP algorithm, and that the expected qubit density operators converge to the average of the network's initial values.

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

PubMed

Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z

2015-11-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization

PubMed Central

Brier, Matthew R.; Mitra, Anish; McCarthy, John E.; Ances, Beau M.; Snyder, Abraham Z.

2015-01-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. PMID:26208872

Affinity learning with diffusion on tensor product graph.

PubMed

Yang, Xingwei; Prasad, Lakshman; Latecki, Longin Jan

2013-01-01

In many applications, we are given a finite set of data points sampled from a data manifold and represented as a graph with edge weights determined by pairwise similarities of the samples. Often the pairwise similarities (which are also called affinities) are unreliable due to noise or due to intrinsic difficulties in estimating similarity values of the samples. As observed in several recent approaches, more reliable similarities can be obtained if the original similarities are diffused in the context of other data points, where the context of each point is a set of points most similar to it. Compared to the existing methods, our approach differs in two main aspects. First, instead of diffusing the similarity information on the original graph, we propose to utilize the tensor product graph (TPG) obtained by the tensor product of the original graph with itself. Since TPG takes into account higher order information, it is not a surprise that we obtain more reliable similarities. However, it comes at the price of higher order computational complexity and storage requirement. The key contribution of the proposed approach is that the information propagation on TPG can be computed with the same computational complexity and the same amount of storage as the propagation on the original graph. We prove that a graph diffusion process on TPG is equivalent to a novel iterative algorithm on the original graph, which is guaranteed to converge. After its convergence we obtain new edge weights that can be interpreted as new, learned affinities. We stress that the affinities are learned in an unsupervised setting. We illustrate the benefits of the proposed approach for data manifolds composed of shapes, images, and image patches on two very different tasks of image retrieval and image segmentation. With learned affinities, we achieve the bull's eye retrieval score of 99.99 percent on the MPEG-7 shape dataset, which is much higher than the state-of-the-art algorithms. When the data- points are image patches, the NCut with the learned affinities not only significantly outperforms the NCut with the original affinities, but it also outperforms state-of-the-art image segmentation methods.

Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting.

PubMed

Schmidt, Katharina; Aumann, Ines; Hollander, Ines; Damm, Kathrin; von der Schulenburg, J-Matthias Graf

2015-12-24

The Analytic Hierarchy Process (AHP), developed by Saaty in the late 1970s, is one of the methods for multi-criteria decision making. The AHP disaggregates a complex decision problem into different hierarchical levels. The weight for each criterion and alternative are judged in pairwise comparisons and priorities are calculated by the Eigenvector method. The slowly increasing application of the AHP was the motivation for this study to explore the current state of its methodology in the healthcare context. A systematic literature review was conducted by searching the Pubmed and Web of Science databases for articles with the following keywords in their titles or abstracts: "Analytic Hierarchy Process," "Analytical Hierarchy Process," "multi-criteria decision analysis," "multiple criteria decision," "stated preference," and "pairwise comparison." In addition, we developed reporting criteria to indicate whether the authors reported important aspects and evaluated the resulting studies' reporting. The systematic review resulted in 121 articles. The number of studies applying AHP has increased since 2005. Most studies were from Asia (almost 30%), followed by the US (25.6%). On average, the studies used 19.64 criteria throughout their hierarchical levels. Furthermore, we restricted a detailed analysis to those articles published within the last 5 years (n = 69). The mean of participants in these studies were 109, whereas we identified major differences in how the surveys were conducted. The evaluation of reporting showed that the mean of reported elements was about 6.75 out of 10. Thus, 12 out of 69 studies reported less than half of the criteria. The AHP has been applied inconsistently in healthcare research. A minority of studies described all the relevant aspects. Thus, the statements in this review may be biased, as they are restricted to the information available in the papers. Hence, further research is required to discover who should be interviewed and how, how inconsistent answers should be dealt with, and how the outcome and stability of the results should be presented. In addition, we need new insights to determine which target group can best handle the challenges of the AHP.

Deconstructing a Species-Complex: Geometric Morphometric and Molecular Analyses Define Species in the Western Rattlesnake (Crotalus viridis)

PubMed Central

Davis, Mark A.; Douglas, Marlis R.; Collyer, Michael L.; Douglas, Michael E.

