Score distributions of gapped multiple sequence alignments down to the low-probability tail

NASA Astrophysics Data System (ADS)

Fieth, Pascal; Hartmann, Alexander K.

2016-08-01

Assessing the significance of alignment scores of optimally aligned DNA or amino acid sequences can be achieved via the knowledge of the score distribution of random sequences. But this requires obtaining the distribution in the biologically relevant high-scoring region, where the probabilities are exponentially small. For gapless local alignments of infinitely long sequences this distribution is known analytically to follow a Gumbel distribution. Distributions for gapped local alignments and global alignments of finite lengths can only be obtained numerically. To obtain result for the small-probability region, specific statistical mechanics-based rare-event algorithms can be applied. In previous studies, this was achieved for pairwise alignments. They showed that, contrary to results from previous simple sampling studies, strong deviations from the Gumbel distribution occur in case of finite sequence lengths. Here we extend the studies to multiple sequence alignments with gaps, which are much more relevant for practical applications in molecular biology. We study the distributions of scores over a large range of the support, reaching probabilities as small as 10-160, for global and local (sum-of-pair scores) multiple alignments. We find that even after suitable rescaling, eliminating the sequence-length dependence, the distributions for multiple alignment differ from the pairwise alignment case. Furthermore, we also show that the previously discussed Gaussian correction to the Gumbel distribution needs to be refined, also for the case of pairwise alignments.

Adjustment for reporting bias in network meta-analysis of antidepressant trials

PubMed Central

2012-01-01

Background Network meta-analysis (NMA), a generalization of conventional MA, allows for assessing the relative effectiveness of multiple interventions. Reporting bias is a major threat to the validity of MA and NMA. Numerous methods are available to assess the robustness of MA results to reporting bias. We aimed to extend such methods to NMA. Methods We introduced 2 adjustment models for Bayesian NMA. First, we extended a meta-regression model that allows the effect size to depend on its standard error. Second, we used a selection model that estimates the propensity of trial results being published and in which trials with lower propensity are weighted up in the NMA model. Both models rely on the assumption that biases are exchangeable across the network. We applied the models to 2 networks of placebo-controlled trials of 12 antidepressants, with 74 trials in the US Food and Drug Administration (FDA) database but only 51 with published results. NMA and adjustment models were used to estimate the effects of the 12 drugs relative to placebo, the 66 effect sizes for all possible pair-wise comparisons between drugs, probabilities of being the best drug and ranking of drugs. We compared the results from the 2 adjustment models applied to published data and NMAs of published data and NMAs of FDA data, considered as representing the totality of the data. Results Both adjustment models showed reduced estimated effects for the 12 drugs relative to the placebo as compared with NMA of published data. Pair-wise effect sizes between drugs, probabilities of being the best drug and ranking of drugs were modified. Estimated drug effects relative to the placebo from both adjustment models were corrected (i.e., similar to those from NMA of FDA data) for some drugs but not others, which resulted in differences in pair-wise effect sizes between drugs and ranking. Conclusions In this case study, adjustment models showed that NMA of published data was not robust to reporting bias and provided estimates closer to that of NMA of FDA data, although not optimal. The validity of such methods depends on the number of trials in the network and the assumption that conventional MAs in the network share a common mean bias mechanism. PMID:23016799

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

Fixation of strategies driven by switching probabilities in evolutionary games

NASA Astrophysics Data System (ADS)

Xu, Zimin; Zhang, Jianlei; Zhang, Chunyan; Chen, Zengqiang

2016-12-01

We study the evolutionary dynamics of strategies in finite populations which are homogeneous and well mixed by means of the pairwise comparison process, the core of which is the proposed switching probability. Previous studies about this subject are usually based on the known payoff comparison of the related players, which is an ideal assumption. In real social systems, acquiring the accurate payoffs of partners at each round of interaction may be not easy. So we bypass the need of explicit knowledge of payoffs, and encode the payoffs into the willingness of any individual shift from her current strategy to the competing one, and the switching probabilities are wholly independent of payoffs. Along this way, the strategy updating can be performed when game models are fixed and payoffs are unclear, expected to extend ideal assumptions to be more realistic one. We explore the impact of the switching probability on the fixation probability and derive a simple formula which determines the fixation probability. Moreover we find that cooperation dominates defection if the probability of cooperation replacing defection is always larger than the probability of defection replacing cooperation in finite populations. Last, we investigate the influences of model parameters on the fixation of strategies in the framework of three concrete game models: prisoner's dilemma, snowdrift game and stag-hunt game, which effectively portray the characteristics of cooperative dilemmas in real social systems.

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.

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.

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.

Changes in flexibility upon binding: Application of the self-consistent pair contact probability method to protein-protein interactions

NASA Astrophysics Data System (ADS)

Canino, Lawrence S.; Shen, Tongye; McCammon, J. Andrew

2002-12-01

We extend the self-consistent pair contact probability method to the evaluation of the partition function for a protein complex at thermodynamic equilibrium. Specifically, we adapt the method for multichain models and introduce a parametrization for amino acid-specific pairwise interactions. This method is similar to the Gaussian network model but allows for the adjusting of the strengths of native state contacts. The method is first validated on a high resolution x-ray crystal structure of bovine Pancreatic Phospholipase A2 by comparing calculated B-factors with reported values. We then examine binding-induced changes in flexibility in protein-protein complexes, comparing computed results with those obtained from x-ray crystal structures and molecular dynamics simulations. In particular, we focus on the mouse acetylcholinesterase:fasciculin II and the human α-thrombin:thrombomodulin complexes.

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.

Statistical mechanics model for the emergence of consensus

NASA Astrophysics Data System (ADS)

Raffaelli, Giacomo; Marsili, Matteo

2005-07-01

The statistical properties of pairwise majority voting over S alternatives are analyzed in an infinite random population. We first compute the probability that the majority is transitive (i.e., that if it prefers A to B to C , then it prefers A to C ) and then study the case of an interacting population. This is described by a constrained multicomponent random field Ising model whose ferromagnetic phase describes the emergence of a strong transitive majority. We derive the phase diagram, which is characterized by a tricritical point and show that, contrary to intuition, it may be more likely for an interacting population to reach consensus on a number S of alternatives when S increases. This effect is due to the constraint imposed by transitivity on voting behavior. Indeed if agents are allowed to express nontransitive votes, the agents’ interaction may decrease considerably the probability of a transitive majority.

Rényi information flow in the Ising model with single-spin dynamics.

PubMed

Deng, Zehui; Wu, Jinshan; Guo, Wenan

2014-12-01

The n-index Rényi mutual information and transfer entropies for the two-dimensional kinetic Ising model with arbitrary single-spin dynamics in the thermodynamic limit are derived as functions of ensemble averages of observables and spin-flip probabilities. Cluster Monte Carlo algorithms with different dynamics from the single-spin dynamics are thus applicable to estimate the transfer entropies. By means of Monte Carlo simulations with the Wolff algorithm, we calculate the information flows in the Ising model with the Metropolis dynamics and the Glauber dynamics, respectively. We find that not only the global Rényi transfer entropy, but also the pairwise Rényi transfer entropy, peaks in the disorder phase.

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

Game-Theoretic strategies for systems of components using product-form utilities

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

Rao, Nageswara S; Ma, Cheng-Yu; Hausken, K.

Many critical infrastructures are composed of multiple systems of components which are correlated so that disruptions to one may propagate to others. We consider such infrastructures with correlations characterized in two ways: (i) an aggregate failure correlation function specifies the conditional failure probability of the infrastructure given the failure of an individual system, and (ii) a pairwise correlation function between two systems specifies the failure probability of one system given the failure of the other. We formulate a game for ensuring the resilience of the infrastructure, wherein the utility functions of the provider and attacker are products of an infrastructuremore » survival probability term and a cost term, both expressed in terms of the numbers of system components attacked and reinforced. The survival probabilities of individual systems satisfy first-order differential conditions that lead to simple Nash Equilibrium conditions. We then derive sensitivity functions that highlight the dependence of infrastructure resilience on the cost terms, correlation functions, and individual system survival probabilities. We apply these results to simplified models of distributed cloud computing and energy grid infrastructures.« less

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.

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.

Analysis of the “naming game” with learning errors in communications

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong

2015-07-01

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

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

Analysis of the "naming game" with learning errors in communications.

PubMed

Lou, Yang; Chen, Guanrong

2015-07-16

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Fine-tuning molecular acoustic models: sensitivity of the predicted attenuation to the Lennard-Jones parameters

NASA Astrophysics Data System (ADS)

Petculescu, Andi G.; Lueptow, Richard M.

2005-01-01

In a previous paper [Y. Dain and R. M. Lueptow, J. Acoust. Soc. Am. 109, 1955 (2001)], a model of acoustic attenuation due to vibration-translation and vibration-vibration relaxation in multiple polyatomic gas mixtures was developed. In this paper, the model is improved by treating binary molecular collisions via fully pairwise vibrational transition probabilities. The sensitivity of the model to small variations in the Lennard-Jones parameters-collision diameter (σ) and potential depth (ɛ)-is investigated for nitrogen-water-methane mixtures. For a N2(98.97%)-H2O(338 ppm)-CH4(1%) test mixture, the transition probabilities and acoustic absorption curves are much more sensitive to σ than they are to ɛ. Additionally, when the 1% methane is replaced by nitrogen, the resulting mixture [N2(99.97%)-H2O(338 ppm)] becomes considerably more sensitive to changes of σwater. The current model minimizes the underprediction of the acoustic absorption peak magnitudes reported by S. G. Ejakov et al. [J. Acoust. Soc. Am. 113, 1871 (2003)]. .

Population structure and covariate analysis based on pairwise microsatellite allele matching frequencies.

PubMed

Givens, Geof H; Ozaksoy, Isin

2007-01-01

We describe a general model for pairwise microsatellite allele matching probabilities. The model can be used for analysis of population substructure, and is particularly focused on relating genetic correlation to measurable covariates. The approach is intended for cases when the existence of subpopulations is uncertain and a priori assignment of samples to hypothesized subpopulations is difficult. Such a situation arises, for example, with western Arctic bowhead whales, where genetic samples are available only from a possibly mixed migratory assemblage. We estimate genetic structure associated with spatial, temporal, or other variables that may confound the detection of population structure. In the bowhead case, the model permits detection of genetic patterns associated with a temporally pulsed multi-population assemblage in the annual migration. Hypothesis tests for population substructure and for covariate effects can be carried out using permutation methods. Simulated and real examples illustrate the effectiveness and reliability of the approach and enable comparisons with other familiar approaches. Analysis of the bowhead data finds no evidence for two temporally pulsed subpopulations using the best available data, although a significant pattern found by other researchers using preliminary data is also confirmed here. Code in the R language is available from www.stat.colostate.edu/~geof/gammmp.html.

Role of conviction in nonequilibrium models of opinion formation

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno; Anteneodo, Celia

2012-12-01

We analyze the critical behavior of a class of discrete opinion models in the presence of disorder. Within this class, each agent opinion takes a discrete value (±1 or 0) and its time evolution is ruled by two terms, one representing agent-agent interactions and the other the degree of conviction or persuasion (a self-interaction). The mean-field limit, where each agent can interact evenly with any other, is considered. Disorder is introduced in the strength of both interactions, with either quenched or annealed random variables. With probability p (1-p), a pairwise interaction reflects a negative (positive) coupling, while the degree of conviction also follows a binary probability distribution (two different discrete probability distributions are considered). Numerical simulations show that a nonequilibrium continuous phase transition, from a disordered state to a state with a prevailing opinion, occurs at a critical point pc that depends on the distribution of the convictions, with the transition being spoiled in some cases. We also show how the critical line, for each model, is affected by the update scheme (either parallel or sequential) as well as by the kind of disorder (either quenched or annealed).

Pairwise Force Smoothed Particle Hydrodynamics model for multiphase flow: Surface tension and contact line dynamics

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

Tartakovsky, Alexandre M.; Panchenko, Alexander

2016-01-01

We present a novel formulation of the Pairwise Force Smoothed Particle Hydrodynamics Model (PF-SPH) and use it to simulate two- and three-phase flows in bounded domains. In the PF-SPH model, the Navier-Stokes equations are discretized with the Smoothed Particle Hydrodynamics (SPH) method and the Young-Laplace boundary condition at the fluid-fluid interface and the Young boundary condition at the fluid-fluid-solid interface are replaced with pairwise forces added into the Navier-Stokes equations. We derive a relationship between the parameters in the pairwise forces and the surface tension and static contact angle. Next, we demonstrate the accuracy of the model under static andmore » dynamic conditions. Finally, to demonstrate the capabilities and robustness of the model we use it to simulate flow of three fluids in a porous material.« less

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

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.

Estimating the concordance probability in a survival analysis with a discrete number of risk groups.

PubMed

Heller, Glenn; Mo, Qianxing

2016-04-01

A clinical risk classification system is an important component of a treatment decision algorithm. A measure used to assess the strength of a risk classification system is discrimination, and when the outcome is survival time, the most commonly applied global measure of discrimination is the concordance probability. The concordance probability represents the pairwise probability of lower patient risk given longer survival time. The c-index and the concordance probability estimate have been used to estimate the concordance probability when patient-specific risk scores are continuous. In the current paper, the concordance probability estimate and an inverse probability censoring weighted c-index are modified to account for discrete risk scores. Simulations are generated to assess the finite sample properties of the concordance probability estimate and the weighted c-index. An application of these measures of discriminatory power to a metastatic prostate cancer risk classification system is examined.

Random walk in generalized quantum theory

NASA Astrophysics Data System (ADS)

Martin, Xavier; O'Connor, Denjoe; Sorkin, Rafael D.

2005-01-01

One can view quantum mechanics as a generalization of classical probability theory that provides for pairwise interference among alternatives. Adopting this perspective, we “quantize” the classical random walk by finding, subject to a certain condition of “strong positivity”, the most general Markovian, translationally invariant “decoherence functional” with nearest neighbor transitions.

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

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

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

On stable Pareto laws in a hierarchical model of economy

NASA Astrophysics Data System (ADS)

Chebotarev, A. M.

2007-01-01

This study considers a model of the income distribution of agents whose pairwise interaction is asymmetric and price-invariant. Asymmetric transactions are typical for chain-trading groups who arrange their business such that commodities move from senior to junior partners and money moves in the opposite direction. The price-invariance of transactions means that the probability of a pairwise interaction is a function of the ratio of incomes, which is independent of the price scale or absolute income level. These two features characterize the hierarchical model. The income distribution in this class of models is a well-defined double-Pareto function, which possesses Pareto tails for the upper and lower incomes. For gross and net upper incomes, the model predicts definite values of the Pareto exponents, agross and anet, which are stable with respect to quantitative variation of the pair-interaction. The Pareto exponents are also stable with respect to the choice of a demand function within two classes of status-dependent behavior of agents: linear demand ( agross=1, anet=2) and unlimited slowly varying demand ( agross=anet=1). For the sigmoidal demand that describes limited returns, agross=anet=1+α, with some α>0 satisfying a transcendental equation. The low-income distribution may be singular or vanishing in the neighborhood of the minimal income; in any case, it is L1-integrable and its Pareto exponent is given explicitly. The theory used in the present study is based on a simple balance equation and new results from multiplicative Markov chains and exponential moments of random geometric progressions.

Metabolic network prediction through pairwise rational kernels.

PubMed

Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

2014-09-26

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy values have been improved, while maintaining lower construction and execution times. The power of using kernels is that almost any sort of data can be represented using kernels. Therefore, completely disparate types of data can be combined to add power to kernel-based machine learning methods. When we compared our proposal using PRKs with other similar kernel, the execution times were decreased, with no compromise of accuracy. We also proved that by combining PRKs with other kernels that include evolutionary information, the accuracy can also also be improved. As our proposal can use any type of sequence data, genes do not need to be properly annotated, avoiding accumulation errors because of incorrect previous annotations.

An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species

PubMed Central

Galpert, Deborah; del Río, Sara; Herrera, Francisco; Ancede-Gallardo, Evys; Antunes, Agostinho; Agüero-Chapin, Guillermin

2015-01-01

Orthology detection requires more effective scaling algorithms. In this paper, a set of gene pair features based on similarity measures (alignment scores, sequence length, gene membership to conserved regions, and physicochemical profiles) are combined in a supervised pairwise ortholog detection approach to improve effectiveness considering low ortholog ratios in relation to the possible pairwise comparison between two genomes. In this scenario, big data supervised classifiers managing imbalance between ortholog and nonortholog pair classes allow for an effective scaling solution built from two genomes and extended to other genome pairs. The supervised approach was compared with RBH, RSD, and OMA algorithms by using the following yeast genome pairs: Saccharomyces cerevisiae-Kluyveromyces lactis, Saccharomyces cerevisiae-Candida glabrata, and Saccharomyces cerevisiae-Schizosaccharomyces pombe as benchmark datasets. Because of the large amount of imbalanced data, the building and testing of the supervised model were only possible by using big data supervised classifiers managing imbalance. Evaluation metrics taking low ortholog ratios into account were applied. From the effectiveness perspective, MapReduce Random Oversampling combined with Spark SVM outperformed RBH, RSD, and OMA, probably because of the consideration of gene pair features beyond alignment similarities combined with the advances in big data supervised classification. PMID:26605337

An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species.

PubMed

Galpert, Deborah; Del Río, Sara; Herrera, Francisco; Ancede-Gallardo, Evys; Antunes, Agostinho; Agüero-Chapin, Guillermin

2015-01-01

Orthology detection requires more effective scaling algorithms. In this paper, a set of gene pair features based on similarity measures (alignment scores, sequence length, gene membership to conserved regions, and physicochemical profiles) are combined in a supervised pairwise ortholog detection approach to improve effectiveness considering low ortholog ratios in relation to the possible pairwise comparison between two genomes. In this scenario, big data supervised classifiers managing imbalance between ortholog and nonortholog pair classes allow for an effective scaling solution built from two genomes and extended to other genome pairs. The supervised approach was compared with RBH, RSD, and OMA algorithms by using the following yeast genome pairs: Saccharomyces cerevisiae-Kluyveromyces lactis, Saccharomyces cerevisiae-Candida glabrata, and Saccharomyces cerevisiae-Schizosaccharomyces pombe as benchmark datasets. Because of the large amount of imbalanced data, the building and testing of the supervised model were only possible by using big data supervised classifiers managing imbalance. Evaluation metrics taking low ortholog ratios into account were applied. From the effectiveness perspective, MapReduce Random Oversampling combined with Spark SVM outperformed RBH, RSD, and OMA, probably because of the consideration of gene pair features beyond alignment similarities combined with the advances in big data supervised classification.

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.

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.

A Single Camera Motion Capture System for Human-Computer Interaction

NASA Astrophysics Data System (ADS)

Okada, Ryuzo; Stenger, Björn

This paper presents a method for markerless human motion capture using a single camera. It uses tree-based filtering to efficiently propagate a probability distribution over poses of a 3D body model. The pose vectors and associated shapes are arranged in a tree, which is constructed by hierarchical pairwise clustering, in order to efficiently evaluate the likelihood in each frame. Anew likelihood function based on silhouette matching is proposed that improves the pose estimation of thinner body parts, i. e. the limbs. The dynamic model takes self-occlusion into account by increasing the variance of occluded body-parts, thus allowing for recovery when the body part reappears. We present two applications of our method that work in real-time on a Cell Broadband Engine™: a computer game and a virtual clothing application.

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.

LEGEND, a LEO-to-GEO Environment Debris Model

NASA Technical Reports Server (NTRS)

Liou, Jer Chyi; Hall, Doyle T.

2013-01-01

LEGEND (LEO-to-GEO Environment Debris model) is a three-dimensional orbital debris evolutionary model that is capable of simulating the historical and future debris populations in the near-Earth environment. The historical component in LEGEND adopts a deterministic approach to mimic the known historical populations. Launched rocket bodies, spacecraft, and mission-related debris (rings, bolts, etc.) are added to the simulated environment. Known historical breakup events are reproduced, and fragments down to 1 mm in size are created. The LEGEND future projection component adopts a Monte Carlo approach and uses an innovative pair-wise collision probability evaluation algorithm to simulate the future breakups and the growth of the debris populations. This algorithm is based on a new "random sampling in time" approach that preserves characteristics of the traditional approach and captures the rapidly changing nature of the orbital debris environment. LEGEND is a Fortran 90-based numerical simulation program. It operates in a UNIX/Linux environment.

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

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.

Automated segmentation of neuroanatomical structures in multispectral MR microscopy of the mouse brain.

PubMed

Ali, Anjum A; Dale, Anders M; Badea, Alexandra; Johnson, G Allan

2005-08-15

We present the automated segmentation of magnetic resonance microscopy (MRM) images of the C57BL/6J mouse brain into 21 neuroanatomical structures, including the ventricular system, corpus callosum, hippocampus, caudate putamen, inferior colliculus, internal capsule, globus pallidus, and substantia nigra. The segmentation algorithm operates on multispectral, three-dimensional (3D) MR data acquired at 90-microm isotropic resolution. Probabilistic information used in the segmentation is extracted from training datasets of T2-weighted, proton density-weighted, and diffusion-weighted acquisitions. Spatial information is employed in the form of prior probabilities of occurrence of a structure at a location (location priors) and the pairwise probabilities between structures (contextual priors). Validation using standard morphometry indices shows good consistency between automatically segmented and manually traced data. Results achieved in the mouse brain are comparable with those achieved in human brain studies using similar techniques. The segmentation algorithm shows excellent potential for routine morphological phenotyping of mouse models.

Saliency Detection via Absorbing Markov Chain With Learnt Transition Probability.

PubMed

Lihe Zhang; Jianwu Ai; Bowen Jiang; Huchuan Lu; Xiukui Li

2018-02-01

In this paper, we propose a bottom-up saliency model based on absorbing Markov chain (AMC). First, a sparsely connected graph is constructed to capture the local context information of each node. All image boundary nodes and other nodes are, respectively, treated as the absorbing nodes and transient nodes in the absorbing Markov chain. Then, the expected number of times from each transient node to all other transient nodes can be used to represent the saliency value of this node. The absorbed time depends on the weights on the path and their spatial coordinates, which are completely encoded in the transition probability matrix. Considering the importance of this matrix, we adopt different hierarchies of deep features extracted from fully convolutional networks and learn a transition probability matrix, which is called learnt transition probability matrix. Although the performance is significantly promoted, salient objects are not uniformly highlighted very well. To solve this problem, an angular embedding technique is investigated to refine the saliency results. Based on pairwise local orderings, which are produced by the saliency maps of AMC and boundary maps, we rearrange the global orderings (saliency value) of all nodes. Extensive experiments demonstrate that the proposed algorithm outperforms the state-of-the-art methods on six publicly available benchmark data sets.

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…

Highly viscous antibody solutions are a consequence of network formation caused by domain-domain electrostatic complementarities: insights from coarse-grained simulations.

PubMed

Buck, Patrick M; Chaudhri, Anuj; Kumar, Sandeep; Singh, Satish K

2015-01-05

Therapeutic monoclonal antibody (mAb) candidates that form highly viscous solutions at concentrations above 100 mg/mL can lead to challenges in bioprocessing, formulation development, and subcutaneous drug delivery. Earlier studies of mAbs with concentration-dependent high viscosity have indicated that mAbs with negatively charged Fv regions have a dipole-like quality that increases the likelihood of reversible self-association. This suggests that weak electrostatic intermolecular interactions can form transient antibody networks that participate in resistance to solution deformation under shear stress. Here this hypothesis is explored by parametrizing a coarse-grained (CG) model of an antibody using the domain charges from four different mAbs that have had their concentration-dependent viscosity behaviors previously determined. Multicopy molecular dynamics simulations were performed for these four CG mAbs at several concentrations to understand the effect of surface charge on mass diffusivity, pairwise interactions, and electrostatic network formation. Diffusion coefficients computed from simulations were in qualitative agreement with experimentally determined viscosities for all four mAbs. Contact analysis revealed an overall greater number of pairwise interactions for the two mAbs in this study with high concentration viscosity issues. Further, using equilibrated solution trajectories, the two mAbs with high concentration viscosity issues quantitatively formed more features of an electrostatic network than the other mAbs. The change in the number of these network features as a function of concentration is related to the number of pairwise interactions formed by electrostatic complementarities between antibody domains. Thus, transient antibody network formation caused by domain-domain electrostatic complementarities is the most probable origin of high concentration viscosity for mAbs in this study.

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

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.

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.

Land use and land cover classification for rural residential areas in China using soft-probability cascading of multifeatures

NASA Astrophysics Data System (ADS)

Zhang, Bin; Liu, Yueyan; Zhang, Zuyu; Shen, Yonglin

2017-10-01

A multifeature soft-probability cascading scheme to solve the problem of land use and land cover (LULC) classification using high-spatial-resolution images to map rural residential areas in China is proposed. The proposed method is used to build midlevel LULC features. Local features are frequently considered as low-level feature descriptors in a midlevel feature learning method. However, spectral and textural features, which are very effective low-level features, are neglected. The acquisition of the dictionary of sparse coding is unsupervised, and this phenomenon reduces the discriminative power of the midlevel feature. Thus, we propose to learn supervised features based on sparse coding, a support vector machine (SVM) classifier, and a conditional random field (CRF) model to utilize the different effective low-level features and improve the discriminability of midlevel feature descriptors. First, three kinds of typical low-level features, namely, dense scale-invariant feature transform, gray-level co-occurrence matrix, and spectral features, are extracted separately. Second, combined with sparse coding and the SVM classifier, the probabilities of the different LULC classes are inferred to build supervised feature descriptors. Finally, the CRF model, which consists of two parts: unary potential and pairwise potential, is employed to construct an LULC classification map. Experimental results show that the proposed classification scheme can achieve impressive performance when the total accuracy reached about 87%.

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

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.

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.