2016-01-01

Morphological data are a conduit for the recognition and description of species, and their acquisition has recently been broadened by geometric morphometric (GM) approaches that co-join the collection of digital data with exploratory ‘big data’ analytics. We employed this approach to dissect the Western Rattlesnake (Crotalus viridis) species-complex in North America, currently partitioned by mitochondrial (mt)DNA analyses into eastern and western lineages (two and seven subspecies, respectively). The GM data (i.e., 33 dorsal and 50 lateral head landmarks) were gleaned from 2,824 individuals located in 10 museum collections. We also downloaded and concatenated sequences for six mtDNA genes from the NCBI GenBank database. GM analyses revealed significant head shape differences attributable to size and subspecies-designation (but not their interactions). Pairwise shape distances among subspecies were significantly greater than those derived from ancestral character states via squared-change parsimony, with the greatest differences separating those most closely related. This, in turn, suggests the potential for historic character displacement as a diversifying force in the complex. All subspecies, save one, were significantly differentiated in a Bayesian discriminant function analysis (DFA), regardless of whether our priors were uniform or informative (i.e., mtDNA data). Finally, shape differences among sister-clades were significantly greater than expected by chance alone under a Brownian model of evolution, promoting the hypothesis that selection rather than drift was the driving force in the evolution of the complex. Lastly, we combine head shape and mtDNA data so as to derived an integrative taxonomy that produced robust boundaries for six OTUs (operational taxonomic units) of the C. viridis complex. We suggest these boundaries are concomitant with species-status and subsequently provide a relevant nomenclature for its recognition and representation. PMID:26816132

Mimvec: a deep learning approach for analyzing the human phenome.

PubMed

Gan, Mingxin; Li, Wenran; Zeng, Wanwen; Wang, Xiaojian; Jiang, Rui

2017-09-21

The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using the traditional term frequency-inverse document frequency (TF-IDF) formulation. This framework, though intuitive, not only ignores semantic relationships between words but also tends to produce high-dimensional vectors, and hence lacks the ability to precisely capture intrinsic semantic characteristics of biomedical documents. To overcome these limitations, we propose a framework called mimvec to analyze the human phenome by making use of the state-of-the-art deep learning technique in natural language processing. We converted 24,061 records in the Online Mendelian Inheritance in Man (OMIM) database to low-dimensional vectors using our method. We demonstrated that the vector presentation not only effectively enabled classification of phenotype records against gene ones, but also succeeded in discriminating diseases of different inheritance styles and different mechanisms. We further derived pairwise phenotype similarities between 7988 human inherited diseases using their vector presentations. With a joint analysis of this phenome with multiple genomic data, we showed that phenotype overlap indeed implied genotype overlap. We finally used the derived phenotype similarities with genomic data to prioritize candidate genes and demonstrated advantages of this method over existing ones. Our method is capable of not only capturing semantic relationships between words in biomedical records but also alleviating the dimensional disaster accompanying the traditional TF-IDF framework. With the approaching of precision medicine, there will be abundant electronic records of medicine and health awaiting for deep analysis, and we expect to see a wide spectrum of applications borrowing the idea of our method in the near future.

Brain tumor detection and segmentation in a CRF (conditional random fields) framework with pixel-pairwise affinity and superpixel-level features.

PubMed

Wu, Wei; Chen, Albert Y C; Zhao, Liang; Corso, Jason J

2014-03-01

Detection and segmentation of a brain tumor such as glioblastoma multiforme (GBM) in magnetic resonance (MR) images are often challenging due to its intrinsically heterogeneous signal characteristics. A robust segmentation method for brain tumor MRI scans was developed and tested. Simple thresholds and statistical methods are unable to adequately segment the various elements of the GBM, such as local contrast enhancement, necrosis, and edema. Most voxel-based methods cannot achieve satisfactory results in larger data sets, and the methods based on generative or discriminative models have intrinsic limitations during application, such as small sample set learning and transfer. A new method was developed to overcome these challenges. Multimodal MR images are segmented into superpixels using algorithms to alleviate the sampling issue and to improve the sample representativeness. Next, features were extracted from the superpixels using multi-level Gabor wavelet filters. Based on the features, a support vector machine (SVM) model and an affinity metric model for tumors were trained to overcome the limitations of previous generative models. Based on the output of the SVM and spatial affinity models, conditional random fields theory was applied to segment the tumor in a maximum a posteriori fashion given the smoothness prior defined by our affinity model. Finally, labeling noise was removed using "structural knowledge" such as the symmetrical and continuous characteristics of the tumor in spatial domain. The system was evaluated with 20 GBM cases and the BraTS challenge data set. Dice coefficients were computed, and the results were highly consistent with those reported by Zikic et al. (MICCAI 2012, Lecture notes in computer science. vol 7512, pp 369-376, 2012). A brain tumor segmentation method using model-aware affinity demonstrates comparable performance with other state-of-the art algorithms.

Post-Hartree-Fock studies of the He/Mg(0001) interaction: Anti-corrugation, screening, and pairwise additivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lara-Castells, María Pilar de, E-mail: Pilar.deLara.Castells@csic.es; Fernández-Perea, Ricardo; Madzharova, Fani

2016-06-28

The adsorption of noble gases on metallic surfaces represents a paradigmatic case of van-der-Waals (vdW) interaction due to the role of screening effects on the corrugation of the interaction potential [J. L. F. Da Silva et al., Phys. Rev. Lett. 90, 066104 (2003)]. The extremely small adsorption energy of He atoms on the Mg(0001) surface (below 3 meV) and the delocalized nature and mobility of the surface electrons make the He/Mg(0001) system particularly challenging, even for state-of-the-art vdW-corrected density functional-based (vdW-DFT) approaches [M. P. de Lara-Castells et al., J. Chem. Phys. 143, 194701 (2015)]. In this work, we meet thismore » challenge by applying two different procedures. First, the dispersion-corrected second-order Möller-Plesset perturbation theory (MP2C) approach is adopted, using bare metal clusters of increasing size. Second, the method of increments [H. Stoll, J. Chem. Phys. 97, 8449 (1992)] is applied at coupled cluster singles and doubles and perturbative triples level, using embedded cluster models of the metal surface. Both approaches provide clear evidences of the anti-corrugation of the interaction potential: the He atom prefers on-top sites, instead of the expected hollow sites. This is interpreted as a signature of the screening of the He atom by the metal for the on-top configuration. The strong screening in the metal is clearly reflected in the relative contribution of successively deeper surface layers to the main dispersion contribution. Aimed to assist future dynamical simulations, a pairwise potential model for the He/surface interaction as a sum of effective He–Mg pair potentials is also presented, as an improvement of the approximation using isolated He–Mg pairs.« less

Estimation of Salivary Parameters among Autoimmune Thyroiditis Patients

PubMed Central

Reddy, BH Satheesh; Ramamurthy, TK; Rajendra, Kavitha; Nerella, Narendra Kumar; Krishnan, Meenakshi; Ramesh, MV; Mohammed, Rezwana Begum

2017-01-01

Introduction Saliva is a complex secretion that protects and lubricates the oral cavity. Various systemic diseases and their treatment alter the salivary gland function; one such disease is Autoimmune Thyroid Disease (AITD). AITD has been postulated to exert its hormonal influence on the salivary glands, leading to reduced salivary output. There’s a paucity of literature, verifying the stated conjunction in human subjects. Aim The aim was to investigate the salivary profile in AITD patients and its comparison with controls. Materials and Methods Descriptive cross-sectional comparative study was conducted using convenience sampling method for screening the presence of thyroid disorders. Two groups comprising of 30 patients in each group diagnosed with autoimmune hypothyroiditis (n=30) and hyperthyroiditis (n=30) respectively and thirty healthy volunteers who were age and sex matched were included as controls. Saliva was collected and evaluated for Unstimulated Salivary Flow Rate (USSFR), pH and buffer capacity. ANOVA and Tukey post-hoc test was performed to find the statistical significance and for pairwise comparison. Results Statistically significant difference was observed between autoimmune hypothyroiditis, autoimmune hyperthyroiditis and control group with respect to USSFR (p<0.007), pH (p<0.001) and buffer capacity (p<0.001). On pairwise comparisons statistically significant difference was observed between autoimmune hypothyroiditis and autoimmune hyperthyroiditis with respect to controls. Conclusion We conclude that significant involvement of salivary glands may occur in cases of AITD. Our study showed significant reduction of sialometric values in AITD patients when compared to controls. A strong clinical suspicion of thyroid diseases should be considered when there is chronic hyposalivation; hence thyroid profile must also be done, if the known causes have been excluded. PMID:28893031

Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model

PubMed Central

Fu, Changhong; Duan, Ran; Kircali, Dogan; Kayacan, Erdal

2016-01-01

In this paper, we present a novel onboard robust visual algorithm for long-term arbitrary 2D and 3D object tracking using a reliable global-local object model for unmanned aerial vehicle (UAV) applications, e.g., autonomous tracking and chasing a moving target. The first main approach in this novel algorithm is the use of a global matching and local tracking approach. In other words, the algorithm initially finds feature correspondences in a way that an improved binary descriptor is developed for global feature matching and an iterative Lucas–Kanade optical flow algorithm is employed for local feature tracking. The second main module is the use of an efficient local geometric filter (LGF), which handles outlier feature correspondences based on a new forward-backward pairwise dissimilarity measure, thereby maintaining pairwise geometric consistency. In the proposed LGF module, a hierarchical agglomerative clustering, i.e., bottom-up aggregation, is applied using an effective single-link method. The third proposed module is a heuristic local outlier factor (to the best of our knowledge, it is utilized for the first time to deal with outlier features in a visual tracking application), which further maximizes the representation of the target object in which we formulate outlier feature detection as a binary classification problem with the output features of the LGF module. Extensive UAV flight experiments show that the proposed visual tracker achieves real-time frame rates of more than thirty-five frames per second on an i7 processor with 640 × 512 image resolution and outperforms the most popular state-of-the-art trackers favorably in terms of robustness, efficiency and accuracy. PMID:27589769

Multiple-region directed functional connectivity based on phase delays.

PubMed

Goelman, Gadi; Dan, Rotem

2017-03-01

Network analysis is increasingly advancing the field of neuroimaging. Neural networks are generally constructed from pairwise interactions with an assumption of linear relations between them. Here, a high-order statistical framework to calculate directed functional connectivity among multiple regions, using wavelet analysis and spectral coherence has been presented. The mathematical expression for 4 regions was derived and used to characterize a quartet of regions as a linear, combined (nonlinear), or disconnected network. Phase delays between regions were used to obtain network's temporal hierarchy and directionality. The validity of the mathematical derivation along with the effects of coupling strength and noise on its outcomes were studied by computer simulations of the Kuramoto model. The simulations demonstrated correct directionality for a large range of coupling strength and low sensitivity to Gaussian noise compared with pairwise coherences. The analysis was applied to resting-state fMRI data of 40 healthy young subjects to characterize the ventral visual system, motor system and default mode network (DMN). It was shown that the ventral visual system was predominantly composed of linear networks while the motor system and the DMN were composed of combined (nonlinear) networks. The ventral visual system exhibits its known temporal hierarchy, the motor system exhibits center ↔ out hierarchy and the DMN has dorsal ↔ ventral and anterior ↔ posterior organizations. The analysis can be applied in different disciplines such as seismology, or economy and in a variety of brain data including stimulus-driven fMRI, electrophysiology, EEG, and MEG, thus open new horizons in brain research. Hum Brain Mapp 38:1374-1386, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Modeling Pair Distribution Functions of Rare-Earth Phosphate Glasses Using Principal Component Analysis.