Sudden transitions in coupled opinion and epidemic dynamics with vaccination

NASA Astrophysics Data System (ADS)

Pires, Marcelo A.; Oestereich, André L.; Crokidakis, Nuno

2018-05-01

This work consists of an epidemic model with vaccination coupled with an opinion dynamics. Our objective was to study how disease risk perception can influence opinions about vaccination and therefore the spreading of the disease. Differently from previous works we have considered continuous opinions. The epidemic spreading is governed by an SIS-like model with an extra vaccinated state. In our model individuals vaccinate with a probability proportional to their opinions. The opinions change due to peer influence in pairwise interactions. The epidemic feedback to the opinion dynamics acts as an external field increasing the vaccination probability. We performed Monte Carlo simulations in fully-connected populations. Interestingly we observed the emergence of a first-order phase transition, besides the usual active-absorbing phase transition presented in the SIS model. Our simulations also show that with a certain combination of parameters, an increment in the initial fraction of the population that is pro-vaccine has a twofold effect: it can lead to smaller epidemic outbreaks in the short term, but it also contributes to the survival of the chain of infections in the long term. Our results also suggest that it is possible that more effective vaccines can decrease the long-term vaccine coverage. This is a counterintuitive outcome, but it is in line with empirical observations that vaccines can become a victim of their own success.

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...

Design of an activity landscape view taking compound-based feature probabilities into account.

PubMed

Zhang, Bijun; Vogt, Martin; Bajorath, Jürgen

2014-09-01

Activity landscapes (ALs) of compound data sets are rationalized as graphical representations that integrate similarity and potency relationships between active compounds. ALs enable the visualization of structure-activity relationship (SAR) information and are thus computational tools of interest for medicinal chemistry. For AL generation, similarity and potency relationships are typically evaluated in a pairwise manner and major AL features are assessed at the level of compound pairs. In this study, we add a conditional probability formalism to AL design that makes it possible to quantify the probability of individual compounds to contribute to characteristic AL features. Making this information graphically accessible in a molecular network-based AL representation is shown to further increase AL information content and helps to quickly focus on SAR-informative compound subsets. This feature probability-based AL variant extends the current spectrum of AL representations for medicinal chemistry applications.

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.

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.

Independence and totalness of subspaces in phase space methods

NASA Astrophysics Data System (ADS)

Vourdas, A.

2018-04-01

The concepts of independence and totalness of subspaces are introduced in the context of quasi-probability distributions in phase space, for quantum systems with finite-dimensional Hilbert space. It is shown that due to the non-distributivity of the lattice of subspaces, there are various levels of independence, from pairwise independence up to (full) independence. Pairwise totalness, totalness and other intermediate concepts are also introduced, which roughly express that the subspaces overlap strongly among themselves, and they cover the full Hilbert space. A duality between independence and totalness, that involves orthocomplementation (logical NOT operation), is discussed. Another approach to independence is also studied, using Rota's formalism on independent partitions of the Hilbert space. This is used to define informational independence, which is proved to be equivalent to independence. As an application, the pentagram (used in discussions on contextuality) is analysed using these concepts.

Evaluation of advanced multiplex short tandem repeat systems in pairwise kinship analysis.

PubMed

Tamura, Tomonori; Osawa, Motoki; Ochiai, Eriko; Suzuki, Takanori; Nakamura, Takashi

2015-09-01

The AmpFLSTR Identifiler Kit, comprising 15 autosomal short tandem repeat (STR) loci, is commonly employed in forensic practice for calculating match probabilities and parentage testing. The conventional system exhibits insufficient estimation for kinship analysis such as sibship testing because of shortness of examined loci. This study evaluated the power of the PowerPlex Fusion System, GlobalFiler Kit, and PowerPlex 21 System, which comprise more than 20 autosomal STR loci, to estimate pairwise blood relatedness (i.e., parent-child, full siblings, second-degree relatives, and first cousins). The genotypes of all 24 STR loci in 10,000 putative pedigrees were constructed by simulation. The likelihood ratio for each locus was calculated from joint probabilities for relatives and non-relatives. The combined likelihood ratio was calculated according to the product rule. The addition of STR loci improved separation between relatives and non-relatives. However, these systems were less effectively extended to the inference for first cousins. In conclusion, these advanced systems will be useful in forensic personal identification, especially in the evaluation of full siblings and second-degree relatives. Moreover, the additional loci may give rise to two major issues of more frequent mutational events and several pairs of linked loci on the same chromosome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Novel presentational approaches were developed for reporting network meta-analysis.

PubMed

Tan, Sze Huey; Cooper, Nicola J; Bujkiewicz, Sylwia; Welton, Nicky J; Caldwell, Deborah M; Sutton, Alexander J

2014-06-01

To present graphical tools for reporting network meta-analysis (NMA) results aiming to increase the accessibility, transparency, interpretability, and acceptability of NMA analyses. The key components of NMA results were identified based on recommendations by agencies such as the National Institute for Health and Care Excellence (United Kingdom). Three novel graphs were designed to amalgamate the identified components using familiar graphical tools such as the bar, line, or pie charts and adhering to good graphical design principles. Three key components for presentation of NMA results were identified, namely relative effects and their uncertainty, probability of an intervention being best, and between-study heterogeneity. Two of the three graphs developed present results (for each pairwise comparison of interventions in the network) obtained from both NMA and standard pairwise meta-analysis for easy comparison. They also include options to display the probability best, ranking statistics, heterogeneity, and prediction intervals. The third graph presents rankings of interventions in terms of their effectiveness to enable clinicians to easily identify "top-ranking" interventions. The graphical tools presented can display results tailored to the research question of interest, and targeted at a whole spectrum of users from the technical analyst to the nontechnical clinician. Copyright © 2014 Elsevier Inc. All rights reserved.

Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

Probabilistic models for neural populations that naturally capture global coupling and criticality

PubMed Central

2017-01-01

Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons; 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying system’s state space; hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality. PMID:28926564

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.

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.

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

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.

Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method.

PubMed

Andersen, Mikkel Meyer; Eriksen, Poul Svante; Morling, Niels

2014-07-01

The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous studies. We also compared pairwise distances (between geographically separated samples) with those obtained using the AMOVA method and found good agreement. Further analyses that are impossible with AMOVA were made using the discrete Laplace method: analysis of the homogeneity in two different ways and calculating marginal STR distributions. We found that the Y-STR haplotypes from e.g. Finland were relatively homogeneous as opposed to the relatively heterogeneous Y-STR haplotypes from e.g. Lublin, Eastern Poland and Berlin, Germany. We demonstrated that the observed distributions of alleles at each locus were similar to the expected ones. We also compared pairwise distances between geographically separated samples from Africa with those obtained using the AMOVA method and found good agreement. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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.

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

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.

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

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

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.

Correlative feature analysis on FFDM

PubMed Central

Yuan, Yading; Giger, Maryellen L.; Li, Hui; Sennett, Charlene

2008-01-01

Identifying the corresponding images of a lesion in different views is an essential step in improving the diagnostic ability of both radiologists and computer-aided diagnosis (CAD) systems. Because of the nonrigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this pilot study, we present a computerized framework that differentiates between corresponding images of the same lesion in different views and noncorresponding images, i.e., images of different lesions. A dual-stage segmentation method, which employs an initial radial gradient index (RGI) based segmentation and an active contour model, is applied to extract mass lesions from the surrounding parenchyma. Then various lesion features are automatically extracted from each of the two views of each lesion to quantify the characteristics of density, size, texture and the neighborhood of the lesion, as well as its distance to the nipple. A two-step scheme is employed to estimate the probability that the two lesion images from different mammographic views are of the same physical lesion. In the first step, a correspondence metric for each pairwise feature is estimated by a Bayesian artificial neural network (BANN). Then, these pairwise correspondence metrics are combined using another BANN to yield an overall probability of correspondence. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing corresponding pairs from noncorresponding pairs. Using a FFDM database with 123 corresponding image pairs and 82 noncorresponding pairs, the distance feature yielded an area under the ROC curve (AUC) of 0.81±0.02 with leave-one-out (by physical lesion) evaluation, and the feature metric subset, which included distance, gradient texture, and ROI-based correlation, yielded an AUC of 0.87±0.02. The improvement by using multiple feature metrics was statistically significant compared to single feature performance. PMID:19175108

Statistical Optimality in Multipartite Ranking and Ordinal Regression.

PubMed

Uematsu, Kazuki; Lee, Yoonkyung

2015-05-01

Statistical optimality in multipartite ranking is investigated as an extension of bipartite ranking. We consider the optimality of ranking algorithms through minimization of the theoretical risk which combines pairwise ranking errors of ordinal categories with differential ranking costs. The extension shows that for a certain class of convex loss functions including exponential loss, the optimal ranking function can be represented as a ratio of weighted conditional probability of upper categories to lower categories, where the weights are given by the misranking costs. This result also bridges traditional ranking methods such as proportional odds model in statistics with various ranking algorithms in machine learning. Further, the analysis of multipartite ranking with different costs provides a new perspective on non-smooth list-wise ranking measures such as the discounted cumulative gain and preference learning. We illustrate our findings with simulation study and real data analysis.

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.

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.

Trellis Coding of Non-coherent Multiple Symbol Full Response M-ary CPFSK with Modulation Index 1/M

NASA Technical Reports Server (NTRS)

Lee, H.; Divsalar, D.; Weber, C.

1994-01-01

This paper introduces a trellis coded modulation (TCM) scheme for non-coherent multiple full response M-ary CPFSK with modulation index 1/M. A proper branch metric for the trellis decoder is obtained by employing a simple approximation of the modified Bessel function for large signal to noise ratio (SNR). Pairwise error probability of coded sequences is evaluated by applying a linear approximation to the Rician random variable.

Acupuncture and related therapies used as add-on or alternative to prokinetics for functional dyspepsia: overview of systematic reviews and network meta-analysis.

PubMed

Ho, Robin S T; Chung, Vincent C H; Wong, Charlene H L; Wu, Justin C Y; Wong, Samuel Y S; Wu, Irene X Y

2017-09-04

Prokinetics for functional dyspepsia (FD) have relatively higher number needed to treat values. Acupuncture and related therapies could be used as add-on or alternative. An overview of systematic reviews (SRs) and network meta-analyses (NMA) were performed to evaluate the comparative effectiveness of different acupuncture and related therapies. We conducted a comprehensive literature search for SRs of randomized controlled trials (RCTs) in eight international and Chinese databases. Data from eligible RCTs were extracted for random effect pairwise meta-analyses. NMA was used to explore the most effective treatment among acupuncture and related therapies used alone or as add-on to prokinetics, compared to prokinetics alone. From five SRs, 22 RCTs assessing various acupuncture and related therapies were included. No serious adverse events were reported. Two pairwise meta-analyses showed manual acupuncture has marginally stronger effect in alleviating global FD symptoms, compared to domperidone or itopride. Results from NMA showed combination of manual acupuncture and clebopride has the highest probability in alleviating patient reported global FD symptom. Combination of manual acupuncture and clebopride has the highest probability of being the most effective treatment for FD symptoms. Patients who are contraindicated for prokinetics may use manual acupuncture or moxibustion as alternative. Future confirmatory comparative effectiveness trials should compare clebopride add-on manual acupuncture with domperidone add-on manual acupuncture and moxibustion.

Stimulus-dependent Maximum Entropy Models of Neural Population Codes

PubMed Central

Segev, Ronen; Schneidman, Elad

2013-01-01

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME) model—a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population. PMID:23516339

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

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.

Non-random Patterns in the Distribution of NOR-bearing Chromosome Territories in Human Fibroblasts: A Network Model of Interactions

PubMed Central

Pliss, Artem; Fritz, Andrew J.; Stojkovic, Branislav; Ding, Hu; Mukherjee, Lopamudra; Bhattacharya, Sambit; Xu, Jinhui; Berezney, Ronald

2017-01-01

We present a 3-D mapping in WI38 human diploid fibroblast cells of chromosome territories (CT) 13,14,15,21, and 22, which contain the nucleolar organizing regions (NOR) and participate in the formation of nucleoli. The nuclear radial positioning of NOR-CT correlated with the size of chromosomes with smaller CT more interior. A high frequency of pairwise associations between NOR-CT ranging from 52% (CT13-21) to 82% (CT15-21) was detected as well as a triplet arrangement of CT15-21-22 (72%). The associations of homologous CT were significantly lower (24–36%). The arrangements of each pairwise CT varied from CT13-14 and CT13-22, which had a majority of cells with single associations, to CT13-15 and CT13-21 where a majority of cells had multiple interactions. In cells with multiple nucleoli, one of the nucleoli (termed “dominant”) always associated with a higher number of CT. Moreover, certain CT pairs more frequently contributed to the same nucleolus than to others. This nonrandom pattern suggests that a large number of the NOR-chromsomes are poised in close proximity during the postmitotic nucleolar recovery and through their NORs may contribute to the formation of the same nucleolus. A global data mining program termed the chromatic median determined the most probable interchromosomal arrangement of the entire NOR-CT population. This interactive network model was significantly above randomized simulation and was composed of 13 connections among the NOR-CT. We conclude that the NOR-CT form a global interactive network in the cell nucleus that may be a fundamental feature for the regulation of nucleolar and other genomic functions. PMID:25077974

Enhancing pairwise state-transition weights: A new weighting scheme in simulated tempering that can minimize transition time between a pair of conformational states

NASA Astrophysics Data System (ADS)

Qiao, Qin; Zhang, Hou-Dao; Huang, Xuhui

2016-04-01

Simulated tempering (ST) is a widely used enhancing sampling method for Molecular Dynamics simulations. As one expanded ensemble method, ST is a combination of canonical ensembles at different temperatures and the acceptance probability of cross-temperature transitions is determined by both the temperature difference and the weights of each temperature. One popular way to obtain the weights is to adopt the free energy of each canonical ensemble, which achieves uniform sampling among temperature space. However, this uniform distribution in temperature space may not be optimal since high temperatures do not always speed up the conformational transitions of interest, as anti-Arrhenius kinetics are prevalent in protein and RNA folding. Here, we propose a new method: Enhancing Pairwise State-transition Weights (EPSW), to obtain the optimal weights by minimizing the round-trip time for transitions among different metastable states at the temperature of interest in ST. The novelty of the EPSW algorithm lies in explicitly considering the kinetics of conformation transitions when optimizing the weights of different temperatures. We further demonstrate the power of EPSW in three different systems: a simple two-temperature model, a two-dimensional model for protein folding with anti-Arrhenius kinetics, and the alanine dipeptide. The results from these three systems showed that the new algorithm can substantially accelerate the transitions between conformational states of interest in the ST expanded ensemble and further facilitate the convergence of thermodynamics compared to the widely used free energy weights. We anticipate that this algorithm is particularly useful for studying functional conformational changes of biological systems where the initial and final states are often known from structural biology experiments.

Revisiting the diffusion approximation to estimate evolutionary rates of gene family diversification.

PubMed

Gjini, Erida; Haydon, Daniel T; David Barry, J; Cobbold, Christina A

2014-01-21

Genetic diversity in multigene families is shaped by multiple processes, including gene conversion and point mutation. Because multi-gene families are involved in crucial traits of organisms, quantifying the rates of their genetic diversification is important. With increasing availability of genomic data, there is a growing need for quantitative approaches that integrate the molecular evolution of gene families with their higher-scale function. In this study, we integrate a stochastic simulation framework with population genetics theory, namely the diffusion approximation, to investigate the dynamics of genetic diversification in a gene family. Duplicated genes can diverge and encode new functions as a result of point mutation, and become more similar through gene conversion. To model the evolution of pairwise identity in a multigene family, we first consider all conversion and mutation events in a discrete manner, keeping track of their details and times of occurrence; second we consider only the infinitesimal effect of these processes on pairwise identity accounting for random sampling of genes and positions. The purely stochastic approach is closer to biological reality and is based on many explicit parameters, such as conversion tract length and family size, but is more challenging analytically. The population genetics approach is an approximation accounting implicitly for point mutation and gene conversion, only in terms of per-site average probabilities. Comparison of these two approaches across a range of parameter combinations reveals that they are not entirely equivalent, but that for certain relevant regimes they do match. As an application of this modelling framework, we consider the distribution of nucleotide identity among VSG genes of African trypanosomes, representing the most prominent example of a multi-gene family mediating parasite antigenic variation and within-host immune evasion. © 2013 Published by Elsevier Ltd. All rights reserved.

Enhancing pairwise state-transition weights: A new weighting scheme in simulated tempering that can minimize transition time between a pair of conformational states

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

Qiao, Qin, E-mail: qqiao@ust.hk; Zhang, Hou-Dao; Huang, Xuhui, E-mail: xuhuihuang@ust.hk

2016-04-21

Simulated tempering (ST) is a widely used enhancing sampling method for Molecular Dynamics simulations. As one expanded ensemble method, ST is a combination of canonical ensembles at different temperatures and the acceptance probability of cross-temperature transitions is determined by both the temperature difference and the weights of each temperature. One popular way to obtain the weights is to adopt the free energy of each canonical ensemble, which achieves uniform sampling among temperature space. However, this uniform distribution in temperature space may not be optimal since high temperatures do not always speed up the conformational transitions of interest, as anti-Arrhenius kineticsmore » are prevalent in protein and RNA folding. Here, we propose a new method: Enhancing Pairwise State-transition Weights (EPSW), to obtain the optimal weights by minimizing the round-trip time for transitions among different metastable states at the temperature of interest in ST. The novelty of the EPSW algorithm lies in explicitly considering the kinetics of conformation transitions when optimizing the weights of different temperatures. We further demonstrate the power of EPSW in three different systems: a simple two-temperature model, a two-dimensional model for protein folding with anti-Arrhenius kinetics, and the alanine dipeptide. The results from these three systems showed that the new algorithm can substantially accelerate the transitions between conformational states of interest in the ST expanded ensemble and further facilitate the convergence of thermodynamics compared to the widely used free energy weights. We anticipate that this algorithm is particularly useful for studying functional conformational changes of biological systems where the initial and final states are often known from structural biology experiments.« less

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.

Modeling the Association of Space, Time, and Host Species with Variation of the HA, NA, and NS Genes of H5N1 Highly Pathogenic Avian Influenza Viruses Isolated from Birds in Romania in 2005–2007

PubMed Central

Alkhamis, Mohammad; Perez, Andres; Batey, Nicole; Howard, Wendy; Baillie, Greg; Watson, Simon; Franz, Stephanie; Focosi-Snyman, Raffaella; Onita, Iuliana; Cioranu, Raluca; Turcitu, Mihai; Kellam, Paul; Brown, Ian H.; Breed, Andrew C.

2014-01-01

SUMMARY Molecular characterization studies of a diverse collection of avian influenza viruses (AIVs) have demonstrated that AIVs’ greatest genetic variability lies in the HA, NA, and NS genes. The objective here was to quantify the association between geographical locations, periods of time, and host species and pairwise nucleotide variation in the HA, NA, and NS genes of 70 isolates of H5N1 highly pathogenic avian influenza virus (HPAIV) collected from October 2005 to December 2007 from birds in Romania. A mixed-binomial Bayesian regression model was used to quantify the probability of nucleotide variation between isolates and its association with space, time, and host species. As expected for the three target genes, a higher probability of nucleotide differences (odds ratios [ORs] > 1) was found between viruses sampled from places at greater geographical distances from each other, viruses sampled over greater periods of time, and viruses derived from different species. The modeling approach in the present study maybe useful in further understanding the molecular epidemiology of H5N1 HPAI virus in bird populations. The methodology presented here will be useful in predicting the most likely genetic distance for any of the three gene segments of viruses that have not yet been isolated or sequenced based on space, time, and host species during the course of an epidemic. PMID:24283126

Modeling the association of space, time, and host species with variation of the HA, NA, and NS genes of H5N1 highly pathogenic avian influenza viruses isolated from birds in Romania in 2005-2007.

PubMed

Alkhamis, Mohammad; Perez, Andres; Batey, Nicole; Howard, Wendy; Baillie, Greg; Watson, Simon; Franz, Stephanie; Focosi-Snyman, Raffaella; Onita, Iuliana; Cioranu, Raluca; Turcitu, Mihai; Kellam, Paul; Brown, Ian H; Breed, Andrew C

2013-09-01

Molecular characterization studies of a diverse collection of avian influenza viruses (AIVs) have demonstrated that AIVs' greatest genetic variability lies in the HA, NA, and NS genes. The objective here was to quantify the association between geographical locations, periods of time, and host species and pairwise nucleotide variation in the HA, NA, and NS genes of 70 isolates of H5N1 highly pathogenic avian influenza virus (HPAIV) collected from October 2005 to December 2007 from birds in Romania. A mixed-binomial Bayesian regression model was used to quantify the probability of nucleotide variation between isolates and its association with space, time, and host species. As expected for the three target genes, a higher probability of nucleotide differences (odds ratios [ORs] > 1) was found between viruses sampled from places at greater geographical distances from each other, viruses sampled over greater periods of time, and viruses derived from different species. The modeling approach in the present study maybe useful in further understanding the molecular epidemiology of H5N1 HPAI virus in bird populations. The methodology presented here will be useful in predicting the most likely genetic distance for any of the three gene segments of viruses that have not yet been isolated or sequenced based on space, time, and host species during the course of an epidemic.

An activity canyon characterization of the pharmacological topography.

PubMed

Kulkarni, Varsha S; Wild, David J

2016-01-01

Highly chemically similar drugs usually possess similar biological activities, but sometimes, small changes in chemistry can result in a large difference in biological effects. Chemically similar drug pairs that show extreme deviations in activity represent distinctive drug interactions having important implications. These associations between chemical and biological similarity are studied as discontinuities in activity landscapes. Particularly, activity cliffs are quantified by the drop in similar activity of chemically similar drugs. In this paper, we construct a landscape using a large drug-target network and consider the rises in similarity and variation in activity along the chemical space. Detailed analysis of structure and activity gives a rigorous quantification of distinctive pairs and the probability of their occurrence. We analyze pairwise similarity (s) and variation (d) in activity of drugs on proteins. Interactions between drugs are quantified by considering pairwise s and d weights jointly with corresponding chemical similarity (c) weights. Similarity and variation in activity are measured as the number of common and uncommon targets of two drugs respectively. Distinctive interactions occur between drugs having high c and above (below) average d (s). Computation of predicted probability of distinctiveness employs joint probability of c, s and of c, d assuming independence of structure and activity. Predictions conform with the observations at different levels of distinctiveness. Results are validated on the data used and another drug ensemble. In the landscape, while s and d decrease as c increases, d maintains value more than s. c ∈ [0.3, 0.64] is the transitional region where rises in d are significantly greater than drops in s. It is fascinating that distinctive interactions filtered with high d and low s are different in nature. It is crucial that high c interactions are more probable of having above average d than s. Identification of distinctive interactions is better with high d than low s. These interactions belong to diverse classes. d is greatest between drugs and analogs prepared for treatment of same class of ailments but with different therapeutic specifications. In contrast, analogs having low s would treat ailments from distinct classes. Intermittent spikes in d along the axis of c represent canyons in the activity landscape. This new representation accounts for distinctiveness through relative rises in s and d. It provides a mathematical basis for predicting the probability of occurrence of distinctiveness. It identifies the drug pairs at varying levels of distinctiveness and non-distinctiveness. The predicted probability formula is validated even if data approximately satisfy the conditions of its construction. Also, the postulated independence of structure and activity is of little significance to the overall assessment. The difference in distinctive interactions obtained by s and d highlights the importance of studying both of them, and reveals how the choice of measurement can affect the interpretation. The methods in this paper can be used to interpret whether or not drug interactions are distinctive and the probability of their occurrence. Practitioners and researchers can rely on this identification for quantitative modeling and assessment.

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.

The construct-behavior gap in behavioral decision research: A challenge beyond replicability.

PubMed

Regenwetter, Michel; Robinson, Maria M

2017-10-01

Behavioral decision research compares theoretical constructs like preferences to behavior such as observed choices. Three fairly common links from constructs to behavior are (1) to tally, across participants and decision problems, the number of choices consistent with one predicted pattern of pairwise preferences; (2) to compare what most people choose in each decision problem against a predicted preference pattern; or (3) to enumerate the decision problems in which two experimental conditions generate a 1-sided significant difference in choice frequency 'consistent' with the theory. Although simple, these theoretical links are heuristics. They are subject to well-known reasoning fallacies, most notably the fallacy of sweeping generalization and the fallacy of composition. No amount of replication can alleviate these fallacies. On the contrary, reiterating logically inconsistent theoretical reasoning over and again across studies obfuscates science. As a case in point, we consider pairwise choices among simple lotteries and the hypotheses of overweighting or underweighting of small probabilities, as well as the description-experience gap. We discuss ways to avoid reasoning fallacies in bridging the conceptual gap between hypothetical constructs, such as, for example, "overweighting" to observable pairwise choice data. Although replication is invaluable, successful replication of hard-to-interpret results is not. Behavioral decision research stands to gain much theoretical and empirical clarity by spelling out precise and formally explicit theories of how hypothetical constructs translate into observable behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

Modelling indirect interactions during failure spreading in a project activity network.

PubMed

Ellinas, Christos

2018-03-12

Spreading broadly refers to the notion of an entity propagating throughout a networked system via its interacting components. Evidence of its ubiquity and severity can be seen in a range of phenomena, from disease epidemics to financial systemic risk. In order to understand the dynamics of these critical phenomena, computational models map the probability of propagation as a function of direct exposure, typically in the form of pairwise interactions between components. By doing so, the important role of indirect interactions remains unexplored. In response, we develop a simple model that accounts for the effect of both direct and subsequent exposure, which we deploy in the novel context of failure propagation within a real-world engineering project. We show that subsequent exposure has a significant effect in key aspects, including the: (a) final spreading event size, (b) propagation rate, and (c) spreading event structure. In addition, we demonstrate the existence of 'hidden influentials' in large-scale spreading events, and evaluate the role of direct and subsequent exposure in their emergence. Given the evidence of the importance of subsequent exposure, our findings offer new insight on particular aspects that need to be included when modelling network dynamics in general, and spreading processes specifically.