PubMed

Cole, Jacqueline M; Cheng, Xie; Payne, Michael C

2016-11-07

The use of principal component analysis (PCA) to statistically infer features of local structure from experimental pair distribution function (PDF) data is assessed on a case study of rare-earth phosphate glasses (REPGs). Such glasses, codoped with two rare-earth ions (R and R') of different sizes and optical properties, are of interest to the laser industry. The determination of structure-property relationships in these materials is an important aspect of their technological development. Yet, realizing the local structure of codoped REPGs presents significant challenges relative to their singly doped counterparts; specifically, R and R' are difficult to distinguish in terms of establishing relative material compositions, identifying atomic pairwise correlation profiles in a PDF that are associated with each ion, and resolving peak overlap of such profiles in PDFs. This study demonstrates that PCA can be employed to help overcome these structural complications, by statistically inferring trends in PDFs that exist for a restricted set of experimental data on REPGs, and using these as training data to predict material compositions and PDF profiles in unknown codoped REPGs. The application of these PCA methods to resolve individual atomic pairwise correlations in t(r) signatures is also presented. The training methods developed for these structural predictions are prevalidated by testing their ability to reproduce known physical phenomena, such as the lanthanide contraction, on PDF signatures of the structurally simpler singly doped REPGs. The intrinsic limitations of applying PCA to analyze PDFs relative to the quality control of source data, data processing, and sample definition, are also considered. While this case study is limited to lanthanide-doped REPGs, this type of statistical inference may easily be extended to other inorganic solid-state materials and be exploited in large-scale data-mining efforts that probe many t(r) functions.

Post-Hartree-Fock studies of the He/Mg(0001) interaction: Anti-corrugation, screening, and pairwise additivity

NASA Astrophysics Data System (ADS)

de Lara-Castells, María Pilar; Fernández-Perea, Ricardo; Madzharova, Fani; Voloshina, Elena

2016-06-01

The adsorption of noble gases on metallic surfaces represents a paradigmatic case of van-der-Waals (vdW) interaction due to the role of screening effects on the corrugation of the interaction potential [J. L. F. Da Silva et al., Phys. Rev. Lett. 90, 066104 (2003)]. The extremely small adsorption energy of He atoms on the Mg(0001) surface (below 3 meV) and the delocalized nature and mobility of the surface electrons make the He/Mg(0001) system particularly challenging, even for state-of-the-art vdW-corrected density functional-based (vdW-DFT) approaches [M. P. de Lara-Castells et al., J. Chem. Phys. 143, 194701 (2015)]. In this work, we meet this challenge by applying two different procedures. First, the dispersion-corrected second-order Möller-Plesset perturbation theory (MP2C) approach is adopted, using bare metal clusters of increasing size. Second, the method of increments [H. Stoll, J. Chem. Phys. 97, 8449 (1992)] is applied at coupled cluster singles and doubles and perturbative triples level, using embedded cluster models of the metal surface. Both approaches provide clear evidences of the anti-corrugation of the interaction potential: the He atom prefers on-top sites, instead of the expected hollow sites. This is interpreted as a signature of the screening of the He atom by the metal for the on-top configuration. The strong screening in the metal is clearly reflected in the relative contribution of successively deeper surface layers to the main dispersion contribution. Aimed to assist future dynamical simulations, a pairwise potential model for the He/surface interaction as a sum of effective He-Mg pair potentials is also presented, as an improvement of the approximation using isolated He-Mg pairs.

Multiple graph regularized protein domain ranking.

PubMed

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Automatic segmentation of mitochondria in EM data using pairwise affinity factorization and graph-based contour searching.

PubMed

Ghita, Ovidiu; Dietlmeier, Julia; Whelan, Paul F

2014-10-01

In this paper, we investigate the segmentation of closed contours in subcellular data using a framework that primarily combines the pairwise affinity grouping principles with a graph partitioning contour searching approach. One salient problem that precluded the application of these methods to large scale segmentation problems is the onerous computational complexity required to generate comprehensive representations that include all pairwise relationships between all pixels in the input data. To compensate for this problem, a practical solution is to reduce the complexity of the input data by applying an over-segmentation technique prior to the application of the computationally demanding strands of the segmentation process. This approach opens the opportunity to build specific shape and intensity models that can be successfully employed to extract the salient structures in the input image which are further processed to identify the cycles in an undirected graph. The proposed framework has been applied to the segmentation of mitochondria membranes in electron microscopy data which are characterized by low contrast and low signal-to-noise ratio. The algorithm has been quantitatively evaluated using two datasets where the segmentation results have been compared with the corresponding manual annotations. The performance of the proposed algorithm has been measured using standard metrics, such as precision and recall, and the experimental results indicate a high level of segmentation accuracy.

Remarkable sequence conservation of the last intron in the PKD1 gene.