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.

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.

Uncertainty quantification for complex systems with very high dimensional response using Grassmann manifold variations

NASA Astrophysics Data System (ADS)

Giovanis, D. G.; Shields, M. D.

2018-07-01

This paper addresses uncertainty quantification (UQ) for problems where scalar (or low-dimensional vector) response quantities are insufficient and, instead, full-field (very high-dimensional) responses are of interest. To do so, an adaptive stochastic simulation-based methodology is introduced that refines the probability space based on Grassmann manifold variations. The proposed method has a multi-element character discretizing the probability space into simplex elements using a Delaunay triangulation. For every simplex, the high-dimensional solutions corresponding to its vertices (sample points) are projected onto the Grassmann manifold. The pairwise distances between these points are calculated using appropriately defined metrics and the elements with large total distance are sub-sampled and refined. As a result, regions of the probability space that produce significant changes in the full-field solution are accurately resolved. An added benefit is that an approximation of the solution within each element can be obtained by interpolation on the Grassmann manifold. The method is applied to study the probability of shear band formation in a bulk metallic glass using the shear transformation zone theory.

Particle-based simulations of self-motile suspensions

NASA Astrophysics Data System (ADS)

Hinz, Denis F.; Panchenko, Alexander; Kim, Tae-Yeon; Fried, Eliot

2015-11-01

A simple model for simulating flows of active suspensions is investigated. The approach is based on dissipative particle dynamics. While the model is potentially applicable to a wide range of self-propelled particle systems, the specific class of self-motile bacterial suspensions is considered as a modeling scenario. To mimic the rod-like geometry of a bacterium, two dissipative particle dynamics particles are connected by a stiff harmonic spring to form an aggregate dissipative particle dynamics molecule. Bacterial motility is modeled through a constant self-propulsion force applied along the axis of each such aggregate molecule. The model accounts for hydrodynamic interactions between self-propelled agents through the pairwise dissipative interactions conventional to dissipative particle dynamics. Numerical simulations are performed using a customized version of the open-source software package LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) software package. Detailed studies of the influence of agent concentration, pairwise dissipative interactions, and Stokes friction on the statistics of the system are provided. The simulations are used to explore the influence of hydrodynamic interactions in active suspensions. For high agent concentrations in combination with dominating pairwise dissipative forces, strongly correlated motion patterns and a fluid-like spectral distributions of kinetic energy are found. In contrast, systems dominated by Stokes friction exhibit weaker spatial correlations of the velocity field. These results indicate that hydrodynamic interactions may play an important role in the formation of spatially extended structures in active suspensions.

Precoded spatial multiplexing MIMO system with spatial component interleaver.

PubMed

Gao, Xiang; Wu, Zhanji

In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.

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.

An R package for analyzing and modeling ranking data

PubMed Central

2013-01-01

Background In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty’s and Koczkodaj’s inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis. Results Examples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians’ preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as “internal/external”), and the second dimension can be interpreted as their overall variance of (labeled as “push/pull factors”). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman’s footrule distance. Conclusions In this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought multidimensional preference analysis. Various probability models for ranking data are also included, allowing users to choose that which is most suitable to their specific situations. PMID:23672645

An R package for analyzing and modeling ranking data.

PubMed

Lee, Paul H; Yu, Philip L H

2013-05-14

In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis. Examples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians' preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as "internal/external"), and the second dimension can be interpreted as their overall variance of (labeled as "push/pull factors"). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman's footrule distance. In this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought multidimensional preference analysis. Various probability models for ranking data are also included, allowing users to choose that which is most suitable to their specific situations.

Evaluating factors that predict the structure of a commensalistic epiphyte–phorophyte network

PubMed Central

Sáyago, Roberto; Lopezaraiza-Mikel, Martha; Quesada, Mauricio; Álvarez-Añorve, Mariana Yolotl; Cascante-Marín, Alfredo; Bastida, Jesus Ma.

2013-01-01

A central issue in ecology is the understanding of the establishment of biotic interactions. We studied the factors that affect the assembly of the commensalistic interactions between vascular epiphytes and their host plants. We used an analytical approach that considers all individuals and species of epiphytic bromeliads and woody hosts and non-hosts at study plots. We built models of interaction probabilities among species to assess if host traits and abundance and spatial overlap of species predict the quantitative epiphyte–host network. Species abundance, species spatial overlap and host size largely predicted pairwise interactions and several network metrics. Wood density and bark texture of hosts also contributed to explain network structure. Epiphytes were more common on large hosts, on abundant woody species, with denser wood and/or rougher bark. The network had a low level of specialization, although several interactions were more frequent than expected by the models. We did not detect a phylogenetic signal on the network structure. The effect of host size on the establishment of epiphytes indicates that mature forests are necessary to preserve diverse bromeliad communities. PMID:23407832

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.

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.

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.

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to that of the complex model including epistatic effects. Conclusions This simulation study showed that the fBayesB approach is convenient for genetic value prediction. Jointly estimating additive and non-additive effects (especially dominance) has reasonable impact on the accuracy of prediction and the proportion of genetic variation assigned to the additive genetic source. PMID:21867519

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.

Bayesian probability analysis: a prospective demonstration of its clinical utility in diagnosing coronary disease

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

Detrano, R.; Yiannikas, J.; Salcedo, E.E.

One hundred fifty-four patients referred for coronary arteriography were prospectively studied with stress electrocardiography, stress thallium scintigraphy, cine fluoroscopy (for coronary calcifications), and coronary angiography. Pretest probabilities of coronary disease were determined based on age, sex, and type of chest pain. These and pooled literature values for the conditional probabilities of test results based on disease state were used in Bayes theorem to calculate posttest probabilities of disease. The results of the three noninvasive tests were compared for statistical independence, a necessary condition for their simultaneous use in Bayes theorem. The test results were found to demonstrate pairwise independence inmore » patients with and those without disease. Some dependencies that were observed between the test results and the clinical variables of age and sex were not sufficient to invalidate application of the theorem. Sixty-eight of the study patients had at least one major coronary artery obstruction of greater than 50%. When these patients were divided into low-, intermediate-, and high-probability subgroups according to their pretest probabilities, noninvasive test results analyzed by Bayesian probability analysis appropriately advanced 17 of them by at least one probability subgroup while only seven were moved backward. Of the 76 patients without disease, 34 were appropriately moved into a lower probability subgroup while 10 were incorrectly moved up. We conclude that posttest probabilities calculated from Bayes theorem more accurately classified patients with and without disease than did pretest probabilities, thus demonstrating the utility of the theorem in this application.« less

Template-based protein-protein docking exploiting pairwise interfacial residue restraints.

PubMed

Xue, Li C; Rodrigues, João P G L M; Dobbs, Drena; Honavar, Vasant; Bonvin, Alexandre M J J

2017-05-01

Although many advanced and sophisticated ab initio approaches for modeling protein-protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to exploit template information in the modeling process. Here, we systematically evaluate and benchmark a TBM method that uses conserved interfacial residue pairs as docking distance restraints [referred to as alpha carbon-alpha carbon (CA-CA)-guided docking]. We compare it with two other template-based protein-protein modeling approaches, including a conserved non-pairwise interfacial residue restrained docking approach [referred to as the ambiguous interaction restraint (AIR)-guided docking] and a simple superposition-based modeling approach. Our results show that, for most cases, the CA-CA-guided docking method outperforms both superposition with refinement and the AIR-guided docking method. We emphasize the superiority of the CA-CA-guided docking on cases with medium to large conformational changes, and interactions mediated through loops, tails or disordered regions. Our results also underscore the importance of a proper refinement of superimposition models to reduce steric clashes. In summary, we provide a benchmarked TBM protocol that uses conserved pairwise interface distance as restraints in generating realistic 3D protein-protein interaction models, when reliable templates are available. The described CA-CA-guided docking protocol is based on the HADDOCK platform, which allows users to incorporate additional prior knowledge of the target system to further improve the quality of the resulting models. © The Author 2016. Published by Oxford University Press.

Systematic review and economic modelling of the effectiveness and cost-effectiveness of non-surgical treatments for women with stress urinary incontinence.

PubMed

Imamura, M; Abrams, P; Bain, C; Buckley, B; Cardozo, L; Cody, J; Cook, J; Eustice, S; Glazener, C; Grant, A; Hay-Smith, J; Hislop, J; Jenkinson, D; Kilonzo, M; Nabi, G; N'Dow, J; Pickard, R; Ternent, L; Wallace, S; Wardle, J; Zhu, S; Vale, L

2010-08-01

To assess the clinical effectiveness and cost-effectiveness of non-surgical treatments for women with stress urinary incontinence (SUI) through systematic review and economic modelling. The Cochrane Incontinence Group Specialised Register, electronic databases and the websites of relevant professional organisations and manufacturers, and the following databases: CINAHL, EMBASE, BIOSIS, Science Citation Index and Social Science Citation Index, Current Controlled Trials, ClinicalTrials.gov and the UKCRN Portfolio Database. The study comprised three distinct elements. (1) A survey of 188 women with SUI to identify outcomes of importance to them (activities of daily living; sex, hygiene and lifestyle issues; emotional health; and the availability of services). (2) A systematic review and meta-analysis of non-surgical treatments for SUI to find out which are most effective by comparing results of trials (direct pairwise comparisons) and by modelling results (mixed-treatment comparisons - MTCs). A total of 88 randomised controlled trials (RCTs) and quasi-RCTs reporting data from 9721 women were identified, considering five generic interventions [pelvic floor muscle training (PFMT), electrical stimulation (ES), vaginal cones (VCs), bladder training (BT) and serotonin-noradrenaline reuptake inhibitor (SNRI) medications], in many variations and combinations. Data were available for 37 interventions and 68 treatment comparisons by direct pairwise assessment. Mixed-treatment comparison models compared 14 interventions, using data from 55 trials (6608 women). (3) Economic modelling, using a Markov model, to find out which combinations of treatments (treatment pathways) are most cost-effective for SUI. Titles and abstracts identified were assessed by one reviewer and full-text copies of all potentially relevant reports independently assessed by two reviewers. Any disagreements were resolved by consensus or arbitration by a third person. Direct pairwise comparison and MTC analysis showed that the treatments were more effective than no treatment. Delivering PFMT in a more intense fashion, either through extra sessions or with biofeedback (BF), appeared to be the most effective treatment [PFMT extra sessions vs no treatment (NT) odds ratio (OR) 10.7, 95% credible interval (CrI) 5.03 to 26.2; PFMT + BF vs NT OR 12.3, 95% CrI 5.35 to 32.7]. Only when success was measured in terms of improvement was there evidence that basic PFMT was better than no treatment (PFMT basic vs NT OR 4.47, 95% CrI 2.03 to 11.9). Analysis of cost-effectiveness showed that for cure rates, the strategy using lifestyle changes and PFMT with extra sessions followed by tension-free vaginal tape (TVT) (lifestyle advice-PFMT extra sessions-TVT) had a probability of greater than 70% of being considered cost-effective for all threshold values for willingness to pay for a QALY up to 50,000 pounds. For improvement rates, lifestyle advice-PFMT extra sessions-TVT had a probability of greater than 50% of being considered cost-effective when society's willingness to pay for an additional QALY was more than 10,000 pounds. The results were most sensitive to changes in the long-term performance of PFMT and also in the relative effectiveness of basic PFMT and PFMT with extra sessions. Although a large number of studies were identified, few data were available for most comparisons and long-term data were sparse. Challenges for evidence synthesis were the lack of consensus on the most appropriate method for assessing incontinence and intervention protocols that were complex and varied considerably across studies. More intensive forms of PFMT appear worthwhile, but further research is required to define an optimal form of more intensive therapy that is feasible and efficient for the NHS to provide, along with further definitive evidence from large, well-designed studies.

Historical demography of common carp estimated from individuals collected from various parts of the world using the pairwise sequentially markovian coalescent approach.

PubMed

Yuan, Zihao; Huang, Wei; Liu, Shikai; Xu, Peng; Dunham, Rex; Liu, Zhanjiang

2018-04-01

The inference of historical demography of a species is helpful for understanding species' differentiation and its population dynamics. However, such inference has been previously difficult due to the lack of proper analytical methods and availability of genetic data. A recently developed method called Pairwise Sequentially Markovian Coalescent (PSMC) offers the capability for estimation of the trajectories of historical populations over considerable time periods using genomic sequences. In this study, we applied this approach to infer the historical demography of the common carp using samples collected from Europe, Asia and the Americas. Comparison between Asian and European common carp populations showed that the last glacial period starting 100 ka BP likely caused a significant decline in population size of the wild common carp in Europe, while it did not have much of an impact on its counterparts in Asia. This was probably caused by differences in glacial activities in East Asia and Europe, and suggesting a separation of the European and Asian clades before the last glacial maximum. The North American clade which is an invasive population shared a similar demographic history as those from Europe, consistent with the idea that the North American common carp probably had European ancestral origins. Our analysis represents the first reconstruction of the historical population demography of the common carp, which is important to elucidate the separation of European and Asian common carp clades during the Quaternary glaciation, as well as the dispersal of common carp across the world.

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.

Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

USGS Publications Warehouse

Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

2016-01-01

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

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.

cDF Theory Software for mesoscopic modeling of equilibrium and transport phenomena

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

2015-12-01

The approach is based on classical Density Functional Theory ((cDFT) coupled with the Poisson-Nernst-Planck (PNP) transport kinetics model and quantum mechanical description of short-range interaction and elementary transport processes. The model we proposed and implemented is fully atomistic, taking into account pairwise short-range and manybody long-range interactions. But in contrast to standard molecular dynamics (MD) simulations, where long-range manybody interactions are evaluated as a sum of pair-wise atom-atom contributions, we include them analytically based on wellestablished theories of electrostatic and excluded volume interactions in multicomponent systems. This feature of the PNP/cDFT approach allows us to reach well beyond the length-scalesmore » accessible to MD simulations, while retaining the essential physics of interatomic interactions from first principles and in a parameter-free fashion.« less

Learning maximum entropy models from finite-size data sets: A fast data-driven algorithm allows sampling from the posterior distribution.

PubMed

Ferrari, Ulisse

2016-08-01

Maximum entropy models provide the least constrained probability distributions that reproduce statistical properties of experimental datasets. In this work we characterize the learning dynamics that maximizes the log-likelihood in the case of large but finite datasets. We first show how the steepest descent dynamics is not optimal as it is slowed down by the inhomogeneous curvature of the model parameters' space. We then provide a way for rectifying this space which relies only on dataset properties and does not require large computational efforts. We conclude by solving the long-time limit of the parameters' dynamics including the randomness generated by the systematic use of Gibbs sampling. In this stochastic framework, rather than converging to a fixed point, the dynamics reaches a stationary distribution, which for the rectified dynamics reproduces the posterior distribution of the parameters. We sum up all these insights in a "rectified" data-driven algorithm that is fast and by sampling from the parameters' posterior avoids both under- and overfitting along all the directions of the parameters' space. Through the learning of pairwise Ising models from the recording of a large population of retina neurons, we show how our algorithm outperforms the steepest descent method.

[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

Constraints on the optical depth of galaxy groups and clusters

DOE PAGES

Flender, Samuel; Nagai, Daisuke; McDonald, Michael

2017-03-10

Here, future data from galaxy redshift surveys, combined with high-resolutions maps of the cosmic microwave background, will enable measurements of the pairwise kinematic Sunyaev–Zel'dovich (kSZ) signal with unprecedented statistical significance. This signal probes the matter-velocity correlation function, scaled by the average optical depth (τ) of the galaxy groups and clusters in the sample, and is thus of fundamental importance for cosmology. However, in order to translate pairwise kSZ measurements into cosmological constraints, external constraints on τ are necessary. In this work, we present a new model for the intracluster medium, which takes into account star formation, feedback, non-thermal pressure, and gas cooling. Our semi-analytic model is computationally efficient and can reproduce results of recent hydrodynamical simulations of galaxy cluster formation. We calibrate the free parameters in the model using recent X-ray measurements of gas density profiles of clusters, and gas masses of groups and clusters. Our observationally calibrated model predicts the averagemore » $${\\tau }_{500}$$ (i.e., the integrated τ within a disk of size R 500) to better than 6% modeling uncertainty (at 95% confidence level). If the remaining uncertainties associated with other astrophysical uncertainties and X-ray selection effects can be better understood, our model for the optical depth should break the degeneracy between optical depth and cluster velocity in the analysis of future pairwise kSZ measurements and improve cosmological constraints with the combination of upcoming galaxy and CMB surveys, including the nature of dark energy, modified gravity, and neutrino mass.« less

Constraints on the optical depth of galaxy groups and clusters

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

Flender, Samuel; Nagai, Daisuke; McDonald, Michael

Here, future data from galaxy redshift surveys, combined with high-resolutions maps of the cosmic microwave background, will enable measurements of the pairwise kinematic Sunyaev–Zel'dovich (kSZ) signal with unprecedented statistical significance. This signal probes the matter-velocity correlation function, scaled by the average optical depth (τ) of the galaxy groups and clusters in the sample, and is thus of fundamental importance for cosmology. However, in order to translate pairwise kSZ measurements into cosmological constraints, external constraints on τ are necessary. In this work, we present a new model for the intracluster medium, which takes into account star formation, feedback, non-thermal pressure, and gas cooling. Our semi-analytic model is computationally efficient and can reproduce results of recent hydrodynamical simulations of galaxy cluster formation. We calibrate the free parameters in the model using recent X-ray measurements of gas density profiles of clusters, and gas masses of groups and clusters. Our observationally calibrated model predicts the averagemore » $${\\tau }_{500}$$ (i.e., the integrated τ within a disk of size R 500) to better than 6% modeling uncertainty (at 95% confidence level). If the remaining uncertainties associated with other astrophysical uncertainties and X-ray selection effects can be better understood, our model for the optical depth should break the degeneracy between optical depth and cluster velocity in the analysis of future pairwise kSZ measurements and improve cosmological constraints with the combination of upcoming galaxy and CMB surveys, including the nature of dark energy, modified gravity, and neutrino mass.« less

Design and implementation of a hybrid MPI-CUDA model for the Smith-Waterman algorithm.

PubMed

Khaled, Heba; Faheem, Hossam El Deen Mostafa; El Gohary, Rania

2015-01-01

This paper provides a novel hybrid model for solving the multiple pair-wise sequence alignment problem combining message passing interface and CUDA, the parallel computing platform and programming model invented by NVIDIA. The proposed model targets homogeneous cluster nodes equipped with similar Graphical Processing Unit (GPU) cards. The model consists of the Master Node Dispatcher (MND) and the Worker GPU Nodes (WGN). The MND distributes the workload among the cluster working nodes and then aggregates the results. The WGN performs the multiple pair-wise sequence alignments using the Smith-Waterman algorithm. We also propose a modified implementation to the Smith-Waterman algorithm based on computing the alignment matrices row-wise. The experimental results demonstrate a considerable reduction in the running time by increasing the number of the working GPU nodes. The proposed model achieved a performance of about 12 Giga cell updates per second when we tested against the SWISS-PROT protein knowledge base running on four nodes.

Computing the non-Markovian coarse-grained interactions derived from the Mori-Zwanzig formalism in molecular systems: Application to polymer melts

NASA Astrophysics Data System (ADS)

Li, Zhen; Lee, Hee Sun; Darve, Eric; Karniadakis, George Em

2017-01-01

Memory effects are often introduced during coarse-graining of a complex dynamical system. In particular, a generalized Langevin equation (GLE) for the coarse-grained (CG) system arises in the context of Mori-Zwanzig formalism. Upon a pairwise decomposition, GLE can be reformulated into its pairwise version, i.e., non-Markovian dissipative particle dynamics (DPD). GLE models the dynamics of a single coarse particle, while DPD considers the dynamics of many interacting CG particles, with both CG systems governed by non-Markovian interactions. We compare two different methods for the practical implementation of the non-Markovian interactions in GLE and DPD systems. More specifically, a direct evaluation of the non-Markovian (NM) terms is performed in LE-NM and DPD-NM models, which requires the storage of historical information that significantly increases computational complexity. Alternatively, we use a few auxiliary variables in LE-AUX and DPD-AUX models to replace the non-Markovian dynamics with a Markovian dynamics in a higher dimensional space, leading to a much reduced memory footprint and computational cost. In our numerical benchmarks, the GLE and non-Markovian DPD models are constructed from molecular dynamics (MD) simulations of star-polymer melts. Results show that a Markovian dynamics with auxiliary variables successfully generates equivalent non-Markovian dynamics consistent with the reference MD system, while maintaining a tractable computational cost. Also, transient subdiffusion of the star-polymers observed in the MD system can be reproduced by the coarse-grained models. The non-interacting particle models, LE-NM/AUX, are computationally much cheaper than the interacting particle models, DPD-NM/AUX. However, the pairwise models with momentum conservation are more appropriate for correctly reproducing the long-time hydrodynamics characterised by an algebraic decay in the velocity autocorrelation function.

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

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.

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

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.

Event-chain Monte Carlo algorithms for three- and many-particle interactions

NASA Astrophysics Data System (ADS)

Harland, J.; Michel, M.; Kampmann, T. A.; Kierfeld, J.

2017-02-01

We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. We validate the resulting three-particle event-chain Monte Carlo algorithms on three different systems by comparison with conventional local Monte Carlo simulations: i) a test system of three particles with a three-particle interaction that depends on the enclosed triangle area; ii) a hard-needle system in two dimensions, where needle interactions constitute three-particle interactions of the needle end points; iii) a semiflexible polymer chain with a bending energy, which constitutes a three-particle interaction of neighboring chain beads. The examples demonstrate that the generalization to many-particle interactions broadens the applicability of event-chain algorithms considerably.

Voids and constraints on nonlinear clustering of galaxies

NASA Technical Reports Server (NTRS)

Vogeley, Michael S.; Geller, Margaret J.; Park, Changbom; Huchra, John P.

1994-01-01

Void statistics of the galaxy distribution in the Center for Astrophysics Redshift Survey provide strong constraints on galaxy clustering in the nonlinear regime, i.e., on scales R equal to or less than 10/h Mpc. Computation of high-order moments of the galaxy distribution requires a sample that (1) densely traces the large-scale structure and (2) covers sufficient volume to obtain good statistics. The CfA redshift survey densely samples structure on scales equal to or less than 10/h Mpc and has sufficient depth and angular coverage to approach a fair sample on these scales. In the nonlinear regime, the void probability function (VPF) for CfA samples exhibits apparent agreement with hierarchical scaling (such scaling implies that the N-point correlation functions for N greater than 2 depend only on pairwise products of the two-point function xi(r)) However, simulations of cosmological models show that this scaling in redshift space does not necessarily imply such scaling in real space, even in the nonlinear regime; peculiar velocities cause distortions which can yield erroneous agreement with hierarchical scaling. The underdensity probability measures the frequency of 'voids' with density rho less than 0.2 -/rho. This statistic reveals a paucity of very bright galaxies (L greater than L asterisk) in the 'voids.' Underdensities are equal to or greater than 2 sigma more frequent in bright galaxy samples than in samples that include fainter galaxies. Comparison of void statistics of CfA samples with simulations of a range of cosmological models favors models with Gaussian primordial fluctuations and Cold Dark Matter (CDM)-like initial power spectra. Biased models tend to produce voids that are too empty. We also compare these data with three specific models of the Cold Dark Matter cosmogony: an unbiased, open universe CDM model (omega = 0.4, h = 0.5) provides a good match to the VPF of the CfA samples. Biasing of the galaxy distribution in the 'standard' CDM model (omega = 1, b = 1.5; see below for definitions) and nonzero cosmological constant CDM model (omega = 0.4, h = 0.6 lambda(sub 0) = 0.6, b = 1.3) produce voids that are too empty. All three simulations match the observed VPF and underdensity probability for samples of very bright (M less than M asterisk = -19.2) galaxies, but produce voids that are too empty when compared with samples that include fainter galaxies.

Pairwise Force SPH Model for Real-Time Multi-Interaction Applications.

PubMed

Yang, Tao; Martin, Ralph R; Lin, Ming C; Chang, Jian; Hu, Shi-Min

2017-10-01

In this paper, we present a novel pairwise-force smoothed particle hydrodynamics (PF-SPH) model to enable simulation of various interactions at interfaces in real time. Realistic capture of interactions at interfaces is a challenging problem for SPH-based simulations, especially for scenarios involving multiple interactions at different interfaces. Our PF-SPH model can readily handle multiple types of interactions simultaneously in a single simulation; its basis is to use a larger support radius than that used in standard SPH. We adopt a novel anisotropic filtering term to further improve the performance of interaction forces. The proposed model is stable; furthermore, it avoids the particle clustering problem which commonly occurs at the free surface. We show how our model can be used to capture various interactions. We also consider the close connection between droplets and bubbles, and show how to animate bubbles rising in liquid as well as bubbles in air. Our method is versatile, physically plausible and easy-to-implement. Examples are provided to demonstrate the capabilities and effectiveness of our approach.

A water market simulator considering pair-wise trades between agents

NASA Astrophysics Data System (ADS)

Huskova, I.; Erfani, T.; Harou, J. J.

2012-04-01

In many basins in England no further water abstraction licences are available. Trading water between water rights holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. A screening tool that could assess the potential for trade through realistic simulation of individual water rights holders would help assess the solution's potential contribution to local water management. We propose an optimisation-driven water market simulator that predicts pair-wise trade in a catchment and represents its interaction with natural hydrology and engineered infrastructure. A model is used to emulate licence-holders' willingness to engage in short-term trade transactions. In their simplest form agents are represented using an economic benefit function. The working hypothesis is that trading behaviour can be partially predicted based on differences in marginal values of water over space and time and estimates of transaction costs on pair-wise trades. We discuss the further possibility of embedding rules, norms and preferences of the different water user sectors to more realistically represent the behaviours, motives and constraints of individual licence holders. The potential benefits and limitations of such a social simulation (agent-based) approach is contrasted with our simulator where agents are driven by economic optimization. A case study based on the Dove River Basin (UK) demonstrates model inputs and outputs. The ability of the model to suggest impacts of water rights policy reforms on trading is discussed.