PubMed

Rodova, Marianna; Islam, M Rafiq; Peterson, Kenneth R; Calvet, James P

2003-10-01

The last intron of the PKD1 gene (intron 45) was found to have exceptionally high sequence conservation across four mammalian species: human, mouse, rat, and dog. This conservation did not extend to the comparable intron in pufferfish. Pairwise comparisons for intron 45 showed 91% identity (human vs. dog) to 100% identity (mouse vs. rat) for an average for all four species of 94% identity. In contrast, introns 43 and 44 of the PKD1 gene had average pairwise identities of 57% and 54%, and exons 43, 44, and 45 and the coding region of exon 46 had average pairwise identities of 80%, 84%, 82%, and 80%. Intron 45 is 90 to 95 bp in length, with the major region of sequence divergence being in a central 4-bp to 9-bp variable region. RNA secondary structure analysis of intron 45 predicts a branching stem-loop structure in which the central variable region lies in one loop and the putative branch point sequence lies in another loop, suggesting that the intron adopts a specific stem-loop structure that may be important for its removal. Although intron 45 appears to conform to the class of small, G-triplet-containing introns that are spliced by a mechanism utilizing intron definition, its high sequence conservation may be a reflection of constraints imposed by a unique mechanism that coordinates splicing of this last PKD1 intron with polyadenylation.

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hardy, David J., E-mail: dhardy@illinois.edu; Schulten, Klaus; Wolff, Matthew A.

2016-03-21

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation methodmore » (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle–mesh Ewald method falls short.« less

Evaluating the Quality of Evidence from a Network Meta-Analysis

PubMed Central

Salanti, Georgia; Del Giovane, Cinzia; Chaimani, Anna; Caldwell, Deborah M.; Higgins, Julian P. T.

2014-01-01

Systematic reviews that collate data about the relative effects of multiple interventions via network meta-analysis are highly informative for decision-making purposes. A network meta-analysis provides two types of findings for a specific outcome: the relative treatment effect for all pairwise comparisons, and a ranking of the treatments. It is important to consider the confidence with which these two types of results can enable clinicians, policy makers and patients to make informed decisions. We propose an approach to determining confidence in the output of a network meta-analysis. Our proposed approach is based on methodology developed by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group for pairwise meta-analyses. The suggested framework for evaluating a network meta-analysis acknowledges (i) the key role of indirect comparisons (ii) the contributions of each piece of direct evidence to the network meta-analysis estimates of effect size; (iii) the importance of the transitivity assumption to the validity of network meta-analysis; and (iv) the possibility of disagreement between direct evidence and indirect evidence. We apply our proposed strategy to a systematic review comparing topical antibiotics without steroids for chronically discharging ears with underlying eardrum perforations. The proposed framework can be used to determine confidence in the results from a network meta-analysis. Judgements about evidence from a network meta-analysis can be different from those made about evidence from pairwise meta-analyses. PMID:24992266

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations.

PubMed

Hardy, David J; Wolff, Matthew A; Xia, Jianlin; Schulten, Klaus; Skeel, Robert D

2016-03-21

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation method (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle-mesh Ewald method falls short.

Determination of ensemble-average pairwise root mean-square deviation from experimental B-factors.

PubMed

Kuzmanic, Antonija; Zagrovic, Bojan

2010-03-03

Root mean-square deviation (RMSD) after roto-translational least-squares fitting is a measure of global structural similarity of macromolecules used commonly. On the other hand, experimental x-ray B-factors are used frequently to study local structural heterogeneity and dynamics in macromolecules by providing direct information about root mean-square fluctuations (RMSF) that can also be calculated from molecular dynamics simulations. We provide a mathematical derivation showing that, given a set of conservative assumptions, a root mean-square ensemble-average of an all-against-all distribution of pairwise RMSD for a single molecular species, (1/2), is directly related to average B-factors () and (1/2). We show this relationship and explore its limits of validity on a heterogeneous ensemble of structures taken from molecular dynamics simulations of villin headpiece generated using distributed-computing techniques and the Folding@Home cluster. Our results provide a basis for quantifying global structural diversity of macromolecules in crystals directly from x-ray experiments, and we show this on a large set of structures taken from the Protein Data Bank. In particular, we show that the ensemble-average pairwise backbone RMSD for a microscopic ensemble underlying a typical protein x-ray structure is approximately 1.1 A, under the assumption that the principal contribution to experimental B-factors is conformational variability. 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.