Exact p-values for pairwise comparison of Friedman rank sums, with application to comparing classifiers.

PubMed

Eisinga, Rob; Heskes, Tom; Pelzer, Ben; Te Grotenhuis, Manfred

2017-01-25

The Friedman rank sum test is a widely-used nonparametric method in computational biology. In addition to examining the overall null hypothesis of no significant difference among any of the rank sums, it is typically of interest to conduct pairwise comparison tests. Current approaches to such tests rely on large-sample approximations, due to the numerical complexity of computing the exact distribution. These approximate methods lead to inaccurate estimates in the tail of the distribution, which is most relevant for p-value calculation. We propose an efficient, combinatorial exact approach for calculating the probability mass distribution of the rank sum difference statistic for pairwise comparison of Friedman rank sums, and compare exact results with recommended asymptotic approximations. Whereas the chi-squared approximation performs inferiorly to exact computation overall, others, particularly the normal, perform well, except for the extreme tail. Hence exact calculation offers an improvement when small p-values occur following multiple testing correction. Exact inference also enhances the identification of significant differences whenever the observed values are close to the approximate critical value. We illustrate the proposed method in the context of biological machine learning, were Friedman rank sum difference tests are commonly used for the comparison of classifiers over multiple datasets. We provide a computationally fast method to determine the exact p-value of the absolute rank sum difference of a pair of Friedman rank sums, making asymptotic tests obsolete. Calculation of exact p-values is easy to implement in statistical software and the implementation in R is provided in one of the Additional files and is also available at http://www.ru.nl/publish/pages/726696/friedmanrsd.zip .

Exclusion probabilities and likelihood ratios with applications to kinship problems.

PubMed

Slooten, Klaas-Jan; Egeland, Thore

2014-05-01

In forensic genetics, DNA profiles are compared in order to make inferences, paternity cases being a standard example. The statistical evidence can be summarized and reported in several ways. For example, in a paternity case, the likelihood ratio (LR) and the probability of not excluding a random man as father (RMNE) are two common summary statistics. There has been a long debate on the merits of the two statistics, also in the context of DNA mixture interpretation, and no general consensus has been reached. In this paper, we show that the RMNE is a certain weighted average of inverse likelihood ratios. This is true in any forensic context. We show that the likelihood ratio in favor of the correct hypothesis is, in expectation, bigger than the reciprocal of the RMNE probability. However, with the exception of pathological cases, it is also possible to obtain smaller likelihood ratios. We illustrate this result for paternity cases. Moreover, some theoretical properties of the likelihood ratio for a large class of general pairwise kinship cases, including expected value and variance, are derived. The practical implications of the findings are discussed and exemplified.

Music-evoked incidental happiness modulates probability weighting during risky lottery choices

PubMed Central

Schulreich, Stefan; Heussen, Yana G.; Gerhardt, Holger; Mohr, Peter N. C.; Binkofski, Ferdinand C.; Koelsch, Stefan; Heekeren, Hauke R.

2014-01-01

We often make decisions with uncertain consequences. The outcomes of the choices we make are usually not perfectly predictable but probabilistic, and the probabilities can be known or unknown. Probability judgments, i.e., the assessment of unknown probabilities, can be influenced by evoked emotional states. This suggests that also the weighting of known probabilities in decision making under risk might be influenced by incidental emotions, i.e., emotions unrelated to the judgments and decisions at issue. Probability weighting describes the transformation of probabilities into subjective decision weights for outcomes and is one of the central components of cumulative prospect theory (CPT) that determine risk attitudes. We hypothesized that music-evoked emotions would modulate risk attitudes in the gain domain and in particular probability weighting. Our experiment featured a within-subject design consisting of four conditions in separate sessions. In each condition, the 41 participants listened to a different kind of music—happy, sad, or no music, or sequences of random tones—and performed a repeated pairwise lottery choice task. We found that participants chose the riskier lotteries significantly more often in the “happy” than in the “sad” and “random tones” conditions. Via structural regressions based on CPT, we found that the observed changes in participants' choices can be attributed to changes in the elevation parameter of the probability weighting function: in the “happy” condition, participants showed significantly higher decision weights associated with the larger payoffs than in the “sad” and “random tones” conditions. Moreover, elevation correlated positively with self-reported music-evoked happiness. Thus, our experimental results provide evidence in favor of a causal effect of incidental happiness on risk attitudes that can be explained by changes in probability weighting. PMID:24432007

Music-evoked incidental happiness modulates probability weighting during risky lottery choices.

PubMed

Schulreich, Stefan; Heussen, Yana G; Gerhardt, Holger; Mohr, Peter N C; Binkofski, Ferdinand C; Koelsch, Stefan; Heekeren, Hauke R

2014-01-07

We often make decisions with uncertain consequences. The outcomes of the choices we make are usually not perfectly predictable but probabilistic, and the probabilities can be known or unknown. Probability judgments, i.e., the assessment of unknown probabilities, can be influenced by evoked emotional states. This suggests that also the weighting of known probabilities in decision making under risk might be influenced by incidental emotions, i.e., emotions unrelated to the judgments and decisions at issue. Probability weighting describes the transformation of probabilities into subjective decision weights for outcomes and is one of the central components of cumulative prospect theory (CPT) that determine risk attitudes. We hypothesized that music-evoked emotions would modulate risk attitudes in the gain domain and in particular probability weighting. Our experiment featured a within-subject design consisting of four conditions in separate sessions. In each condition, the 41 participants listened to a different kind of music-happy, sad, or no music, or sequences of random tones-and performed a repeated pairwise lottery choice task. We found that participants chose the riskier lotteries significantly more often in the "happy" than in the "sad" and "random tones" conditions. Via structural regressions based on CPT, we found that the observed changes in participants' choices can be attributed to changes in the elevation parameter of the probability weighting function: in the "happy" condition, participants showed significantly higher decision weights associated with the larger payoffs than in the "sad" and "random tones" conditions. Moreover, elevation correlated positively with self-reported music-evoked happiness. Thus, our experimental results provide evidence in favor of a causal effect of incidental happiness on risk attitudes that can be explained by changes in probability weighting.

Fire frequency, area burned, and severity: A quantitative approach to defining a normal fire year

USGS Publications Warehouse

Lutz, J.A.; Key, C.H.; Kolden, C.A.; Kane, J.T.; van Wagtendonk, J.W.

2011-01-01

Fire frequency, area burned, and fire severity are important attributes of a fire regime, but few studies have quantified the interrelationships among them in evaluating a fire year. Although area burned is often used to summarize a fire season, burned area may not be well correlated with either the number or ecological effect of fires. Using the Landsat data archive, we examined all 148 wildland fires (prescribed fires and wildfires) >40 ha from 1984 through 2009 for the portion of the Sierra Nevada centered on Yosemite National Park, California, USA. We calculated mean fire frequency and mean annual area burned from a combination of field- and satellite-derived data. We used the continuous probability distribution of the differenced Normalized Burn Ratio (dNBR) values to describe fire severity. For fires >40 ha, fire frequency, annual area burned, and cumulative severity were consistent in only 13 of 26 years (50 %), but all pair-wise comparisons among these fire regime attributes were significant. Borrowing from long-established practice in climate science, we defined "fire normals" to be the 26 year means of fire frequency, annual area burned, and the area under the cumulative probability distribution of dNBR. Fire severity normals were significantly lower when they were aggregated by year compared to aggregation by area. Cumulative severity distributions for each year were best modeled with Weibull functions (all 26 years, r2 ??? 0.99; P < 0.001). Explicit modeling of the cumulative severity distributions may allow more comprehensive modeling of climate-severity and area-severity relationships. Together, the three metrics of number of fires, size of fires, and severity of fires provide land managers with a more comprehensive summary of a given fire year than any single metric.

Experimental characterization of pairwise correlations from triple quantum correlated beams generated by cascaded four-wave mixing processes

NASA Astrophysics Data System (ADS)

Wang, Wei; Cao, Leiming; Lou, Yanbo; Du, Jinjian; Jing, Jietai

2018-01-01

We theoretically and experimentally characterize the performance of the pairwise correlations from triple quantum correlated beams based on the cascaded four-wave mixing (FWM) processes. The pairwise correlations between any two of the beams are theoretically calculated and experimentally measured. The experimental and theoretical results are in good agreement. We find that two of the three pairwise correlations can be in the quantum regime. The other pairwise correlation is always in the classical regime. In addition, we also measure the triple-beam correlation which is always in the quantum regime. Such unbalanced and controllable pairwise correlation structures may be taken as advantages in practical quantum communications, for example, hierarchical quantum secret sharing. Our results also open the way for the classification and application of quantum states generated from the cascaded FWM processes.

Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model.

PubMed

Liu, Dan; Liu, Xuejun; Wu, Yiguang

2018-04-24

This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

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.

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.

Using structural equation modeling for network meta-analysis.

PubMed

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison. SEM provides a very flexible framework for univariate and multivariate meta-analysis, and its potential as a powerful tool for advanced meta-analysis is still to be explored.

Hierarchical Interactions Model for Predicting Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) Conversion

PubMed Central

Li, Han; Liu, Yashu; Gong, Pinghua; Zhang, Changshui; Ye, Jieping

2014-01-01

Identifying patients with Mild Cognitive Impairment (MCI) who are likely to convert to dementia has recently attracted increasing attention in Alzheimer's disease (AD) research. An accurate prediction of conversion from MCI to AD can aid clinicians to initiate treatments at early stage and monitor their effectiveness. However, existing prediction systems based on the original biosignatures are not satisfactory. In this paper, we propose to fit the prediction models using pairwise biosignature interactions, thus capturing higher-order relationship among biosignatures. Specifically, we employ hierarchical constraints and sparsity regularization to prune the high-dimensional input features. Based on the significant biosignatures and underlying interactions identified, we build classifiers to predict the conversion probability based on the selected features. We further analyze the underlying interaction effects of different biosignatures based on the so-called stable expectation scores. We have used 293 MCI subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) database that have MRI measurements at the baseline to evaluate the effectiveness of the proposed method. Our proposed method achieves better classification performance than state-of-the-art methods. Moreover, we discover several significant interactions predictive of MCI-to-AD conversion. These results shed light on improving the prediction performance using interaction features. PMID:24416143

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.

Estimating Function Approaches for Spatial Point Processes

NASA Astrophysics Data System (ADS)

Deng, Chong

Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting second-order intensity function of spatial point processes. However, the original second-order quasi-likelihood is barely feasible due to the intense computation and high memory requirement needed to solve a large linear system. Motivated by the existence of geometric regular patterns in the stationary point processes, we find a lower dimension representation of the optimal weight function and propose a reduced second-order quasi-likelihood approach. Through a simulation study, we show that the proposed method not only demonstrates superior performance in fitting the clustering parameter but also merits in the relaxation of the constraint of the tuning parameter, H. Third, we studied the quasi-likelihood type estimating funciton that is optimal in a certain class of first-order estimating functions for estimating the regression parameter in spatial point process models. Then, by using a novel spectral representation, we construct an implementation that is computationally much more efficient and can be applied to more general setup than the original quasi-likelihood method.

Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences

PubMed Central

2018-01-01

Prediction of taxonomy for marker gene sequences such as 16S ribosomal RNA (rRNA) is a fundamental task in microbiology. Most experimentally observed sequences are diverged from reference sequences of authoritatively named organisms, creating a challenge for prediction methods. I assessed the accuracy of several algorithms using cross-validation by identity, a new benchmark strategy which explicitly models the variation in distances between query sequences and the closest entry in a reference database. When the accuracy of genus predictions was averaged over a representative range of identities with the reference database (100%, 99%, 97%, 95% and 90%), all tested methods had ≤50% accuracy on the currently-popular V4 region of 16S rRNA. Accuracy was found to fall rapidly with identity; for example, better methods were found to have V4 genus prediction accuracy of ∼100% at 100% identity but ∼50% at 97% identity. The relationship between identity and taxonomy was quantified as the probability that a rank is the lowest shared by a pair of sequences with a given pair-wise identity. With the V4 region, 95% identity was found to be a twilight zone where taxonomy is highly ambiguous because the probabilities that the lowest shared rank between pairs of sequences is genus, family, order or class are approximately equal. PMID:29682424

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.

Self-organization in a simple model of adaptive agents playing 2×2 games with arbitrary payoff matrices

NASA Astrophysics Data System (ADS)

Fort, H.; Viola, S.

2004-03-01

We analyze, both analytically and numerically, the self-organization of a system of “selfish” adaptive agents playing an arbitrary iterated pairwise game (defined by a 2×2 payoff matrix). Examples of possible games to play are the prisoner’s dilemma (PD) game, the chicken game, the hero game, etc. The agents have no memory, use strategies not based on direct reciprocity nor “tags” and are chosen at random, i.e., geographical vicinity is neglected. They can play two possible strategies: cooperate (C) or defect (D). The players measure their success by comparing their utilities with an estimate for the expected benefits and update their strategy following a simple rule. Two versions of the model are studied: (1) the deterministic version (the agents are either in definite states C or D) and (2) the stochastic version (the agents have a probability c of playing C). Using a general master equation we compute the equilibrium states into which the system self-organizes, characterized by their average probability of cooperation ceq. Depending on the payoff matrix, we show that ceq can take five different values. We also consider the mixing of agents using two different payoff matrices and show that any value of ceq can be reached by tuning the proportions of agents using each payoff matrix. In particular, this can be used as a way to simulate the effect of a fraction d of “antisocial” individuals—incapable of realizing any value to cooperation—on the cooperative regime hold by a population of neutral or “normal” agents.

Self-organization in a simple model of adaptive agents playing 2 x 2 games with arbitrary payoff matrices.

PubMed

Fort, H; Viola, S

2004-03-01

We analyze, both analytically and numerically, the self-organization of a system of "selfish" adaptive agents playing an arbitrary iterated pairwise game (defined by a 2 x 2 payoff matrix). Examples of possible games to play are the prisoner's dilemma (PD) game, the chicken game, the hero game, etc. The agents have no memory, use strategies not based on direct reciprocity nor "tags" and are chosen at random, i.e., geographical vicinity is neglected. They can play two possible strategies: cooperate (C) or defect (D). The players measure their success by comparing their utilities with an estimate for the expected benefits and update their strategy following a simple rule. Two versions of the model are studied: (1) the deterministic version (the agents are either in definite states C or D) and (2) the stochastic version (the agents have a probability c of playing C). Using a general master equation we compute the equilibrium states into which the system self-organizes, characterized by their average probability of cooperation c(eq). Depending on the payoff matrix, we show that c(eq) can take five different values. We also consider the mixing of agents using two different payoff matrices and show that any value of c(eq) can be reached by tuning the proportions of agents using each payoff matrix. In particular, this can be used as a way to simulate the effect of a fraction d of "antisocial" individuals--incapable of realizing any value to cooperation--on the cooperative regime hold by a population of neutral or "normal" agents.

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.

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

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.

Pairwise-interaction extended point-particle model for particle-laden flows

NASA Astrophysics Data System (ADS)

Akiki, G.; Moore, W. C.; Balachandar, S.

2017-12-01

In this work we consider the pairwise interaction extended point-particle (PIEP) model for Euler-Lagrange simulations of particle-laden flows. By accounting for the precise location of neighbors the PIEP model goes beyond local particle volume fraction, and distinguishes the influence of upstream, downstream and laterally located neighbors. The two main ingredients of the PIEP model are (i) the undisturbed flow at any particle is evaluated as a superposition of the macroscale flow and a microscale flow that is approximated as a pairwise superposition of perturbation fields induced by each of the neighboring particles, and (ii) the forces and torque on the particle are then calculated from the undisturbed flow using the Faxén form of the force relation. The computational efficiency of the standard Euler-Lagrange approach is retained, since the microscale perturbation fields induced by a neighbor are pre-computed and stored as PIEP maps. Here we extend the PIEP force model of Akiki et al. [3] with a corresponding torque model to systematically include the effect of perturbation fields induced by the neighbors in evaluating the net torque. Also, we use DNS results from a uniform flow over two stationary spheres to further improve the PIEP force and torque models. We then test the PIEP model in three different sedimentation problems and compare the results against corresponding DNS to assess the accuracy of the PIEP model and improvement over the standard point-particle approach. In the case of two sedimenting spheres in a quiescent ambient the PIEP model is shown to capture the drafting-kissing-tumbling process. In cases of 5 and 80 sedimenting spheres a good agreement is obtained between the PIEP simulation and the DNS. For all three simulations, the DEM-PIEP was able to recreate, to a good extent, the results from the DNS, while requiring only a negligible fraction of the numerical resources required by the fully-resolved DNS.

Spatial interactions of yarded White-tailed Deer, Odocoileus virginianus

USGS Publications Warehouse

Nelson, M.E.; Sargeant, G.A.

2008-01-01

We examined the spatial interactions of nine female White-tailed Deer (Odocoileus virginianus) in two deeryards (winter aggregations) in northeastern Minnesota during February-April 1999. Global positioning system (GPS) collars yielded seven pair-wise comparisons of deer that were located at the same time (???1 minute apart) and mat used overlapping areas. Deer traveled separately and did not associate with one another. Within overlapping areas, comparisons of distances between deer and distances between random locations indicated deer moved without regard to each other. Similarly, comparisons of observed and expected probabilities of deer using areas overlapping those of other deer also evinced that deer moved independently.

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.

Feature-based pairwise retinal image registration by radial distortion correction

NASA Astrophysics Data System (ADS)

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

2007-03-01

Fundus camera imaging is widely used to document disorders such as diabetic retinopathy and macular degeneration. Multiple retinal images can be combined together through a procedure known as mosaicing to form an image with a larger field of view. Mosaicing typically requires multiple pairwise registrations of partially overlapped images. We describe a new method for pairwise retinal image registration. The proposed method is unique in that the radial distortion due to image acquisition is corrected prior to the geometric transformation. Vessel lines are detected using the Hessian operator and are used as input features to the registration. Since the overlapping region is typically small in a retinal image pair, only a few correspondences are available, thus limiting the applicable model to an afine transform at best. To recover the distortion due to curved-surface of retina and lens optics, a combined approach of an afine model with a radial distortion correction is proposed. The parameters of the image acquisition and radial distortion models are estimated during an optimization step that uses Powell's method driven by the vessel line distance. Experimental results using 20 pairs of green channel images acquired from three subjects with a fundus camera confirmed that the afine model with distortion correction could register retinal image pairs to within 1.88+/-0.35 pixels accuracy (mean +/- standard deviation) assessed by vessel line error, which is 17% better than the afine-only approach. Because the proposed method needs only two correspondences, it can be applied to obtain good registration accuracy even in the case of small overlap between retinal image pairs.

EGFR oligomerization organizes kinase-active dimers into competent signalling platforms

PubMed Central

Needham, Sarah R.; Roberts, Selene K.; Arkhipov, Anton; Mysore, Venkatesh P.; Tynan, Christopher J.; Zanetti-Domingues, Laura C.; Kim, Eric T.; Losasso, Valeria; Korovesis, Dimitrios; Hirsch, Michael; Rolfe, Daniel J.; Clarke, David T.; Winn, Martyn D.; Lajevardipour, Alireza; Clayton, Andrew H. A.; Pike, Linda J.; Perani, Michela; Parker, Peter J.; Shan, Yibing; Shaw, David E.; Martin-Fernandez, Marisa L.

2016-01-01

Epidermal growth factor receptor (EGFR) signalling is activated by ligand-induced receptor dimerization. Notably, ligand binding also induces EGFR oligomerization, but the structures and functions of the oligomers are poorly understood. Here, we use fluorophore localization imaging with photobleaching to probe the structure of EGFR oligomers. We find that at physiological epidermal growth factor (EGF) concentrations, EGFR assembles into oligomers, as indicated by pairwise distances of receptor-bound fluorophore-conjugated EGF ligands. The pairwise ligand distances correspond well with the predictions of our structural model of the oligomers constructed from molecular dynamics simulations. The model suggests that oligomerization is mediated extracellularly by unoccupied ligand-binding sites and that oligomerization organizes kinase-active dimers in ways optimal for auto-phosphorylation in trans between neighbouring dimers. We argue that ligand-induced oligomerization is essential to the regulation of EGFR signalling. PMID:27796308

Learning Maximal Entropy Models from finite size datasets: a fast Data-Driven algorithm allows to sample from the posterior distribution

NASA Astrophysics Data System (ADS)

Ferrari, Ulisse

A maximal entropy model provides the least constrained probability distribution that reproduces experimental averages of an observables set. In this work we characterize the learning dynamics that maximizes the log-likelihood in the case of large but finite datasets. We first show how the steepest descent dynamics is not optimal as it is slowed down by the inhomogeneous curvature of the model parameters space. We then provide a way for rectifying this space which relies only on dataset properties and does not require large computational efforts. We conclude by solving the long-time limit of the parameters dynamics including the randomness generated by the systematic use of Gibbs sampling. In this stochastic framework, rather than converging to a fixed point, the dynamics reaches a stationary distribution, which for the rectified dynamics reproduces the posterior distribution of the parameters. We sum up all these insights in a ``rectified'' Data-Driven algorithm that is fast and by sampling from the parameters posterior avoids both under- and over-fitting along all the directions of the parameters space. Through the learning of pairwise Ising models from the recording of a large population of retina neurons, we show how our algorithm outperforms the steepest descent method. This research was supported by a Grant from the Human Brain Project (HBP CLAP).

An Extension of Dominance Analysis to Canonical Correlation Analysis

ERIC Educational Resources Information Center

Huo, Yan; Budescu, David V.

2009-01-01

Dominance analysis (Budescu, 1993) offers a general framework for determination of relative importance of predictors in univariate and multivariate multiple regression models. This approach relies on pairwise comparisons of the contribution of predictors in all relevant subset models. In this article we extend dominance analysis to canonical…

A Hybrid Physics-Based Data-Driven Approach for Point-Particle Force Modeling

NASA Astrophysics Data System (ADS)

Moore, Chandler; Akiki, Georges; Balachandar, S.

2017-11-01

This study improves upon the physics-based pairwise interaction extended point-particle (PIEP) model. The PIEP model leverages a physical framework to predict fluid mediated interactions between solid particles. While the PIEP model is a powerful tool, its pairwise assumption leads to increased error in flows with high particle volume fractions. To reduce this error, a regression algorithm is used to model the differences between the current PIEP model's predictions and the results of direct numerical simulations (DNS) for an array of monodisperse solid particles subjected to various flow conditions. The resulting statistical model and the physical PIEP model are superimposed to construct a hybrid, physics-based data-driven PIEP model. It must be noted that the performance of a pure data-driven approach without the model-form provided by the physical PIEP model is substantially inferior. The hybrid model's predictive capabilities are analyzed using more DNS. In every case tested, the hybrid PIEP model's prediction are more accurate than those of physical PIEP model. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-1315138 and the U.S. DOE, NNSA, ASC Program, as a Cooperative Agreement under Contract No. DE-NA0002378.

A Scalar Product Model for the Multidimensional Scaling of Choice

ERIC Educational Resources Information Center

Bechtel, Gordon G.; And Others

1971-01-01

Contains a solution for the multidimensional scaling of pairwise choice when individuals are represented as dimensional weights. The analysis supplies an exact least squares solution and estimates of group unscalability parameters. (DG)

Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

PubMed

van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

2014-03-01

For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (< 3 km), we calculated several measures of landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

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.

Exact calculation of distributions on integers, with application to sequence alignment.

PubMed

Newberg, Lee A; Lawrence, Charles E

2009-01-01

Computational biology is replete with high-dimensional discrete prediction and inference problems. Dynamic programming recursions can be applied to several of the most important of these, including sequence alignment, RNA secondary-structure prediction, phylogenetic inference, and motif finding. In these problems, attention is frequently focused on some scalar quantity of interest, a score, such as an alignment score or the free energy of an RNA secondary structure. In many cases, score is naturally defined on integers, such as a count of the number of pairing differences between two sequence alignments, or else an integer score has been adopted for computational reasons, such as in the test of significance of motif scores. The probability distribution of the score under an appropriate probabilistic model is of interest, such as in tests of significance of motif scores, or in calculation of Bayesian confidence limits around an alignment. Here we present three algorithms for calculating the exact distribution of a score of this type; then, in the context of pairwise local sequence alignments, we apply the approach so as to find the alignment score distribution and Bayesian confidence limits.

Acrocentric chromosome associations in man.

PubMed Central

Jacobs, P A; Mayer, M; Morton, N E

1976-01-01

Heterogeneity among chromosomes was found to be a highly significant source of variation for association proportions, while culture, slide, and observer were negligible sources of variation for association proportions although important for numbers of associations. The consequences of these results for tests of group differences are discussed. It seems evident that each pair of acrocentric chromosomes has its own characteristic probability of entering into association. This is presumably a combination of the probability for each individual member of the pair, a proposition easily tested utilizing acrocentric chromosomes carrying polymorphisms which allow each member of the pair to be individually recognized. A mathematical theory for pairwise satellite association was developed and shown to fit observations on banded chromosomes. While we found very significant heterogeneity among individuals in the frequency with which different chromosomes entered into associations, there was no significant evidence for preferential association between any particular chromosomes, either heterologous or homologous. This finding in our material of apparently random associations between different chromosomes is contrary to claims made by other investigators and should be tested on other material. No correlation was found between the phenotype of the chromosome, as judged by cytogenetic polymorphisms, and its probability of association. PMID:795295

Communicating with sentences: A multi-word naming game model

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong; Hu, Jianwei

2018-01-01

Naming game simulates the process of naming an object by a single word, in which a population of communicating agents can reach global consensus asymptotically through iteratively pair-wise conversations. We propose an extension of the single-word model to a multi-word naming game (MWNG), simulating the case of describing a complex object by a sentence (multiple words). Words are defined in categories, and then organized as sentences by combining them from different categories. We refer to a formatted combination of several words as a pattern. In such an MWNG, through a pair-wise conversation, it requires the hearer to achieve consensus with the speaker with respect to both every single word in the sentence as well as the sentence pattern, so as to guarantee the correct meaning of the saying; otherwise, they fail reaching consensus in the interaction. We validate the model in three typical topologies as the underlying communication network, and employ both conventional and man-designed patterns in performing the MWNG.

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.

Multiple graph regularized protein domain ranking

PubMed Central

2012-01-01

Background 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. Results 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. Conclusion 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. PMID:23157331

Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

USGS Publications Warehouse

Row, Jeffrey R.; Knick, Steven T.; Oyler-McCance, Sara J.; Lougheed, Stephen C.; Fedy, Bradley C.

2017-01-01

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

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.

An Analytic Hierarchy Process for School Quality and Inspection: Model Development and Application

ERIC Educational Resources Information Center

Al Qubaisi, Amal; Badri, Masood; Mohaidat, Jihad; Al Dhaheri, Hamad; Yang, Guang; Al Rashedi, Asma; Greer, Kenneth

2016-01-01

Purpose: The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections. Design/methodology/approach: The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the…

Impact of Missing Data on Person-Model Fit and Person Trait Estimation

ERIC Educational Resources Information Center

Zhang, Bo; Walker, Cindy M.

2008-01-01

The purpose of this research was to examine the effects of missing data on person-model fit and person trait estimation in tests with dichotomous items. Under the missing-completely-at-random framework, four missing data treatment techniques were investigated including pairwise deletion, coding missing responses as incorrect, hotdeck imputation,…

Whole Protein Native Fitness Potentials

NASA Astrophysics Data System (ADS)

Faraggi, Eshel; Kloczkowski, Andrzej

2013-03-01

Protein structure prediction can be separated into two tasks: sample the configuration space of the protein chain, and assign a fitness between these hypothetical models and the native structure of the protein. One of the more promising developments in this area is that of knowledge based energy functions. However, standard approaches using pair-wise interactions have shown shortcomings demonstrated by the superiority of multi-body-potentials. These shortcomings are due to residue pair-wise interaction being dependent on other residues along the chain. We developed a method that uses whole protein information filtered through machine learners to score protein models based on their likeness to native structures. For all models we calculated parameters associated with the distance to the solvent and with distances between residues. These parameters, in addition to energy estimates obtained by using a four-body-potential, DFIRE, and RWPlus were used as training for machine learners to predict the fitness of the models. Testing on CASP 9 targets showed that our method is superior to DFIRE, RWPlus, and the four-body potential, which are considered standards in the field.

Predicting community composition from pairwise interactions

NASA Astrophysics Data System (ADS)

Friedman, Jonathan; Higgins, Logan; Gore, Jeff

The ability to predict the structure of complex, multispecies communities is crucial for understanding the impact of species extinction and invasion on natural communities, as well as for engineering novel, synthetic communities. Communities are often modeled using phenomenological models, such as the classical generalized Lotka-Volterra (gLV) model. While a lot of our intuition comes from such models, their predictive power has rarely been tested experimentally. To directly assess the predictive power of this approach, we constructed synthetic communities comprised of up to 8 soil bacteria. We measured the outcome of competition between all species pairs, and used these measurements to predict the composition of communities composed of more than 2 species. The pairwise competitions resulted in a diverse set of outcomes, including coexistence, exclusion, and bistability, and displayed evidence for both interference and facilitation. Most pair outcomes could be captured by the gLV framework, and the composition of multispecies communities could be predicted for communities composed solely of such pairs. Our results demonstrate the predictive ability and utility of simple phenomenology, which enables accurate predictions in the absence of mechanistic details.

Galaxy and Mass Assembly (GAMA): small-scale anisotropic galaxy clustering and the pairwise velocity dispersion of galaxies

NASA Astrophysics Data System (ADS)

Loveday, J.; Christodoulou, L.; Norberg, P.; Peacock, J. A.; Baldry, I. K.; Bland-Hawthorn, J.; Brown, M. J. I.; Colless, M.; Driver, S. P.; Holwerda, B. W.; Hopkins, A. M.; Kafle, P. R.; Liske, J.; Lopez-Sanchez, A. R.; Taylor, E. N.

2018-03-01

The galaxy pairwise velocity dispersion (PVD) can provide important tests of non-standard gravity and galaxy formation models. We describe measurements of the PVD of galaxies in the Galaxy and Mass Assembly (GAMA) survey as a function of projected separation and galaxy luminosity. Due to the faint magnitude limit (r < 19.8) and highly complete spectroscopic sampling of the GAMA survey, we are able to reliably measure the PVD to smaller scales (r⊥ = 0.01 h - 1 Mpc) than previous work. The measured PVD at projected separations r⊥ ≲ 1 h - 1 Mpc increases near monotonically with increasing luminosity from σ12 ≈ 200 km s - 1 at Mr = -17 mag to σ12 ≈ 600 km s - 1 at Mr ≈ -22 mag. Analysis of the Gonzalez-Perez et al. (2014) GALFORM semi-analytic model yields no such trend of PVD with luminosity: the model overpredicts the PVD for faint galaxies. This is most likely a result of the model placing too many low-luminosity galaxies in massive haloes.

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.

Long-term reduction of health care costs & utilization after epilepsy surgery

PubMed Central

Schiltz, Nicholas K.; Kaiboriboon, Kitti; Koroukian, Siran M.; Singer, Mendel E.; Love, Thomas E.

2015-01-01

SUMMARY Objective To assess long-term direct medical costs, health care utilization, and mortality following resective surgery in persons with uncontrolled epilepsy. Methods Retrospective longitudinal cohort study of Medicaid beneficiaries with epilepsy from 2000 - 2008. The study population included 7,835 persons with uncontrolled focal epilepsy age 18 to 64 years, with an average follow-up time of 5 years. Of these, 135 received surgery during the study period. To account for selection bias, we used risk-set optimal pairwise matching on a time-varying propensity score, and inverse probability of treatment weighting. Repeated measures generalized linear models were used to model utilization and cost outcomes. Cox proportional hazard was used to model survival. Results The mean direct medical cost difference between the surgical group and control group was $6,806 after risk-set matching. The incidence rate ratio of inpatient, emergency room, and outpatient utilization was lower among the surgical group in both unadjusted and adjusted analyses. There was no significant difference in mortality after adjustment. Among surgical cases, mean annual costs per subject were on average $6,484 lower, and all utilization measures were lower after surgery compared to before. Significance Subjects that underwent epilepsy surgery had lower direct medical care costs and health care utilization. These findings support that epilepsy surgery yield substantial health care cost savings. PMID:26693701

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

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…

Pharmacological treatments in asthma-affected horses: A pair-wise and network meta-analysis.

PubMed

Calzetta, L; Roncada, P; di Cave, D; Bonizzi, L; Urbani, A; Pistocchini, E; Rogliani, P; Matera, M G

2017-11-01

Equine asthma is a disease characterised by reversible airflow obstruction, bronchial hyper-responsiveness and airway inflammation following exposure of susceptible horses to specific airborne agents. Although clinical remission can be achieved in a low-airborne dust environment, repeated exacerbations may lead to irreversible airway remodelling. The available data on the pharmacotherapy of equine asthma result from several small studies, and no head-to-head clinical trials have been conducted among the available medications. To assess the impact of the pharmacological interventions in equine asthma and compare the effect of different classes of drugs on lung function. Pair-wise and network meta-analysis. Literature searches for clinical trials on the pharmacotherapy of equine asthma were performed. The risk of publication bias was assessed by funnel plots and Egger's test. Changes in maximum transpulmonary or pleural pressure, pulmonary resistance and dynamic lung compliance vs. control were analysed via random-effects models and Bayesian networks. The results obtained from 319 equine asthma-affected horses were extracted from 32 studies. Bronchodilators, corticosteroids and chromones improved maximum transpulmonary or pleural pressure (range: -8.0 to -21.4 cmH 2 O; P<0.001). Bronchodilators, corticosteroids and furosemide reduced pulmonary resistance (range: -1.2 to -1.9 cmH 2 O/L/s; P<0.001), and weakly increased dynamic lung compliance. Inhaled β 2 -adrenoreceptor (β 2 -AR) agonists and inhaled corticosteroids had the highest probability of being the best therapies. Long-term treatments were more effective than short-term treatments. Weak publication bias was detected. This study demonstrates that long-term treatments with inhaled corticosteroids and long-acting β 2 -AR agonists may represent the first choice for treating equine asthma. Further high quality clinical trials are needed to clarify whether inhaled bronchodilators should be preferred to inhaled corticosteroids or vice versa, and to investigate the potential superiority of combination therapy in equine asthma. © 2017 EVJ Ltd.

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.

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

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.

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.

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

Detecting Earthquakes over a Seismic Network using Single-Station Similarity Measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-03-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected move-out. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to two weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalog (including 95% of the catalog events), and less than 1% of these candidate events are false detections.

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.

Elucidating the multiple genetic lineages and population genetic structure of the brooding coral Seriatopora (Scleractinia: Pocilloporidae) in the Ryukyu Archipelago

NASA Astrophysics Data System (ADS)

Nakajima, Yuichi; Nishikawa, Akira; Iguchi, Akira; Nagata, Tomofumi; Uyeno, Daisuke; Sakai, Kazuhiko; Mitarai, Satoshi

2017-06-01

The elucidation of species diversity and connectivity is essential for conserving coral reef communities and for understanding the characteristics of coral populations. To assess the species diversity, intraspecific genetic diversity, and genetic differentiation among populations of the brooding coral Seriatopora spp., we conducted phylogenetic and population genetic analyses using a mitochondrial DNA control region and microsatellites at ten sites in the Ryukyu Archipelago, Japan. At least three genetic lineages of Seriatopora (Seriatopora-A, -B, and -C) were detected in our specimens. We collected colonies morphologically similar to Seriatopora hystrix, but these may have included multiple, genetically distinct species. Although sexual reproduction maintains the populations of all the genetic lineages, Seriatopora-A and Seriatopora-C had lower genetic diversity than Seriatopora-B. We detected significant genetic differentiation in Seriatopora-B among the three populations as follows: pairwise F ST = 0.064-0.116 (all P = 0.001), pairwise G''ST = 0.107-0.209 (all P = 0.001). Additionally, only one migrant from an unsampled population was genetically identified within Seriatopora-B. Because the peak of the settlement of Seriatopora larvae is within 1 d and almost all larvae are settled within 5 d of spawning, our observations may be related to low dispersal ability. Populations of Seriatopora in the Ryukyu Archipelago will probably not recover unless there is substantial new recruitment from distant populations.

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.

Estimating parameters for probabilistic linkage of privacy-preserved datasets.

PubMed

Brown, Adrian P; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Boyd, James H

2017-07-10

Probabilistic record linkage is a process used to bring together person-based records from within the same dataset (de-duplication) or from disparate datasets using pairwise comparisons and matching probabilities. The linkage strategy and associated match probabilities are often estimated through investigations into data quality and manual inspection. However, as privacy-preserved datasets comprise encrypted data, such methods are not possible. In this paper, we present a method for estimating the probabilities and threshold values for probabilistic privacy-preserved record linkage using Bloom filters. Our method was tested through a simulation study using synthetic data, followed by an application using real-world administrative data. Synthetic datasets were generated with error rates from zero to 20% error. Our method was used to estimate parameters (probabilities and thresholds) for de-duplication linkages. Linkage quality was determined by F-measure. Each dataset was privacy-preserved using separate Bloom filters for each field. Match probabilities were estimated using the expectation-maximisation (EM) algorithm on the privacy-preserved data. Threshold cut-off values were determined by an extension to the EM algorithm allowing linkage quality to be estimated for each possible threshold. De-duplication linkages of each privacy-preserved dataset were performed using both estimated and calculated probabilities. Linkage quality using the F-measure at the estimated threshold values was also compared to the highest F-measure. Three large administrative datasets were used to demonstrate the applicability of the probability and threshold estimation technique on real-world data. Linkage of the synthetic datasets using the estimated probabilities produced an F-measure that was comparable to the F-measure using calculated probabilities, even with up to 20% error. Linkage of the administrative datasets using estimated probabilities produced an F-measure that was higher than the F-measure using calculated probabilities. Further, the threshold estimation yielded results for F-measure that were only slightly below the highest possible for those probabilities. The method appears highly accurate across a spectrum of datasets with varying degrees of error. As there are few alternatives for parameter estimation, the approach is a major step towards providing a complete operational approach for probabilistic linkage of privacy-preserved datasets.

Modelling particles moving in a potential field with pairwise interactions and an application

Treesearch

D. R. Brillinger; Haiganoush Preisler; M. J. Wisdom

2011-01-01

Motions of particles in fields characterized by real-valued potential functions, are considered. Three particular expressions for potential functions are studied. One, U, depends on the ith particle’s location, ri(t) at times t

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.

Characterization of demographic expansions from pairwise comparisons of linked microsatellite haplotypes.

PubMed

Navascués, Miguel; Hardy, Olivier J; Burgarella, Concetta

2009-03-01

This work extends the methods of demographic inference based on the distribution of pairwise genetic differences between individuals (mismatch distribution) to the case of linked microsatellite data. Population genetics theory describes the distribution of mutations among a sample of genes under different demographic scenarios. However, the actual number of mutations can rarely be deduced from DNA polymorphisms. The inclusion of mutation models in theoretical predictions can improve the performance of statistical methods. We have developed a maximum-pseudolikelihood estimator for the parameters that characterize a demographic expansion for a series of linked loci evolving under a stepwise mutation model. Those loci would correspond to DNA polymorphisms of linked microsatellites (such as those found on the Y chromosome or the chloroplast genome). The proposed method was evaluated with simulated data sets and with a data set of chloroplast microsatellites that showed signal for demographic expansion in a previous study. The results show that inclusion of a mutational model in the analysis improves the estimates of the age of expansion in the case of older expansions.

Comparing methods for modelling spreading cell fronts.

PubMed

Markham, Deborah C; Simpson, Matthew J; Maini, Philip K; Gaffney, Eamonn A; Baker, Ruth E

2014-07-21

Spreading cell fronts play an essential role in many physiological processes. Classically, models of this process are based on the Fisher-Kolmogorov equation; however, such continuum representations are not always suitable as they do not explicitly represent behaviour at the level of individual cells. Additionally, many models examine only the large time asymptotic behaviour, where a travelling wave front with a constant speed has been established. Many experiments, such as a scratch assay, never display this asymptotic behaviour, and in these cases the transient behaviour must be taken into account. We examine the transient and the asymptotic behaviour of moving cell fronts using techniques that go beyond the continuum approximation via a volume-excluding birth-migration process on a regular one-dimensional lattice. We approximate the averaged discrete results using three methods: (i) mean-field, (ii) pair-wise, and (iii) one-hole approximations. We discuss the performance of these methods, in comparison to the averaged discrete results, for a range of parameter space, examining both the transient and asymptotic behaviours. The one-hole approximation, based on techniques from statistical physics, is not capable of predicting transient behaviour but provides excellent agreement with the asymptotic behaviour of the averaged discrete results, provided that cells are proliferating fast enough relative to their rate of migration. The mean-field and pair-wise approximations give indistinguishable asymptotic results, which agree with the averaged discrete results when cells are migrating much more rapidly than they are proliferating. The pair-wise approximation performs better in the transient region than does the mean-field, despite having the same asymptotic behaviour. Our results show that each approximation only works in specific situations, thus we must be careful to use a suitable approximation for a given system, otherwise inaccurate predictions could be made. Copyright © 2014 Elsevier Ltd. All rights reserved.

Intercenter Differences in Bronchopulmonary Dysplasia or Death Among Very Low Birth Weight Infants

PubMed Central

Walsh, Michele; Bobashev, Georgiy; Das, Abhik; Levine, Burton; Carlo, Waldemar A.; Higgins, Rosemary D.

2011-01-01

OBJECTIVES: To determine (1) the magnitude of clustering of bronchopulmonary dysplasia (36 weeks) or death (the outcome) across centers of the Eunice Kennedy Shriver National Institute of Child and Human Development National Research Network, (2) the infant-level variables associated with the outcome and estimate their clustering, and (3) the center-specific practices associated with the differences and build predictive models. METHODS: Data on neonates with a birth weight of <1250 g from the cluster-randomized benchmarking trial were used to determine the magnitude of clustering of the outcome according to alternating logistic regression by using pairwise odds ratio and predictive modeling. Clinical variables associated with the outcome were identified by using multivariate analysis. The magnitude of clustering was then evaluated after correction for infant-level variables. Predictive models were developed by using center-specific and infant-level variables for data from 2001 2004 and projected to 2006. RESULTS: In 2001–2004, clustering of bronchopulmonary dysplasia/death was significant (pairwise odds ratio: 1.3; P < .001) and increased in 2006 (pairwise odds ratio: 1.6; overall incidence: 52%; range across centers: 32%–74%); center rates were relatively stable over time. Variables that varied according to center and were associated with increased risk of outcome included lower body temperature at NICU admission, use of prophylactic indomethacin, specific drug therapy on day 1, and lack of endotracheal intubation. Center differences remained significant even after correction for clustered variables. CONCLUSION: Bronchopulmonary dysplasia/death rates demonstrated moderate clustering according to center. Clinical variables associated with the outcome were also clustered. Center differences after correction of clustered variables indicate presence of as-yet unmeasured center variables. PMID:21149431

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.

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.

The Gaussian streaming model and convolution Lagrangian effective field theory

DOE PAGES

Vlah, Zvonimir; Castorina, Emanuele; White, Martin

2016-12-05

We update the ingredients of the Gaussian streaming model (GSM) for the redshift-space clustering of biased tracers using the techniques of Lagrangian perturbation theory, effective field theory (EFT) and a generalized Lagrangian bias expansion. After relating the GSM to the cumulant expansion, we present new results for the real-space correlation function, mean pairwise velocity and pairwise velocity dispersion including counter terms from EFT and bias terms through third order in the linear density, its leading derivatives and its shear up to second order. We discuss the connection to the Gaussian peaks formalism. We compare the ingredients of the GSM tomore » a suite of large N-body simulations, and show the performance of the theory on the low order multipoles of the redshift-space correlation function and power spectrum. We highlight the importance of a general biasing scheme, which we find to be as important as higher-order corrections due to non-linear evolution for the halos we consider on the scales of interest to us.« less

Collective memory in primate conflict implied by temporal scaling collapse.

PubMed

Lee, Edward D; Daniels, Bryan C; Krakauer, David C; Flack, Jessica C

2017-09-01

In biological systems, prolonged conflict is costly, whereas contained conflict permits strategic innovation and refinement. Causes of variation in conflict size and duration are not well understood. We use a well-studied primate society model system to study how conflicts grow. We find conflict duration is a 'first to fight' growth process that scales superlinearly, with the number of possible pairwise interactions. This is in contrast with a 'first to fail' process that characterizes peaceful durations. Rescaling conflict distributions reveals a universal curve, showing that the typical time scale of correlated interactions exceeds nearly all individual fights. This temporal correlation implies collective memory across pairwise interactions beyond those assumed in standard models of contagion growth or iterated evolutionary games. By accounting for memory, we make quantitative predictions for interventions that mitigate or enhance the spread of conflict. Managing conflict involves balancing the efficient use of limited resources with an intervention strategy that allows for conflict while keeping it contained and controlled. © 2017 The Author(s).

The Gaussian streaming model and convolution Lagrangian effective field theory

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

Vlah, Zvonimir; Castorina, Emanuele; White, Martin, E-mail: zvlah@stanford.edu, E-mail: ecastorina@berkeley.edu, E-mail: mwhite@berkeley.edu

We update the ingredients of the Gaussian streaming model (GSM) for the redshift-space clustering of biased tracers using the techniques of Lagrangian perturbation theory, effective field theory (EFT) and a generalized Lagrangian bias expansion. After relating the GSM to the cumulant expansion, we present new results for the real-space correlation function, mean pairwise velocity and pairwise velocity dispersion including counter terms from EFT and bias terms through third order in the linear density, its leading derivatives and its shear up to second order. We discuss the connection to the Gaussian peaks formalism. We compare the ingredients of the GSM tomore » a suite of large N-body simulations, and show the performance of the theory on the low order multipoles of the redshift-space correlation function and power spectrum. We highlight the importance of a general biasing scheme, which we find to be as important as higher-order corrections due to non-linear evolution for the halos we consider on the scales of interest to us.« less

Generalized priority-queue network dynamics: Impact of team and hierarchy

NASA Astrophysics Data System (ADS)

Cho, Won-Kuk; Min, Byungjoon; Goh, K.-I.; Kim, I.-M.

2010-06-01

We study the effect of team and hierarchy on the waiting-time dynamics of priority-queue networks. To this end, we introduce generalized priority-queue network models incorporating interaction rules based on team-execution and hierarchy in decision making, respectively. It is numerically found that the waiting-time distribution exhibits a power law for long waiting times in both cases, yet with different exponents depending on the team size and the position of queue nodes in the hierarchy, respectively. The observed power-law behaviors have in many cases a corresponding single or pairwise-interacting queue dynamics, suggesting that the pairwise interaction may constitute a major dynamic consequence in the priority-queue networks. It is also found that the reciprocity of influence is a relevant factor for the priority-queue network dynamics.

Plus Disease in Retinopathy of Prematurity: Improving Diagnosis by Ranking Disease Severity and Using Quantitative Image Analysis.

PubMed

Kalpathy-Cramer, Jayashree; Campbell, J Peter; Erdogmus, Deniz; Tian, Peng; Kedarisetti, Dharanish; Moleta, Chace; Reynolds, James D; Hutcheson, Kelly; Shapiro, Michael J; Repka, Michael X; Ferrone, Philip; Drenser, Kimberly; Horowitz, Jason; Sonmez, Kemal; Swan, Ryan; Ostmo, Susan; Jonas, Karyn E; Chan, R V Paul; Chiang, Michael F

2016-11-01

To determine expert agreement on relative retinopathy of prematurity (ROP) disease severity and whether computer-based image analysis can model relative disease severity, and to propose consideration of a more continuous severity score for ROP. We developed 2 databases of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP (i-ROP) cohort study and recruited expert physician, nonexpert physician, and nonphysician graders to classify and perform pairwise comparisons on both databases. Six participating expert ROP clinician-scientists, each with a minimum of 10 years of clinical ROP experience and 5 ROP publications, and 5 image graders (3 physicians and 2 nonphysician graders) who analyzed images that were obtained during routine ROP screening in neonatal intensive care units. Images in both databases were ranked by average disease classification (classification ranking), by pairwise comparison using the Elo rating method (comparison ranking), and by correlation with the i-ROP computer-based image analysis system. Interexpert agreement (weighted κ statistic) compared with the correlation coefficient (CC) between experts on pairwise comparisons and correlation between expert rankings and computer-based image analysis modeling. There was variable interexpert agreement on diagnostic classification of disease (plus, preplus, or normal) among the 6 experts (mean weighted κ, 0.27; range, 0.06-0.63), but good correlation between experts on comparison ranking of disease severity (mean CC, 0.84; range, 0.74-0.93) on the set of 34 images. Comparison ranking provided a severity ranking that was in good agreement with ranking obtained by classification ranking (CC, 0.92). Comparison ranking on the larger dataset by both expert and nonexpert graders demonstrated good correlation (mean CC, 0.97; range, 0.95-0.98). The i-ROP system was able to model this continuous severity with good correlation (CC, 0.86). Experts diagnose plus disease on a continuum, with poor absolute agreement on classification but good relative agreement on disease severity. These results suggest that the use of pairwise rankings and a continuous severity score, such as that provided by the i-ROP system, may improve agreement on disease severity in the future. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

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

Correlated Fluctuations in Strongly Coupled Binary Networks Beyond Equilibrium

NASA Astrophysics Data System (ADS)

Dahmen, David; Bos, Hannah; Helias, Moritz

2016-07-01

Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering glassy magnetism and frustration, combinatorial optimization, protein folding, stock market dynamics, and social dynamics. The phase diagram of these systems is obtained in the thermodynamic limit by averaging over the quenched randomness of the couplings. However, many applications require the statistics of activity for a single realization of the possibly asymmetric couplings in finite-sized networks. Examples include reconstruction of couplings from the observed dynamics, representation of probability distributions for sampling-based inference, and learning in the central nervous system based on the dynamic and correlation-dependent modification of synaptic connections. The systematic cumulant expansion for kinetic binary (Ising) threshold units with strong, random, and asymmetric couplings presented here goes beyond mean-field theory and is applicable outside thermodynamic equilibrium; a system of approximate nonlinear equations predicts average activities and pairwise covariances in quantitative agreement with full simulations down to hundreds of units. The linearized theory yields an expansion of the correlation and response functions in collective eigenmodes, leads to an efficient algorithm solving the inverse problem, and shows that correlations are invariant under scaling of the interaction strengths.

Competitive Abilities in Experimental Microcosms Are Accurately Predicted by a Demographic Index for R*

PubMed Central

Murrell, Ebony G.; Juliano, Steven A.

2012-01-01

Resource competition theory predicts that R*, the equilibrium resource amount yielding zero growth of a consumer population, should predict species' competitive abilities for that resource. This concept has been supported for unicellular organisms, but has not been well-tested for metazoans, probably due to the difficulty of raising experimental populations to equilibrium and measuring population growth rates for species with long or complex life cycles. We developed an index (Rindex) of R* based on demography of one insect cohort, growing from egg to adult in a non-equilibrium setting, and tested whether Rindex yielded accurate predictions of competitive abilities using mosquitoes as a model system. We estimated finite rate of increase (λ′) from demographic data for cohorts of three mosquito species raised with different detritus amounts, and estimated each species' Rindex using nonlinear regressions of λ′ vs. initial detritus amount. All three species' Rindex differed significantly, and accurately predicted competitive hierarchy of the species determined in simultaneous pairwise competition experiments. Our Rindex could provide estimates and rigorous statistical comparisons of competitive ability for organisms for which typical chemostat methods and equilibrium population conditions are impractical. PMID:22970128

Particle Filter with State Permutations for Solving Image Jigsaw Puzzles

PubMed Central

Yang, Xingwei; Adluru, Nagesh; Latecki, Longin Jan

2016-01-01

We deal with an image jigsaw puzzle problem, which is defined as reconstructing an image from a set of square and non-overlapping image patches. It is known that a general instance of this problem is NP-complete, and it is also challenging for humans, since in the considered setting the original image is not given. Recently a graphical model has been proposed to solve this and related problems. The target label probability function is then maximized using loopy belief propagation. We also formulate the problem as maximizing a label probability function and use exactly the same pairwise potentials. Our main contribution is a novel inference approach in the sampling framework of Particle Filter (PF). Usually in the PF framework it is assumed that the observations arrive sequentially, e.g., the observations are naturally ordered by their time stamps in the tracking scenario. Based on this assumption, the posterior density over the corresponding hidden states is estimated. In the jigsaw puzzle problem all observations (puzzle pieces) are given at once without any particular order. Therefore, we relax the assumption of having ordered observations and extend the PF framework to estimate the posterior density by exploring different orders of observations and selecting the most informative permutations of observations. This significantly broadens the scope of applications of the PF inference. Our experimental results demonstrate that the proposed inference framework significantly outperforms the loopy belief propagation in solving the image jigsaw puzzle problem. In particular, the extended PF inference triples the accuracy of the label assignment compared to that using loopy belief propagation. PMID:27795660

Query-seeded iterative sequence similarity searching improves selectivity 5–20-fold

PubMed Central

Li, Weizhong; Lopez, Rodrigo

2017-01-01

Abstract Iterative similarity search programs, like psiblast, jackhmmer, and psisearch, are much more sensitive than pairwise similarity search methods like blast and ssearch because they build a position specific scoring model (a PSSM or HMM) that captures the pattern of sequence conservation characteristic to a protein family. But models are subject to contamination; once an unrelated sequence has been added to the model, homologs of the unrelated sequence will also produce high scores, and the model can diverge from the original protein family. Examination of alignment errors during psiblast PSSM contamination suggested a simple strategy for dramatically reducing PSSM contamination. psiblast PSSMs are built from the query-based multiple sequence alignment (MSA) implied by the pairwise alignments between the query model (PSSM, HMM) and the subject sequences in the library. When the original query sequence residues are inserted into gapped positions in the aligned subject sequence, the resulting PSSM rarely produces alignment over-extensions or alignments to unrelated sequences. This simple step, which tends to anchor the PSSM to the original query sequence and slightly increase target percent identity, can reduce the frequency of false-positive alignments more than 20-fold compared with psiblast and jackhmmer, with little loss in search sensitivity. PMID:27923999

Identification of landscape features influencing gene flow: How useful are habitat selection models?

USGS Publications Warehouse

Roffler, Gretchen H.; Schwartz, Michael K.; Pilgrim, Kristy L.; Talbot, Sandra L.; Sage, Kevin; Adams, Layne G.; Luikart, Gordon

2016-01-01

Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modeling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is important to consider explicit assumptions and spatial scales of measurement. We calculated pairwise genetic distance among 301 Dall's sheep (Ovis dalli dalli) in southcentral Alaska using an intensive noninvasive sampling effort and 15 microsatellite loci. We used multiple regression of distance matrices to assess the correlation of pairwise genetic distance and landscape resistance derived from an RSF, and combinations of landscape features hypothesized to influence dispersal. Dall's sheep gene flow was positively correlated with steep slopes, moderate peak normalized difference vegetation indices (NDVI), and open land cover. Whereas RSF covariates were significant in predicting genetic distance, the RSF model itself was not significantly correlated with Dall's sheep gene flow, suggesting that certain habitat features important during summer (rugged terrain, mid-range elevation) were not influential to effective dispersal. This work underscores that consideration of both habitat selection and landscape genetics models may be useful in developing management strategies to both meet the immediate survival of a species and allow for long-term genetic connectivity.

A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.

PubMed

Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2018-06-12

Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.

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

Detecting earthquakes over a seismic network using single-station similarity measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-06-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected moveout. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to 2 weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalogue (including 95 per cent of the catalogue events), and less than 1 per cent of these candidate events are false detections.

Performance analysis of model based iterative reconstruction with dictionary learning in transportation security CT

NASA Astrophysics Data System (ADS)

Haneda, Eri; Luo, Jiajia; Can, Ali; Ramani, Sathish; Fu, Lin; De Man, Bruno

2016-05-01

In this study, we implement and compare model based iterative reconstruction (MBIR) with dictionary learning (DL) over MBIR with pairwise pixel-difference regularization, in the context of transportation security. DL is a technique of sparse signal representation using an over complete dictionary which has provided promising results in image processing applications including denoising,1 as well as medical CT reconstruction.2 It has been previously reported that DL produces promising results in terms of noise reduction and preservation of structural details, especially for low dose and few-view CT acquisitions.2 A distinguishing feature of transportation security CT is that scanned baggage may contain items with a wide range of material densities. While medical CT typically scans soft tissues, blood with and without contrast agents, and bones, luggage typically contains more high density materials (i.e. metals and glass), which can produce severe distortions such as metal streaking artifacts. Important factors of security CT are the emphasis on image quality such as resolution, contrast, noise level, and CT number accuracy for target detection. While MBIR has shown exemplary performance in the trade-off of noise reduction and resolution preservation, we demonstrate that DL may further improve this trade-off. In this study, we used the KSVD-based DL3 combined with the MBIR cost-minimization framework and compared results to Filtered Back Projection (FBP) and MBIR with pairwise pixel-difference regularization. We performed a parameter analysis to show the image quality impact of each parameter. We also investigated few-view CT acquisitions where DL can show an additional advantage relative to pairwise pixel difference regularization.

Performance analysis of a dual-tree algorithm for computing spatial distance histograms

PubMed Central

Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni

2011-01-01

Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree. PMID:21804753

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.

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits

PubMed Central

Zeng, Ping; Mukherjee, Sayan; Zhou, Xiang

2017-01-01

Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. PMID:28746338

Toward n-Ship Computation of Trajectories for Shared Airspace

NASA Technical Reports Server (NTRS)

Moerder, Daniel D.; Rothhaar, Paul M.

2016-01-01

This paper considers an approach for modelling transport aircraft trajectories that can facilitate their rapid evaluation and modification, either en route or in terminal control areas, with the goal of efficiently making use of airspace and runways by a large population of vehicles without pairwise violation of separation criteria.

Methods for Mediation Analysis with Missing Data

ERIC Educational Resources Information Center

Zhang, Zhiyong; Wang, Lijuan

2013-01-01

Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including list wise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum…

Analyzing Longitudinal Item Response Data via the Pairwise Fitting Method

ERIC Educational Resources Information Center

Fu, Zhi-Hui; Tao, Jian; Shi, Ning-Zhong; Zhang, Ming; Lin, Nan

2011-01-01

Multidimensional item response theory (MIRT) models can be applied to longitudinal educational surveys where a group of individuals are administered different tests over time with some common items. However, computational problems typically arise as the dimension of the latent variables increases. This is especially true when the latent variable…

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

Σ 3 (111 ) grain boundary of body-centered cubic Ti-Mo and Ti-V alloys: First-principles and model calculations

NASA Astrophysics Data System (ADS)

Yan, Jia-Yi; Ehteshami, Hossein; Korzhavyi, Pavel A.; Borgenstam, Annika

2017-07-01

The energetics and atomic structures of Σ 3 [1 1 ¯0 ] (111 ) grain boundary (GB) of body-centered cubic (bcc) Ti-Mo and Ti-V alloys are investigated using density-functional-theory calculations and virtual crystal approximation. The electron density in bcc structure and the atomic displacements and excess energy of the GB are correlated to bcc-ω phase stability. Model calculations based on pairwise interplanar interactions successfully reproduce the chemical part of GB energy. The chemical GB energy can be expressed as a sum of excess pairwise interactions between bcc (111) layers, which are obtained from Gaussian elimination of the total energies of a number of periodic structures. The energy associated with the relaxation near the GB is solved by numerical minimization using the derivatives of the excess interactions. Anharmonic interlayer interactions are necessary for obtaining accurate relaxation energy and excess GB volume from model calculations. The effect of GB on vibrational spectrum is also investigated. Segregation energies of B and Y to a substitutional site on the GB plane are calculated. Preliminary results suggest that Y tends to segregate, while B tends to antisegregate.

High-throughput determination of RNA structure by proximity ligation.

PubMed

Ramani, Vijay; Qiu, Ruolan; Shendure, Jay

2015-09-01

We present an unbiased method to globally resolve RNA structures through pairwise contact measurements between interacting regions. RNA proximity ligation (RPL) uses proximity ligation of native RNA followed by deep sequencing to yield chimeric reads with ligation junctions in the vicinity of structurally proximate bases. We apply RPL in both baker's yeast (Saccharomyces cerevisiae) and human cells and generate contact probability maps for ribosomal and other abundant RNAs, including yeast snoRNAs, the RNA subunit of the signal recognition particle and the yeast U2 spliceosomal RNA homolog. RPL measurements correlate with established secondary structures for these RNA molecules, including stem-loop structures and long-range pseudoknots. We anticipate that RPL will complement the current repertoire of computational and experimental approaches in enabling the high-throughput determination of secondary and tertiary RNA structures.

Identification of forgeries in handwritten petitions for ballot propositions

NASA Astrophysics Data System (ADS)

Srihari, Sargur; Ramakrishnan, Veshnu; Malgireddy, Manavender; Ball, Gregory R.

2009-01-01

Many governments have some form of "direct democracy" legislation procedure whereby individual citizens can propose various measures creating or altering laws. Generally, such a process is started with the gathering of a large number of signatures. There is interest in whether or not there are fraudulent signatures present in such a petition, and if so what percentage of the signatures are indeed fraudulent. However, due to the large number of signatures (tens of thousands), it is not feasible to have a document examiner verify the signatures directly. Instead, there is interest in creating a subset of signatures where there is a high probability of fraud that can be verified. We present a method by which a pairwise comparison of signatures can be performed and subsequent sorting can generate such subsets.

A comparative study for chest radiograph image retrieval using binary texture and deep learning classification.

PubMed

Anavi, Yaron; Kogan, Ilya; Gelbart, Elad; Geva, Ofer; Greenspan, Hayit

2015-08-01

In this work various approaches are investigated for X-ray image retrieval and specifically chest pathology retrieval. Given a query image taken from a data set of 443 images, the objective is to rank images according to similarity. Different features, including binary features, texture features, and deep learning (CNN) features are examined. In addition, two approaches are investigated for the retrieval task. One approach is based on the distance of image descriptors using the above features (hereon termed the "descriptor"-based approach); the second approach ("classification"-based approach) is based on a probability descriptor, generated by a pair-wise classification of each two classes (pathologies) and their decision values using an SVM classifier. Best results are achieved using deep learning features in a classification scheme.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns.

PubMed

Lezon, Timothy R; Banavar, Jayanth R; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V

2006-12-12

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems.

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.

Modeling protein conformational changes by iterative fitting of distance constraints using reoriented normal modes.

PubMed

Zheng, Wenjun; Brooks, Bernard R

2006-06-15

Recently we have developed a normal-modes-based algorithm that predicts the direction of protein conformational changes given the initial state crystal structure together with a small number of pairwise distance constraints for the end state. Here we significantly extend this method to accurately model both the direction and amplitude of protein conformational changes. The new protocol implements a multisteps search in the conformational space that is driven by iteratively minimizing the error of fitting the given distance constraints and simultaneously enforcing the restraint of low elastic energy. At each step, an incremental structural displacement is computed as a linear combination of the lowest 10 normal modes derived from an elastic network model, whose eigenvectors are reorientated to correct for the distortions caused by the structural displacements in the previous steps. We test this method on a list of 16 pairs of protein structures for which relatively large conformational changes are observed (root mean square deviation >3 angstroms), using up to 10 pairwise distance constraints selected by a fluctuation analysis of the initial state structures. This method has achieved a near-optimal performance in almost all cases, and in many cases the final structural models lie within root mean square deviation of 1 approximately 2 angstroms from the native end state structures.

Testing hypotheses for differences between linear regression lines

Treesearch

Stanley J. Zarnoch

2009-01-01

Five hypotheses are identified for testing differences between simple linear regression lines. The distinctions between these hypotheses are based on a priori assumptions and illustrated with full and reduced models. The contrast approach is presented as an easy and complete method for testing for overall differences between the regressions and for making pairwise...

Affective Outcomes of Schooling: Full-Information Item Factor Analysis of a Student Questionnaire.

ERIC Educational Resources Information Center

Muraki, Eiji; Engelhard, George, Jr.

Recent developments in dichotomous factor analysis based on multidimensional item response models (Bock and Aitkin, 1981; Muthen, 1978) provide an effective method for exploring the dimensionality of questionnaire items. Implemented in the TESTFACT program, this "full information" item factor analysis accounts not only for the pairwise joint…

A Study of the Use of Pairwise Comparison in the Context of Social Online Moderation

ERIC Educational Resources Information Center

Tarricone, Pina; Newhouse, C. Paul

2016-01-01

Traditional moderation of student assessments is often carried out with groups of teachers working face-to-face in a specified location making judgements concerning the quality of representations of achievement. This traditional model has relied little on modern information communications technologies and has been logistically challenging. We…

Inductive Game Theory and the Dynamics of Animal Conflict

PubMed Central

DeDeo, Simon; Krakauer, David C.; Flack, Jessica C.

2010-01-01

Conflict destabilizes social interactions and impedes cooperation at multiple scales of biological organization. Of fundamental interest are the causes of turbulent periods of conflict. We analyze conflict dynamics in an monkey society model system. We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups. This technique uses Monte Carlo simulation to test alternative causal models of conflict dynamics. We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition. Furthermore, the social assessments on which these decisions are based are triadic (self in relation to another pair of individuals), not pairwise. We show that this triadic decision making causes long conflict cascades and that there is a high population cost of the large fights associated with these cascades. These results suggest that individual agency has been over-emphasized in the social evolution of complex aggregates, and that pair-wise formalisms are inadequate. An appreciation of the empirical foundations of the collective dynamics of conflict is a crucial step towards its effective management. PMID:20485557

Inductive game theory and the dynamics of animal conflict.

PubMed

DeDeo, Simon; Krakauer, David C; Flack, Jessica C

2010-05-13

Conflict destabilizes social interactions and impedes cooperation at multiple scales of biological organization. Of fundamental interest are the causes of turbulent periods of conflict. We analyze conflict dynamics in an monkey society model system. We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups. This technique uses Monte Carlo simulation to test alternative causal models of conflict dynamics. We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition. Furthermore, the social assessments on which these decisions are based are triadic (self in relation to another pair of individuals), not pairwise. We show that this triadic decision making causes long conflict cascades and that there is a high population cost of the large fights associated with these cascades. These results suggest that individual agency has been over-emphasized in the social evolution of complex aggregates, and that pair-wise formalisms are inadequate. An appreciation of the empirical foundations of the collective dynamics of conflict is a crucial step towards its effective management.

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.

Restricting the marketing of foods and non-alcoholic beverages to children in South Africa: are all nutrient profiling models the same?

PubMed

Wicks, Mariaan; Wright, Hattie; Wentzel-Viljoen, Edelweiss

2016-12-01

The WHO has called for governments to improve children's food environment by implementing restrictions on the marketing of 'unhealthy' foods to children. Nutrient profiling (NP) models are used to define 'unhealthy' foods and support child-directed food marketing regulations. The aim of the present study was to assess the suitability of the South African NP model (SANPM), developed and validated for health claim regulations, for child-directed food marketing regulations. The SANPM was compared with four NP models specifically developed for such regulations. A representative list of 197 foods was compiled by including all foods advertised on South African free-to-air television channels in 2014 and foods commonly consumed by South African children. The nutritional information of the foods was sourced from food packaging, company websites and a food composition table. Each individual food was classified by each of the five NP models. The percentage of foods that would be allowed according to the different NP models ranged from 6 to 45 %; the models also varied considerably with regard to the type of foods allowed for marketing to children. The majority of the pairwise comparisons between the NP models yielded κ statistics >0·4, indicating a moderate agreement between the models. An almost perfect pairwise agreement (κ=0·948) existed between the SANPM and the UK Food Standards Agency model (United Kingdom Office of Communication nutrient profiling model), a model extensively tested and validated for such regulations. The SANPM is considered appropriate for child-directed food marketing regulations in South Africa.

Prediction of penicillin resistance in Staphylococcus aureus isolates from dairy cows with mastitis, based on prior test results.

PubMed

Grinberg, A; Lopez-Villalobos, N; Lawrence, K; Nulsen, M

2005-10-01

To gauge how well prior laboratory test results predict in vitro penicillin resistance of Staphylococcus aureus isolates from dairy cows with mastitis. Population-based data on the farm of origin (n=79), genotype based on pulsed-field gel electrophoresis (PFGE) results, and the penicillin-resistance status of Staph. aureus isolates (n=115) from milk samples collected from dairy cows with mastitis submitted to two diagnostic laboratories over a 6-month period were used. Data were mined stochastically using the all-possible-pairs method, binomial modelling and bootstrap simulation, to test whether prior test results enhance the accuracy of prediction of penicillin resistance on farms. Of all Staph. aureus isolates tested, 38% were penicillin resistant. A significant aggregation of penicillin-resistance status was evident within farms. The probability of random pairs of isolates from the same farm having the same penicillin-resistance status was 76%, compared with 53% for random pairings of samples across all farms. Thus, the resistance status of randomly selected isolates was 1.43 times more likely to correctly predict the status of other isolates from the same farm than the random population pairwise concordance probability (p=0.011). This effect was likely due to the clonal relationship of isolates within farms, as the predictive fraction attributable to prior test results was close to nil when the effect of within-farm clonal infections was withdrawn from the model. Knowledge of the penicillin-resistance status of a prior Staph. aureus isolate significantly enhanced the predictive capability of other isolates from the same farm. In the time and space frame of this study, clinicians using previous information from a farm would have more accurately predicted the penicillin-resistance status of an isolate than they would by chance alone on farms infected with clonal Staph. aureus isolates, but not on farms infected with highly genetically heterogeneous bacterial strains.

Random regression analysis for body weights and main morphological traits in genetically improved farmed tilapia (Oreochromis niloticus).

PubMed

He, Jie; Zhao, Yunfeng; Zhao, Jingli; Gao, Jin; Xu, Pao; Yang, Runqing

2018-02-01

To genetically analyse growth traits in genetically improved farmed tilapia (GIFT), the body weight (BWE) and main morphological traits, including body length (BL), body depth (BD), body width (BWI), head length (HL) and length of the caudal peduncle (CPL), were measured six times in growth duration on 1451 fish from 45 mixed families of full and half sibs. A random regression model (RRM) was used to model genetic changes of the growth traits with days of age and estimate the heritability for any growth point and genetic correlations between pairwise growth points. Using the covariance function based on optimal RRMs, the heritabilities were estimated to be from 0.102 to 0.662 for BWE, 0.157 to 0.591 for BL, 0.047 to 0.621 for BD, 0.018 to 0.577 for BWI, 0.075 to 0.597 for HL and 0.032 to 0.610 for CPL between 60 and 140 days of age. All genetic correlations exceeded 0.5 between pairwise growth points. Moreover, the traits at initial days of age showed less correlation with those at later days of age. With phenotypes observed repeatedly, the model choice showed that the optimal RRMs could more precisely predict breeding values at a specific growth time than repeatability models or multiple trait animal models, which enhanced the efficiency of selection for the BWE and main morphological traits.

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

PubMed Central

Joyce, Blake L.; Haug-Baltzell, Asher K.; Hulvey, Jonathan P.; McCarthy, Fiona; Devisetty, Upendra Kumar; Lyons, Eric

2017-01-01

This workflow allows novice researchers to leverage advanced computational resources such as cloud computing to carry out pairwise comparative transcriptomics. It also serves as a primer for biologists to develop data scientist computational skills, e.g. executing bash commands, visualization and management of large data sets. All command line code and further explanations of each command or step can be found on the wiki (https://wiki.cyverse.org/wiki/x/dgGtAQ). The Discovery Environment and Atmosphere platforms are connected together through the CyVerse Data Store. As such, once the initial raw sequencing data has been uploaded there is no more need to transfer large data files over an Internet connection, minimizing the amount of time needed to conduct analyses. This protocol is designed to analyze only two experimental treatments or conditions. Differential gene expression analysis is conducted through pairwise comparisons, and will not be suitable to test multiple factors. This workflow is also designed to be manual rather than automated. Each step must be executed and investigated by the user, yielding a better understanding of data and analytical outputs, and therefore better results for the user. Once complete, this protocol will yield de novo assembled transcriptome(s) for underserved (non-model) organisms without the need to map to previously assembled reference genomes (which are usually not available in underserved organism). These de novo transcriptomes are further used in pairwise differential gene expression analysis to investigate genes differing between two experimental conditions. Differentially expressed genes are then functionally annotated to understand the genetic response organisms have to experimental conditions. In total, the data derived from this protocol is used to test hypotheses about biological responses of underserved organisms. PMID:28518075

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.

Untargeted analysis of chromatographic data for green and fermented rooibos: Problem with size effect removal.

PubMed

Tobin, Jade; Walach, Jan; de Beer, Dalene; Williams, Paul J; Filzmoser, Peter; Walczak, Beata

2017-11-24

While analyzing chromatographic data, it is necessary to preprocess it properly before exploration and/or supervised modeling. To make chromatographic signals comparable, it is crucial to remove the scaling effect, caused by differences in overall sample concentrations. One of the efficient methods of signal scaling is Probabilistic Quotient Normalization (PQN) [1]. However, it can be applied only to data for which the majority of features do not vary systematically among the studied classes of signals. When studying the influence of the traditional "fermentation" (oxidation) process on the concentration of 56 individual peaks detected in rooibos plant material, this assumption is not fulfilled. In this case, the only possible solution is the analysis of pairwise log-ratios, which are not influenced by the scaling constant. To estimate significant features, i.e., peaks differentiating the studied classes of samples (green and fermented rooibos plant material), we propose the application of rPLR (robust pair-wise log-ratios) as proposed by Walach et al. [2]. It allows for fast computation and identification of the significant features in terms of original variables (peaks) which is problematic, while working with the unfolded pair-wise log ratios. As demonstrated, it can be applied to designed data sets and in the case of contaminated data, it allows proper conclusions. Copyright © 2017 Elsevier B.V. All rights reserved.

KECSA-Movable Type Implicit Solvation Model (KMTISM)

PubMed Central

2015-01-01

Computation of the solvation free energy for chemical and biological processes has long been of significant interest. The key challenges to effective solvation modeling center on the choice of potential function and configurational sampling. Herein, an energy sampling approach termed the “Movable Type” (MT) method, and a statistical energy function for solvation modeling, “Knowledge-based and Empirical Combined Scoring Algorithm” (KECSA) are developed and utilized to create an implicit solvation model: KECSA-Movable Type Implicit Solvation Model (KMTISM) suitable for the study of chemical and biological systems. KMTISM is an implicit solvation model, but the MT method performs energy sampling at the atom pairwise level. For a specific molecular system, the MT method collects energies from prebuilt databases for the requisite atom pairs at all relevant distance ranges, which by its very construction encodes all possible molecular configurations simultaneously. Unlike traditional statistical energy functions, KECSA converts structural statistical information into categorized atom pairwise interaction energies as a function of the radial distance instead of a mean force energy function. Within the implicit solvent model approximation, aqueous solvation free energies are then obtained from the NVT ensemble partition function generated by the MT method. Validation is performed against several subsets selected from the Minnesota Solvation Database v2012. Results are compared with several solvation free energy calculation methods, including a one-to-one comparison against two commonly used classical implicit solvation models: MM-GBSA and MM-PBSA. Comparison against a quantum mechanics based polarizable continuum model is also discussed (Cramer and Truhlar’s Solvation Model 12). PMID:25691832

Validation of Potential Models for Li2O in Classical Molecular Dynamics Simulation

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

Oda, Takuji; Oya, Yasuhisa; Tanaka, Satoru

2007-08-01

Four Buckingham-type pairwise potential models for Li2O were assessed by molecular static and dynamics simulations. In the static simulation, all models afforded acceptable agreement with experimental values and ab initio calculation results for the crystalline properties. Moreover, the superionic phase transition was realized in the dynamics simulation. However, the Li diffusivity and the lattice expansion were not adequately reproduced at the same time by any model. When using these models in future radiation simulation, these features should be taken into account, in order to reduce the model dependency of the results.

Developing Pairwise Preference-Based Personality Test and Experimental Investigation of Its Resistance to Faking Effect by Item Response Model

ERIC Educational Resources Information Center

Usami, Satoshi; Sakamoto, Asami; Naito, Jun; Abe, Yu

2016-01-01

Recent years have shown increased awareness of the importance of personality tests in educational, clinical, and occupational settings, and developing faking-resistant personality tests is a very pragmatic issue for achieving more precise measurement. Inspired by Stark (2002) and Stark, Chernyshenko, and Drasgow (2005), we develop a pairwise…

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

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.

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

Cost-efficient designs for three-arm trials with treatment delivered by health professionals: Sample sizes for a combination of nested and crossed designs

PubMed Central

Moerbeek, Mirjam

2018-01-01

Background This article studies the design of trials that compare three treatment conditions that are delivered by two types of health professionals. The one type of health professional delivers one treatment, and the other type delivers two treatments, hence, this design is a combination of a nested and crossed design. As each health professional treats multiple patients, the data have a nested structure. This nested structure has thus far been ignored in the design of such trials, which may result in an underestimate of the required sample size. In the design stage, the sample sizes should be determined such that a desired power is achieved for each of the three pairwise comparisons, while keeping costs or sample size at a minimum. Methods The statistical model that relates outcome to treatment condition and explicitly takes the nested data structure into account is presented. Mathematical expressions that relate sample size to power are derived for each of the three pairwise comparisons on the basis of this model. The cost-efficient design achieves sufficient power for each pairwise comparison at lowest costs. Alternatively, one may minimize the total number of patients. The sample sizes are found numerically and an Internet application is available for this purpose. The design is also compared to a nested design in which each health professional delivers just one treatment. Results Mathematical expressions show that this design is more efficient than the nested design. For each pairwise comparison, power increases with the number of health professionals and the number of patients per health professional. The methodology of finding a cost-efficient design is illustrated using a trial that compares treatments for social phobia. The optimal sample sizes reflect the costs for training and supervising psychologists and psychiatrists, and the patient-level costs in the three treatment conditions. Conclusion This article provides the methodology for designing trials that compare three treatment conditions while taking the nesting of patients within health professionals into account. As such, it helps to avoid underpowered trials. To use the methodology, a priori estimates of the total outcome variances and intraclass correlation coefficients must be obtained from experts’ opinions or findings in the literature. PMID:29316807

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.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

PubMed Central

Lezon, Timothy R.; Banavar, Jayanth R.; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V.

2006-01-01

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems. PMID:17138668

Which is more effective for suppressing an infectious disease: imperfect vaccination or defense against contagion?

NASA Astrophysics Data System (ADS)

Kuga, Kazuki; Tanimoto, Jun

2018-02-01

We consider two imperfect ways to protect against an infectious disease such as influenza, namely vaccination giving only partial immunity and a defense against contagion such as wearing a mask. We build up a new analytic framework considering those two cases instead of perfect vaccination, conventionally assumed as a premise, with the assumption of an infinite and well-mixed population. Our framework also considers three different strategy-updating rules based on evolutionary game theory: conventional pairwise comparison with one randomly selected agent, another concept of pairwise comparison referring to a social average, and direct alternative selection not depending on the usual copying concept. We successfully obtain a phase diagram in which vaccination coverage at equilibrium can be compared when assuming the model of either imperfect vaccination or a defense against contagion. The obtained phase diagram reveals that a defense against contagion is marginally inferior to an imperfect vaccination as long as the same coefficient value is used. Highlights - We build a new analytical framework for a vaccination game combined with the susceptible-infected-recovered (SIR) model. - Our model can evaluate imperfect provisions such as vaccination giving only partial immunity and a defense against contagion. - We obtain a phase diagram with which to compare the quantitative effects of partial vaccination and a defense against contagion.

A randomized trial to determine the impact on compliance of a psychophysical peripheral cue based on the Elaboration Likelihood Model.

PubMed

Horton, Rachael Jane; Minniti, Antoinette; Mireylees, Stewart; McEntegart, Damian

2008-11-01

Non-compliance in clinical studies is a significant issue, but causes remain unclear. Utilizing the Elaboration Likelihood Model of persuasion, this study assessed the psychophysical peripheral cue 'Interactive Voice Response System (IVRS) call frequency' on compliance. 71 participants were randomized to once daily (OD), twice daily (BID) or three times daily (TID) call schedules over two weeks. Participants completed 30-item cognitive function tests at each call. Compliance was defined as proportion of expected calls within a narrow window (+/- 30 min around scheduled time), and within a relaxed window (-30 min to +4 h). Data were analyzed by ANOVA and pairwise comparisons adjusted by the Bonferroni correction. There was a relationship between call frequency and compliance. Bonferroni adjusted pairwise comparisons showed significantly higher compliance (p=0.03) for the BID (51.0%) than TID (30.3%) for the narrow window; for the extended window, compliance was higher (p=0.04) with OD (59.5%), than TID (38.4%). The IVRS psychophysical peripheral cue call frequency supported the ELM as a route to persuasion. The results also support OD strategy for optimal compliance. Models suggest specific indicators to enhance compliance with medication dosing and electronic patient diaries to improve health outcomes and data integrity respectively.

Redshift-space distortions with the halo occupation distribution - II. Analytic model

NASA Astrophysics Data System (ADS)

Tinker, Jeremy L.

2007-01-01

We present an analytic model for the galaxy two-point correlation function in redshift space. The cosmological parameters of the model are the matter density Ωm, power spectrum normalization σ8, and velocity bias of galaxies αv, circumventing the linear theory distortion parameter β and eliminating nuisance parameters for non-linearities. The model is constructed within the framework of the halo occupation distribution (HOD), which quantifies galaxy bias on linear and non-linear scales. We model one-halo pairwise velocities by assuming that satellite galaxy velocities follow a Gaussian distribution with dispersion proportional to the virial dispersion of the host halo. Two-halo velocity statistics are a combination of virial motions and host halo motions. The velocity distribution function (DF) of halo pairs is a complex function with skewness and kurtosis that vary substantially with scale. Using a series of collisionless N-body simulations, we demonstrate that the shape of the velocity DF is determined primarily by the distribution of local densities around a halo pair, and at fixed density the velocity DF is close to Gaussian and nearly independent of halo mass. We calibrate a model for the conditional probability function of densities around halo pairs on these simulations. With this model, the full shape of the halo velocity DF can be accurately calculated as a function of halo mass, radial separation, angle and cosmology. The HOD approach to redshift-space distortions utilizes clustering data from linear to non-linear scales to break the standard degeneracies inherent in previous models of redshift-space clustering. The parameters of the occupation function are well constrained by real-space clustering alone, separating constraints on bias and cosmology. We demonstrate the ability of the model to separately constrain Ωm,σ8 and αv in models that are constructed to have the same value of β at large scales as well as the same finger-of-god distortions at small scales.

Genome-wide screening of Oryza sativa ssp. japonica and indica reveals a complex family of proteins with ribosome-inactivating protein domains.

PubMed

Wytynck, Pieter; Rougé, Pierre; Van Damme, Els J M

2017-11-01

Ribosome-inactivating proteins (RIPs) are cytotoxic enzymes capable of halting protein synthesis by irreversible modification of ribosomes. Although RIPs are widespread they are not ubiquitous in the plant kingdom. The physiological importance of RIPs is not fully elucidated, but evidence suggests a role in the protection of the plant against biotic and abiotic stresses. Searches in the rice genome revealed a large and highly complex family of proteins with a RIP domain. A comparative analysis retrieved 38 RIP sequences from the genome sequence of Oryza sativa subspecies japonica and 34 sequences from the subspecies indica. The RIP sequences are scattered over different chromosomes but are mostly found on the third chromosome. The phylogenetic tree revealed the pairwise clustering of RIPs from japonica and indica. Molecular modeling and sequence analysis yielded information on the catalytic site of the enzyme, and suggested that a large part of RIP domains probably possess N-glycosidase activity. Several RIPs are differentially expressed in plant tissues and in response to specific abiotic stresses. This study provides an overview of RIP motifs in rice and will help to understand their biological role(s) and evolutionary relationships. Copyright © 2017 Elsevier Ltd. All rights reserved.

Novel space-time trellis codes for free-space optical communications using transmit laser selection.

PubMed

García-Zambrana, Antonio; Boluda-Ruiz, Rubén; Castillo-Vázquez, Carmen; Castillo-Vázquez, Beatriz

2015-09-21

In this paper, the deployment of novel space-time trellis codes (STTCs) with transmit laser selection (TLS) for free-space optical (FSO) communication systems using intensity modulation and direct detection (IM/DD) over atmospheric turbulence and misalignment fading channels is presented. Combining TLS and STTC with rate 1 bit/(s · Hz), a new code design criterion based on the use of the largest order statistics is here proposed for multiple-input/single-output (MISO) FSO systems in order to improve the diversity order gain by properly chosing the transmit lasers out of the available L lasers. Based on a pairwise error probability (PEP) analysis, closed-form asymptotic bit error-rate (BER) expressions in the range from low to high signal-to-noise ratio (SNR) are derived when the irradiance of the transmitted optical beam is susceptible to moderate-to-strong turbulence conditions, following a gamma-gamma (GG) distribution, and pointing error effects, following a misalignment fading model where the effect of beam width, detector size and jitter variance is considered. Obtained results show diversity orders of 2L and 3L when simple two-state and four-state STTCs are considered, respectively. Simulation results are further demonstrated to confirm the analytical results.

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.

Comparison of structural, thermodynamic, kinetic and mass transport properties of Mg(2+) ion models commonly used in biomolecular simulations.

PubMed

Panteva, Maria T; Giambaşu, George M; York, Darrin M

2015-05-15

The prevalence of Mg(2+) ions in biology and their essential role in nucleic acid structure and function has motivated the development of various Mg(2+) ion models for use in molecular simulations. Currently, the most widely used models in biomolecular simulations represent a nonbonded metal ion as an ion-centered point charge surrounded by a nonelectrostatic pairwise potential that takes into account dispersion interactions and exchange effects that give rise to the ion's excluded volume. One strategy toward developing improved models for biomolecular simulations is to first identify a Mg(2+) model that is consistent with the simulation force fields that closely reproduces a range of properties in aqueous solution, and then, in a second step, balance the ion-water and ion-solute interactions by tuning parameters in a pairwise fashion where necessary. The present work addresses the first step in which we compare 17 different nonbonded single-site Mg(2+) ion models with respect to their ability to simultaneously reproduce structural, thermodynamic, kinetic and mass transport properties in aqueous solution. None of the models based on a 12-6 nonelectrostatic nonbonded potential was able to reproduce the experimental radial distribution function, solvation free energy, exchange barrier and diffusion constant. The models based on a 12-6-4 potential offered improvement, and one model in particular, in conjunction with the SPC/E water model, performed exceptionally well for all properties. The results reported here establish useful benchmark calculations for Mg(2+) ion models that provide insight into the origin of the behavior in aqueous solution, and may aid in the development of next-generation models that target specific binding sites in biomolecules. © 2015 Wiley Periodicals, Inc.

Diel variation in detection and vocalization rates of king (Rallus elegans) and clapper (Rallus crepitans) rails in intracoastal waterways

USGS Publications Warehouse

Stiffler, Lydia L.; Anderson, James T.; Welsh, Amy B.; Harding, Sergio R.; Costanzo, Gary R.; Katzner, Todd

2017-01-01

Surveys for secretive marsh birds could be improved with refinements to address regional and species-specific variation in detection probabilities and optimal times of day to survey. Diel variation in relation to naïve occupancy, detection rates, and vocalization rates of King (Rallus elegans) and Clapper (R. crepitans) rails were studied in intracoastal waterways in Virginia, USA. Autonomous acoustic devices recorded vocalizations of King and Clapper rails at 75 locations for 48-hr periods within a marsh complex. Naïve King and Clapper rail occupancy did not vary hourly at either the marsh or the study area level. Combined King and Clapper rail detections and vocalizations varied across marshes, decreased as the sampling season progressed, and, for detections, was greatest during low rising tides (P < 0.01). Hourly variation in vocalization and detection rates did not show a pattern but occurred between 7.8% of pairwise comparisons for detections and 10.5% of pairwise comparisons for vocalizations (P < 0.01). Higher rates of detections and vocalizations occurred during the hours of 00:00–00:59, 05:00–05:59, 14:00–15:59, and lower rates during the hours of 07:00–09:59. Although statistically significant, because there were no patterns in these hourly differences, they may not be biologically relevant and are of little use to management. In fact, these findings demonstrate that surveys for King and Clapper rails in Virginia intracoastal waterways may be effectively conducted throughout the day.

Molecular characterization of echovirus 30-associated outbreak of aseptic meningitis in Korea in 2008.

PubMed

Choi, Young Jin; Park, Kwi Sung; Baek, Kyoung Ah; Jung, Eun Hye; Nam, Hae Seon; Kim, Yong Bae; Park, Joon Soo

2010-03-01

Evaluation of the primary etiologic agents that cause aseptic meningitis outbreaks may provide valuable information regarding the prevention and management of aseptic meningitis. In Korea, an outbreak of aseptic meningitis caused by echovirus type 30 (E30) occurred from May to October in 2008. In order to determine the etiologic agent, CSF and/or stool specimens from 140 children hospitalized for aseptic meningitis at Soonchunhyang University Cheonan Hospital between June and October of 2008 were tested for virus isolation and identification. E30 accounted for 61.7% (37 cases) and echovirus 6 accounted for 21.7% (13 cases) of all the human enteroviruses (HEVs) isolates (60 cases in total). For the molecular characterization of the isolates, the VP1 gene sequence of 18 Korean E30 isolates was compared pairwise using the MegAlign with 34 reference strains from the GenBank database. The pairwise comparison of the nucleotide sequences of the VP1 genes demonstrated that the sequences of the Korean strains differed from those of lineage groups A, B, C, D, E, F and G. Reconstruction of the phylogenetic tree based on the complete VP1 nucleotide sequences resulted in a monophyletic tree, with eight clustered lineage groups. All Korean isolates were segregated from other lineage groups, thus suggesting that the Korean strains were a distinct lineage of E30, and a probable cause of this outbreak. This manuscript is the first report, to the best of our knowledge, of the molecular characteristics of E30 strains associated with an aseptic meningitis outbreak in Korea, and their respective phylogenetic relationships.

Analysis of the seismicity preceding large earthquakes

NASA Astrophysics Data System (ADS)

Stallone, Angela; Marzocchi, Warner

2017-04-01

The most common earthquake forecasting models assume that the magnitude of the next earthquake is independent from the past. This feature is probably one of the most severe limitations of the capability to forecast large earthquakes. In this work, we investigate empirically on this specific aspect, exploring whether variations in seismicity in the space-time-magnitude domain encode some information on the size of the future earthquakes. For this purpose, and to verify the stability of the findings, we consider seismic catalogs covering quite different space-time-magnitude windows, such as the Alto Tiberina Near Fault Observatory (TABOO) catalogue, the California and Japanese seismic catalog. Our method is inspired by the statistical methodology proposed by Baiesi & Paczuski (2004) and elaborated by Zaliapin et al. (2008) to distinguish between triggered and background earthquakes, based on a pairwise nearest-neighbor metric defined by properly rescaled temporal and spatial distances. We generalize the method to a metric based on the k-nearest-neighbors that allows us to consider the overall space-time-magnitude distribution of k-earthquakes, which are the strongly correlated ancestors of a target event. Finally, we analyze the statistical properties of the clusters composed by the target event and its k-nearest-neighbors. In essence, the main goal of this study is to verify if different classes of target event magnitudes are characterized by distinctive "k-foreshocks" distributions. The final step is to show how the findings of this work may (or not) improve the skill of existing earthquake forecasting models.

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

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.

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…

Obtaining Rubric Weights for Assessments by More than One Lecturer Using a Pairwise Learning Model

ERIC Educational Resources Information Center

Quevedo, J. R.; Montanes, E.

2009-01-01

Specifying the criteria of a rubric to assess an activity, establishing the different quality levels of proficiency of development and defining weights for every criterion is not as easy as one a priori might think. Besides, the complexity of these tasks increases when they involve more than one lecturer. Reaching an agreement about the criteria…

New hypothesis elucidates self-incompatibility in the olive tree regarding S-alleles dominance relationships as in the sporophytic model.

PubMed

Breton, Catherine M; Bervillé, André

2012-09-01

Most olive varieties are not strictly self-incompatible, nevertheless, they request foreign pollen to enhance fruit yield, and consequently orchards should contain pollinisers to ensure fruit set of the main variety. The best way to choose pollinisers is to experiment numerous crosses in a diallel design. Here, the genetic mode of inheritance of SI in the olive is deciphered and it does not correspond to the GSI type, but to the SSI type. It leaves S-allele dominance relationship expression in the male (pollen and pollen tube), but not in the female (stigma and style). Thus, a pair-wise combination of varieties may be inter-compatible in one direction (male to female, or female to male) and inter-incompatible in the other direction. Dominance relationships also explain different levels of self-pollination observed in varieties. Little efficient pollinisers were found and predicted in varieties; nevertheless, some new efficient pair-wise allele combinations are predicted and could be created. This model enables one to forecast compatibility without waiting for several years of yield records and to choose pollinisers in silico. Copyright © 2012 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Reexamination of the interaction of atoms with a LiF(001) surface

NASA Astrophysics Data System (ADS)

Miraglia, J. E.; Gravielle, M. S.

2017-02-01

Pairwise additive potentials for multielectronic atoms interacting with a LiF(001) surface are revisited by including an improved description of the electron density associated with the different lattice sites, as well as nonlocal electron density contributions. Within this model, the electron distribution around each ionic site of the crystal is described by means of a so-called "onion" approach that accounts for the influence of the Madelung potential. From such densities, binary interatomic potentials are then derived by using well-known nonlocal functionals. Rumpling and long-range contributions due to projectile polarization and van der Waals forces are also included. We apply this pairwise additive approximation to evaluate the interaction potential between closed-shell (He, Ne, Ar, Kr, and Xe) and open-shell (N, S, and Cl) atoms and the LiF surface, analyzing the relative importance of the different contributions. The performance of the proposed potentials is assessed by contrasting angular positions of rainbow and supernumerary rainbow maxima produced by fast grazing incidence with available experimental data. One important result of our model is that both van der Waals contributions and thermal lattice vibrations play a negligible role for normal energies in the eV range.

Prioritizing Project Risks Using AHP

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

Thibadeau, Barbara M

2007-01-01

This essay introduces the Analytic Hierarchy Process (AHP) as a method by which to rank project risks, in terms of importance as well as likelihood. AHP is way to handle quantifiable and/or intangible criteria in the decision making process. It is a multi-objective multi-criteria decision-making approach that is based on the idea of pair-wise comparisons of alternatives with respect to a given criterion (e.g., which alternative, A or B, is preferred and by how much more is it preferred) or with respect to an objective (e.g., which is more important, A or B, and by how much more is itmore » important). This approach was pioneered by Thomas Saaty in the late 1970's. It has been suggested that a successful project is one that successfully manages risk and that project management is the management of uncertainty. Risk management relies on the quantification of uncertainty which, in turn, is predicated upon the accuracy of probabilistic approaches (in terms of likelihood as well as magnitude). In many cases, the appropriate probability distribution (or probability value) is unknown. And, researchers have shown that probability values are not made very accurately, that the use of verbal expressions is not a suitable alternative, that there is great variability in the use and interpretation of these values and that there is a great reluctance to assign them in the first place. Data from an ongoing project is used to show that AHP can be used to obtain these values, thus overcoming some of the problems associated with the direct assignment of discrete probability values. A novel method by which to calculate the consistency of the data is introduced. The AHP approach is easily implemented and, typically, offers results that are consistent with the decision maker's intuition.« less

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

Hierarchical semi-numeric method for pairwise fuzzy group decision making.

PubMed

Marimin, M; Umano, M; Hatono, I; Tamura, H

2002-01-01

Gradual improvements to a single-level semi-numeric method, i.e., linguistic labels preference representation by fuzzy sets computation for pairwise fuzzy group decision making are summarized. The method is extended to solve multiple criteria hierarchical structure pairwise fuzzy group decision-making problems. The problems are hierarchically structured into focus, criteria, and alternatives. Decision makers express their evaluations of criteria and alternatives based on each criterion by using linguistic labels. The labels are converted into and processed in triangular fuzzy numbers (TFNs). Evaluations of criteria yield relative criteria weights. Evaluations of the alternatives, based on each criterion, yield a degree of preference for each alternative or a degree of satisfaction for each preference value. By using a neat ordered weighted average (OWA) or a fuzzy weighted average operator, solutions obtained based on each criterion are aggregated into final solutions. The hierarchical semi-numeric method is suitable for solving a larger and more complex pairwise fuzzy group decision-making problem. The proposed method has been verified and applied to solve some real cases and is compared to Saaty's (1996) analytic hierarchy process (AHP) method.

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.

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

Algorithm for selection of optimized EPR distance restraints for de novo protein structure determination

PubMed Central

Kazmier, Kelli; Alexander, Nathan S.; Meiler, Jens; Mchaourab, Hassane S.

2010-01-01

A hybrid protein structure determination approach combining sparse Electron Paramagnetic Resonance (EPR) distance restraints and Rosetta de novo protein folding has been previously demonstrated to yield high quality models (Alexander et al., 2008). However, widespread application of this methodology to proteins of unknown structures is hindered by the lack of a general strategy to place spin label pairs in the primary sequence. In this work, we report the development of an algorithm that optimally selects spin labeling positions for the purpose of distance measurements by EPR. For the α-helical subdomain of T4 lysozyme (T4L), simulated restraints that maximize sequence separation between the two spin labels while simultaneously ensuring pairwise connectivity of secondary structure elements yielded vastly improved models by Rosetta folding. 50% of all these models have the correct fold compared to only 21% and 8% correctly folded models when randomly placed restraints or no restraints are used, respectively. Moreover, the improvements in model quality require a limited number of optimized restraints, the number of which is determined by the pairwise connectivities of T4L α-helices. The predicted improvement in Rosetta model quality was verified by experimental determination of distances between spin labels pairs selected by the algorithm. Overall, our results reinforce the rationale for the combined use of sparse EPR distance restraints and de novo folding. By alleviating the experimental bottleneck associated with restraint selection, this algorithm sets the stage for extending computational structure determination to larger, traditionally elusive protein topologies of critical structural and biochemical importance. PMID:21074624

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

Evolutionary games in the multiverse.

PubMed

Gokhale, Chaitanya S; Traulsen, Arne

2010-03-23

Evolutionary game dynamics of two players with two strategies has been studied in great detail. These games have been used to model many biologically relevant scenarios, ranging from social dilemmas in mammals to microbial diversity. Some of these games may, in fact, take place between a number of individuals and not just between two. Here we address one-shot games with multiple players. As long as we have only two strategies, many results from two-player games can be generalized to multiple players. For games with multiple players and more than two strategies, we show that statements derived for pairwise interactions no longer hold. For two-player games with any number of strategies there can be at most one isolated internal equilibrium. For any number of players with any number of strategies , there can be at most isolated internal equilibria. Multiplayer games show a great dynamical complexity that cannot be captured based on pairwise interactions. Our results hold for any game and can easily be applied to specific cases, such as public goods games or multiplayer stag hunts.

Graph Curvature for Differentiating Cancer Networks

PubMed Central

Sandhu, Romeil; Georgiou, Tryphon; Reznik, Ed; Zhu, Liangjia; Kolesov, Ivan; Senbabaoglu, Yasin; Tannenbaum, Allen

2015-01-01

Cellular interactions can be modeled as complex dynamical systems represented by weighted graphs. The functionality of such networks, including measures of robustness, reliability, performance, and efficiency, are intrinsically tied to the topology and geometry of the underlying graph. Utilizing recently proposed geometric notions of curvature on weighted graphs, we investigate the features of gene co-expression networks derived from large-scale genomic studies of cancer. We find that the curvature of these networks reliably distinguishes between cancer and normal samples, with cancer networks exhibiting higher curvature than their normal counterparts. We establish a quantitative relationship between our findings and prior investigations of network entropy. Furthermore, we demonstrate how our approach yields additional, non-trivial pair-wise (i.e. gene-gene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pair-wise changes in curvature which was computationally infeasible using prior methods. As such, our findings lay the foundation for an analytical approach to studying complex biological networks. PMID:26169480

Parametric embedding for class visualization.

PubMed

Iwata, Tomoharu; Saito, Kazumi; Ueda, Naonori; Stromsten, Sean; Griffiths, Thomas L; Tenenbaum, Joshua B

2007-09-01

We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.

Linkage of Viral Sequences among HIV-Infected Village Residents in Botswana: Estimation of Linkage Rates in the Presence of Missing Data

PubMed Central

Carnegie, Nicole Bohme; Wang, Rui; Novitsky, Vladimir; De Gruttola, Victor

2014-01-01

Linkage analysis is useful in investigating disease transmission dynamics and the effect of interventions on them, but estimates of probabilities of linkage between infected people from observed data can be biased downward when missingness is informative. We investigate variation in the rates at which subjects' viral genotypes link across groups defined by viral load (low/high) and antiretroviral treatment (ART) status using blood samples from household surveys in the Northeast sector of Mochudi, Botswana. The probability of obtaining a sequence from a sample varies with viral load; samples with low viral load are harder to amplify. Pairwise genetic distances were estimated from aligned nucleotide sequences of HIV-1C env gp120. It is first shown that the probability that randomly selected sequences are linked can be estimated consistently from observed data. This is then used to develop estimates of the probability that a sequence from one group links to at least one sequence from another group under the assumption of independence across pairs. Furthermore, a resampling approach is developed that accounts for the presence of correlation across pairs, with diagnostics for assessing the reliability of the method. Sequences were obtained for 65% of subjects with high viral load (HVL, n = 117), 54% of subjects with low viral load but not on ART (LVL, n = 180), and 45% of subjects on ART (ART, n = 126). The probability of linkage between two individuals is highest if both have HVL, and lowest if one has LVL and the other has LVL or is on ART. Linkage across groups is high for HVL and lower for LVL and ART. Adjustment for missing data increases the group-wise linkage rates by 40–100%, and changes the relative rates between groups. Bias in inferences regarding HIV viral linkage that arise from differential ability to genotype samples can be reduced by appropriate methods for accommodating missing data. PMID:24415932

Linkage of viral sequences among HIV-infected village residents in Botswana: estimation of linkage rates in the presence of missing data.

PubMed

Carnegie, Nicole Bohme; Wang, Rui; Novitsky, Vladimir; De Gruttola, Victor

2014-01-01

Linkage analysis is useful in investigating disease transmission dynamics and the effect of interventions on them, but estimates of probabilities of linkage between infected people from observed data can be biased downward when missingness is informative. We investigate variation in the rates at which subjects' viral genotypes link across groups defined by viral load (low/high) and antiretroviral treatment (ART) status using blood samples from household surveys in the Northeast sector of Mochudi, Botswana. The probability of obtaining a sequence from a sample varies with viral load; samples with low viral load are harder to amplify. Pairwise genetic distances were estimated from aligned nucleotide sequences of HIV-1C env gp120. It is first shown that the probability that randomly selected sequences are linked can be estimated consistently from observed data. This is then used to develop estimates of the probability that a sequence from one group links to at least one sequence from another group under the assumption of independence across pairs. Furthermore, a resampling approach is developed that accounts for the presence of correlation across pairs, with diagnostics for assessing the reliability of the method. Sequences were obtained for 65% of subjects with high viral load (HVL, n = 117), 54% of subjects with low viral load but not on ART (LVL, n = 180), and 45% of subjects on ART (ART, n = 126). The probability of linkage between two individuals is highest if both have HVL, and lowest if one has LVL and the other has LVL or is on ART. Linkage across groups is high for HVL and lower for LVL and ART. Adjustment for missing data increases the group-wise linkage rates by 40-100%, and changes the relative rates between groups. Bias in inferences regarding HIV viral linkage that arise from differential ability to genotype samples can be reduced by appropriate methods for accommodating missing data.

Percolation on fitness landscapes: effects of correlation, phenotype, and incompatibilities

PubMed Central

Gravner, Janko; Pitman, Damien; Gavrilets, Sergey

2009-01-01

We study how correlations in the random fitness assignment may affect the structure of fitness landscapes, in three classes of fitness models. The first is a phenotype space in which individuals are characterized by a large number n of continuously varying traits. In a simple model of random fitness assignment, viable phenotypes are likely to form a giant connected cluster percolating throughout the phenotype space provided the viability probability is larger than 1/2n. The second model explicitly describes genotype-to-phenotype and phenotype-to-fitness maps, allows for neutrality at both phenotype and fitness levels, and results in a fitness landscape with tunable correlation length. Here, phenotypic neutrality and correlation between fitnesses can reduce the percolation threshold, and correlations at the point of phase transition between local and global are most conducive to the formation of the giant cluster. In the third class of models, particular combinations of alleles or values of phenotypic characters are “incompatible” in the sense that the resulting genotypes or phenotypes have zero fitness. This setting can be viewed as a generalization of the canonical Bateson-Dobzhansky-Muller model of speciation and is related to K- SAT problems, prominent in computer science. We analyze the conditions for the existence of viable genotypes, their number, as well as the structure and the number of connected clusters of viable genotypes. We show that analysis based on expected values can easily lead to wrong conclusions, especially when fitness correlations are strong. We focus on pairwise incompatibilities between diallelic loci, but we also address multiple alleles, complex incompatibilities, and continuous phenotype spaces. In the case of diallelic loci, the number of clusters is stochastically bounded and each cluster contains a very large sub-cube. Finally, we demonstrate that the discrete NK model shares some signature properties of models with high correlations. PMID:17692873

Numerical approach for finite volume three-body interaction

NASA Astrophysics Data System (ADS)

Guo, Peng; Gasparian, Vladimir

2018-01-01

In the present work, we study a numerical approach to one dimensional finite volume three-body interaction, the method is demonstrated by considering a toy model of three spinless particles interacting with pair-wise δ -function potentials. The numerical results are compared with the exact solutions of three spinless bosons interaction when the strength of short-range interactions are set equal for all pairs.

TSP Symposium 2012 Proceedings

DTIC Science & Technology

2012-11-01

and Statistical Model 78 7.3 Analysis and Results 79 7.4 Threats to Validity and Limitations 85 7.5 Conclusions 86 7.6 Acknowledgments 87 7.7...Table 12: Overall Statistics of the Experiment 32 Table 13: Results of Pairwise ANOVA Analysis, Highlighting Statistically Significant Differences...we calculated the percentage of defects injected. The distribution statistics are shown in Table 2. Table 2: Mean Lower, Upper Confidence Interval

Hamiltonian formulation of systems with balanced loss-gain and exactly solvable models

NASA Astrophysics Data System (ADS)

Ghosh, Pijush K.; Sinha, Debdeep

2018-01-01

A Hamiltonian formulation of generic many-body systems with balanced loss and gain is presented. It is shown that a Hamiltonian formulation is possible only if the balancing of loss and gain terms occurs in a pairwise fashion. It is also shown that with the choice of a suitable co-ordinate, the Hamiltonian can always be reformulated in the background of a pseudo-Euclidean metric. If the equations of motion of some of the well-known many-body systems like Calogero models are generalized to include balanced loss and gain, it appears that the same may not be amenable to a Hamiltonian formulation. A few exactly solvable systems with balanced loss and gain, along with a set of integrals of motion are constructed. The examples include a coupled chain of nonlinear oscillators and a many-particle Calogero-type model with four-body inverse square plus two-body pair-wise harmonic interactions. For the case of nonlinear oscillators, stable solution exists even if the loss and gain parameter has unbounded upper range. Further, the range of the parameter for which the stable solutions are obtained is independent of the total number of the oscillators. The set of coupled nonlinear equations are solved exactly for the case when the values of all the constants of motions except the Hamiltonian are equal to zero. Exact, analytical classical solutions are presented for all the examples considered.

Cold dark matter. 2: Spatial and velocity statistics

NASA Technical Reports Server (NTRS)

Gelb, James M.; Bertschinger, Edmund

1994-01-01

We examine high-resolution gravitational N-body simulations of the omega = 1 cold dark matter (CDM) model in order to determine whether there is any normalization of the initial density fluctuation spectrum that yields acceptable results for galaxy clustering and velocities. Dense dark matter halos in the evolved mass distribution are identified with luminous galaxies; the most massive halos are also considered as sites for galaxy groups, with a range of possibilities explored for the group mass-to-light ratios. We verify the earlier conclusions of White et al. (1987) for the low-amplitude (high-bias) CDM model-the galaxy correlation function is marginally acceptable but that there are too many galaxies. We also show that the peak biasing method does not accurately reproduce the results obtained using dense halos identified in the simulations themselves. The Cosmic Background Explorer (COBE) anisotropy implies a higher normalization, resulting in problems with excessive pairwise galaxy velocity dispersion unless a strong velocity bias is present. Although we confirm the strong velocity bias of halos reported by Couchman & Carlberg (1992), we show that the galaxy motions are still too large on small scales. We find no amplitude for which the CDM model can reconcile simultaneously and galaxy correlation function, the low pairwise velocity dispersion, and the richness distribution of groups and clusters. With the normalization implied by COBE, the CDM spectrum has too much power on small scales if omega = 1.

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.

Pairwise domain adaptation module for CNN-based 2-D/3-D registration.

PubMed

Zheng, Jiannan; Miao, Shun; Jane Wang, Z; Liao, Rui

2018-04-01

Accurate two-dimensional to three-dimensional (2-D/3-D) registration of preoperative 3-D data and intraoperative 2-D x-ray images is a key enabler for image-guided therapy. Recent advances in 2-D/3-D registration formulate the problem as a learning-based approach and exploit the modeling power of convolutional neural networks (CNN) to significantly improve the accuracy and efficiency of 2-D/3-D registration. However, for surgery-related applications, collecting a large clinical dataset with accurate annotations for training can be very challenging or impractical. Therefore, deep learning-based 2-D/3-D registration methods are often trained with synthetically generated data, and a performance gap is often observed when testing the trained model on clinical data. We propose a pairwise domain adaptation (PDA) module to adapt the model trained on source domain (i.e., synthetic data) to target domain (i.e., clinical data) by learning domain invariant features with only a few paired real and synthetic data. The PDA module is designed to be flexible for different deep learning-based 2-D/3-D registration frameworks, and it can be plugged into any pretrained CNN model such as a simple Batch-Norm layer. The proposed PDA module has been quantitatively evaluated on two clinical applications using different frameworks of deep networks, demonstrating its significant advantages of generalizability and flexibility for 2-D/3-D medical image registration when a small number of paired real-synthetic data can be obtained.

A discrete model of Ostwald ripening based on multiple pairwise interactions

NASA Astrophysics Data System (ADS)

Di Nunzio, Paolo Emilio

2018-06-01

A discrete multi-particle model of Ostwald ripening based on direct pairwise interactions is developed for particles with incoherent interfaces as an alternative to the classical LSW mean field theory. The rate of matter exchange depends on the average surface-to-surface interparticle distance, a characteristic feature of the system which naturally incorporates the effect of volume fraction of second phase. The multi-particle diffusion is described through the definition of an interaction volume containing all the particles involved in the exchange of solute. At small volume fractions this is proportional to the size of the central particle, at higher volume fractions it gradually reduces as a consequence of diffusion screening described on a geometrical basis. The topological noise present in real systems is also included. For volume fractions below about 0.1 the model predicts broad and right-skewed stationary size distributions resembling a lognormal function. Above this value, a transition to sharper, more symmetrical but still right-skewed shapes occurs. An excellent agreement with experiments is obtained for 3D particle size distributions of solid-solid and solid-liquid systems with volume fraction 0.07, 0.30, 0.52 and 0.74. The kinetic constant of the model depends on the cube root of volume fraction up to about 0.1, then increases rapidly with an upward concavity. It is in good agreement with the available literature data on solid-liquid mixtures in the volume fraction range from 0.20 to about 0.75.

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

Unified framework for information integration based on information geometry

PubMed Central

Oizumi, Masafumi; Amari, Shun-ichi

2016-01-01

Assessment of causal influences is a ubiquitous and important subject across diverse research fields. Drawn from consciousness studies, integrated information is a measure that defines integration as the degree of causal influences among elements. Whereas pairwise causal influences between elements can be quantified with existing methods, quantifying multiple influences among many elements poses two major mathematical difficulties. First, overestimation occurs due to interdependence among influences if each influence is separately quantified in a part-based manner and then simply summed over. Second, it is difficult to isolate causal influences while avoiding noncausal confounding influences. To resolve these difficulties, we propose a theoretical framework based on information geometry for the quantification of multiple causal influences with a holistic approach. We derive a measure of integrated information, which is geometrically interpreted as the divergence between the actual probability distribution of a system and an approximated probability distribution where causal influences among elements are statistically disconnected. This framework provides intuitive geometric interpretations harmonizing various information theoretic measures in a unified manner, including mutual information, transfer entropy, stochastic interaction, and integrated information, each of which is characterized by how causal influences are disconnected. In addition to the mathematical assessment of consciousness, our framework should help to analyze causal relationships in complex systems in a complete and hierarchical manner. PMID:27930289

Network meta-analysis of probiotics to prevent respiratory infections in children and adolescents.

PubMed

Amaral, Marina Azambuja; Guedes, Gabriela Helena Barbosa Ferreira; Epifanio, Matias; Wagner, Mario Bernardes; Jones, Marcus Herbert; Mattiello, Rita

2017-06-01

Probiotics have emerged as a promising intervention for the prevention of respiratory tract infections (RTIs) in children. Assess the effect of probiotics on prevention of RTIs in children and adolescents. MEDLINE, EMBASE, LILACS, SCIELO, CINAHL, SCOPUS, and Web of Science. Key words: "respiratory tract infections" AND probiotics. Randomized controlled trials RCT assessing the effect of probiotics on RTIs in children and adolescents were included. Two reviewers, working independently, to identify studies that met the eligibility criteria. Main and secondary outcomes were RTIs and adverse effects, respectively. Twenty-one trials with 6.603 participants were included. Pairwise meta-analysis suggested that Lactobacillus casei rhamnosus (LCA) was the only effective probiotic to the rate of RTIs compared to placebo (RR0.38; Crl 0.19-0.45). Network analysis showed that the LCA exhibited 54.7% probability of being classified in first, while the probability of Lactobacillus fermentum CECT5716 (LFC) being last in the ranking was 15.3%. LCA showed no better effect compared to other probiotic strains by indirect analysis. This systematic review found a lack of evidence to support the effect of probiotic on the incidence rate of respiratory infections in children and adolescents. Pediatr Pulmonol. 2017;52:833-843. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder

PubMed Central

Venkataraman, Archana; Kubicki, Marek; Golland, Polina

2014-01-01

We propose a novel approach to identify the foci of a neurological disorder based on anatomical and functional connectivity information. Specifically, we formulate a generative model that characterizes the network of abnormal functional connectivity emanating from the affected foci. This allows us to aggregate pairwise connectivity changes into a region-based representation of the disease. We employ the variational expectation-maximization algorithm to fit the model and subsequently identify both the afflicted regions and the differences in connectivity induced by the disorder. We demonstrate our method on a population study of schizophrenia. PMID:23864168

Evolution of biological sequences implies an extreme value distribution of type I for both global and local pairwise alignment scores.

PubMed

Bastien, Olivier; Maréchal, Eric

2008-08-07

Confidence in pairwise alignments of biological sequences, obtained by various methods such as Blast or Smith-Waterman, is critical for automatic analyses of genomic data. Two statistical models have been proposed. In the asymptotic limit of long sequences, the Karlin-Altschul model is based on the computation of a P-value, assuming that the number of high scoring matching regions above a threshold is Poisson distributed. Alternatively, the Lipman-Pearson model is based on the computation of a Z-value from a random score distribution obtained by a Monte-Carlo simulation. Z-values allow the deduction of an upper bound of the P-value (1/Z-value2) following the TULIP theorem. Simulations of Z-value distribution is known to fit with a Gumbel law. This remarkable property was not demonstrated and had no obvious biological support. We built a model of evolution of sequences based on aging, as meant in Reliability Theory, using the fact that the amount of information shared between an initial sequence and the sequences in its lineage (i.e., mutual information in Information Theory) is a decreasing function of time. This quantity is simply measured by a sequence alignment score. In systems aging, the failure rate is related to the systems longevity. The system can be a machine with structured components, or a living entity or population. "Reliability" refers to the ability to operate properly according to a standard. Here, the "reliability" of a sequence refers to the ability to conserve a sufficient functional level at the folded and maturated protein level (positive selection pressure). Homologous sequences were considered as systems 1) having a high redundancy of information reflected by the magnitude of their alignment scores, 2) which components are the amino acids that can independently be damaged by random DNA mutations. From these assumptions, we deduced that information shared at each amino acid position evolved with a constant rate, corresponding to the information hazard rate, and that pairwise sequence alignment scores should follow a Gumbel distribution, which parameters could find some theoretical rationale. In particular, one parameter corresponds to the information hazard rate. Extreme value distribution of alignment scores, assessed from high scoring segments pairs following the Karlin-Altschul model, can also be deduced from the Reliability Theory applied to molecular sequences. It reflects the redundancy of information between homologous sequences, under functional conservative pressure. This model also provides a link between concepts of biological sequence analysis and of systems biology.

Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach

USGS Publications Warehouse

Row, Jeff R; Oyler-McCance, Sara J.; Fike, Jennifer; O'Donnell, Michael; Doherty, Kevin E.; Aldridge, Cameron L.; Bowen, Zachary H.; Fedy, Brad C.

2015-01-01

Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.

Relating Diseases by Integrating Gene Associations and Information Flow through Protein Interaction Network

PubMed Central

Hamaneh, Mehdi Bagheri; Yu, Yi-Kuo

2014-01-01

Identifying similar diseases could potentially provide deeper understanding of their underlying causes, and may even hint at possible treatments. For this purpose, it is necessary to have a similarity measure that reflects the underpinning molecular interactions and biological pathways. We have thus devised a network-based measure that can partially fulfill this goal. Our method assigns weights to all proteins (and consequently their encoding genes) by using information flow from a disease to the protein interaction network and back. Similarity between two diseases is then defined as the cosine of the angle between their corresponding weight vectors. The proposed method also provides a way to suggest disease-pathway associations by using the weights assigned to the genes to perform enrichment analysis for each disease. By calculating pairwise similarities between 2534 diseases, we show that our disease similarity measure is strongly correlated with the probability of finding the diseases in the same disease family and, more importantly, sharing biological pathways. We have also compared our results to those of MimMiner, a text-mining method that assigns pairwise similarity scores to diseases. We find the results of the two methods to be complementary. It is also shown that clustering diseases based on their similarities and performing enrichment analysis for the cluster centers significantly increases the term association rate, suggesting that the cluster centers are better representatives for biological pathways than the diseases themselves. This lends support to the view that our similarity measure is a good indicator of relatedness of biological processes involved in causing the diseases. Although not needed for understanding this paper, the raw results are available for download for further study at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbpmn/DiseaseRelations/. PMID:25360770

Resurrecting an extinct salmon evolutionarily significant unit: archived scales, historical DNA and implications for restoration.

PubMed

Iwamoto, Eric M; Myers, James M; Gustafson, Richard G

2012-04-01

Archival scales from 603 sockeye salmon (Oncorhynchus nerka), sampled from May to July 1924 in the lower Columbia River, were analysed for genetic variability at 12 microsatellite loci and compared to 17 present-day O. nerka populations-exhibiting either anadromous (sockeye salmon) or nonanadromous (kokanee) life histories-from throughout the Columbia River Basin, including areas upstream of impassable dams built subsequent to 1924. Statistical analyses identified four major genetic assemblages of sockeye salmon in the 1924 samples. Two of these putative historical groupings were found to be genetically similar to extant evolutionarily significant units (ESUs) in the Okanogan and Wenatchee Rivers (pairwise F(ST)  = 0.004 and 0.002, respectively), and assignment tests were able to allocate 77% of the fish in these two historical groupings to the contemporary Okanogan River and Lake Wenatchee ESUs. A third historical genetic grouping was most closely aligned with contemporary sockeye salmon in Redfish Lake, Idaho, although the association was less robust (pairwise F(ST)  = 0.060). However, a fourth genetic grouping did not appear to be related to any contemporary sockeye salmon or kokanee population, assigned poorly to the O. nerka baseline, and had distinctive early return migration timing, suggesting that this group represents a historical ESU originating in headwater lakes in British Columbia that was probably extirpated sometime after 1924. The lack of a contemporary O. nerka population possessing the genetic legacy of this extinct ESU indicates that efforts to reestablish early-migrating sockeye salmon to the headwater lakes region of the Columbia River will be difficult. © 2012 Blackwell Publishing Ltd.

Relating diseases by integrating gene associations and information flow through protein interaction network.

PubMed

Hamaneh, Mehdi Bagheri; Yu, Yi-Kuo

2014-01-01

Identifying similar diseases could potentially provide deeper understanding of their underlying causes, and may even hint at possible treatments. For this purpose, it is necessary to have a similarity measure that reflects the underpinning molecular interactions and biological pathways. We have thus devised a network-based measure that can partially fulfill this goal. Our method assigns weights to all proteins (and consequently their encoding genes) by using information flow from a disease to the protein interaction network and back. Similarity between two diseases is then defined as the cosine of the angle between their corresponding weight vectors. The proposed method also provides a way to suggest disease-pathway associations by using the weights assigned to the genes to perform enrichment analysis for each disease. By calculating pairwise similarities between 2534 diseases, we show that our disease similarity measure is strongly correlated with the probability of finding the diseases in the same disease family and, more importantly, sharing biological pathways. We have also compared our results to those of MimMiner, a text-mining method that assigns pairwise similarity scores to diseases. We find the results of the two methods to be complementary. It is also shown that clustering diseases based on their similarities and performing enrichment analysis for the cluster centers significantly increases the term association rate, suggesting that the cluster centers are better representatives for biological pathways than the diseases themselves. This lends support to the view that our similarity measure is a good indicator of relatedness of biological processes involved in causing the diseases. Although not needed for understanding this paper, the raw results are available for download for further study at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbpmn/DiseaseRelations/.

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.

Species detection and identification in sexual organisms using population genetic theory and DNA sequences.

PubMed

Birky, C William

2013-01-01

Phylogenetic trees of DNA sequences of a group of specimens may include clades of two kinds: those produced by stochastic processes (random genetic drift) within a species, and clades that represent different species. The ratio of the mean pairwise sequence difference between a pair of clades (K) to the mean pairwise sequence difference within a clade (θ) can be used to determine whether the clades are samples from different species (K/θ ≥ 4) or the same species (K/θ<4) with probability ≥ 0.95. Previously I applied this criterion to delimit species of asexual organisms. Here I use data from the literature to show how it can also be applied to delimit sexual species using four groups of sexual organisms as examples: ravens, spotted leopards, sea butterflies, and liverworts. Mitochondrial or chloroplast genes are used because these segregate earlier during speciation than most nuclear genes and hence detect earlier stages of speciation. In several cases the K/θ ratio was greater than 4, confirming the original authors' intuition that the clades were sufficiently different to be assigned to different species. But the K/θ ratio split each of two liverwort species into two evolutionary species, and showed that support for the distinction between the common and Chihuahuan raven species is weak. I also discuss some possible sources of error in using the K/θ ratio; the most significant one would be cases where males migrate between different populations but females do not, making the use of maternally inherited organelle genes problematic. The K/θ ratio must be used with some caution, like all other methods for species delimitation. Nevertheless, it is a simple theory-based quantitative method for using DNA sequences to make rigorous decisions about species delimitation in sexual as well as asexual eukaryotes.

Systematic review with meta-analysis: comparative efficacy of immunosuppressants and biologics for reducing hospitalisation and surgery in Crohn's disease and ulcerative colitis.

PubMed

Mao, E J; Hazlewood, G S; Kaplan, G G; Peyrin-Biroulet, L; Ananthakrishnan, A N

2017-01-01

Crohn's disease (CD) and ulcerative colitis (UC) have a progressive course leading to hospitalisation and surgery. The ability of existing therapies to alter disease course is not clearly defined. To investigate the comparative efficacy of currently available inflammatory bowel disease (IBD) therapies to reduce hospitalisation and surgery. We conducted a systematic review in MEDLINE/PubMed for randomised controlled trials (RCT) published between January 1980 and May 2016 examining efficacy of biological or immunomodulator therapy in IBD. We performed direct comparisons of pooled proportions of hospitalisation and surgery. Pair-wise comparisons using a random-effects Bayesian network meta-analysis were performed to assess comparative efficacy of different treatments. We identified seven randomised controlled trials (5 CD; 2 UC) comparing three biologics and one immunomodulator with placebo. In CD, anti-TNF biologics significantly reduced hospitalisation [Odds ratio (OR) 0.46, 95% confidence interval (CI) 0.36-0.60] and surgery (OR 0.23, 95% CI 0.13-0.42) compared to placebo. No statistically significant reduction was noted with azathioprine or vedolizumab. Azathioprine was inferior to both infliximab and adalimumab in preventing CD-related hospitalisation (>97.5% probability). Anti-TNF biologics significantly reduced hospitalisation (OR 0.48, 95% CI 0.29-0.80) and surgery (OR 0.67, 95% CI 0.46-0.97) in UC. There were no statistically significant differences in the pair-wise comparisons between active treatments. In CD and UC, anti-TNF biologics are efficacious in reducing the odds of hospitalisation by half and surgery by 33-77%. Azathioprine and vedolizumab were not associated with a similar improvement, but robust conclusions may be limited due to paucity of RCTs. © 2016 John Wiley & Sons Ltd.

Information Geometry for Landmark Shape Analysis: Unifying Shape Representation and Deformation

PubMed Central

Peter, Adrian M.; Rangarajan, Anand

2010-01-01

Shape matching plays a prominent role in the comparison of similar structures. We present a unifying framework for shape matching that uses mixture models to couple both the shape representation and deformation. The theoretical foundation is drawn from information geometry wherein information matrices are used to establish intrinsic distances between parametric densities. When a parameterized probability density function is used to represent a landmark-based shape, the modes of deformation are automatically established through the information matrix of the density. We first show that given two shapes parameterized by Gaussian mixture models (GMMs), the well-known Fisher information matrix of the mixture model is also a Riemannian metric (actually, the Fisher-Rao Riemannian metric) and can therefore be used for computing shape geodesics. The Fisher-Rao metric has the advantage of being an intrinsic metric and invariant to reparameterization. The geodesic—computed using this metric—establishes an intrinsic deformation between the shapes, thus unifying both shape representation and deformation. A fundamental drawback of the Fisher-Rao metric is that it is not available in closed form for the GMM. Consequently, shape comparisons are computationally very expensive. To address this, we develop a new Riemannian metric based on generalized ϕ-entropy measures. In sharp contrast to the Fisher-Rao metric, the new metric is available in closed form. Geodesic computations using the new metric are considerably more efficient. We validate the performance and discriminative capabilities of these new information geometry-based metrics by pairwise matching of corpus callosum shapes. We also study the deformations of fish shapes that have various topological properties. A comprehensive comparative analysis is also provided using other landmark-based distances, including the Hausdorff distance, the Procrustes metric, landmark-based diffeomorphisms, and the bending energies of the thin-plate (TPS) and Wendland splines. PMID:19110497

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

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].

Chinese Herbal Medicine for Improving Quality of Life Among Nonsmall Cell Lung Cancer Patients: Overview of Systematic Reviews and Network Meta-Analysis.

PubMed

Wu, Xinyin; Chung, Vincent C H; Lu, Ping; Poon, Simon K; Hui, Edwin P; Lau, Alexander Y L; Balneaves, Lynda G; Wong, Samuel Y S; Wu, Justin C Y

2016-01-01

For patients with nonsmall cell lung cancer (NSCLC) receiving chemotherapy, current clinical evidence has indicated add-on benefit of Chinese herbal medicine (CHM) in improving quality of life (QoL). However, the relative performance among different CHM is unknown. The aim of this overview of systematic reviews (SRs) and network meta-analyses (NMA) is to evaluate the comparative effectiveness of different CHM. Seven electronic databases including both international databases and Chinese databases were searched. SRs focus on randomized controlled trials (RCTs) with comparison of CHM plus chemotherapy against chemotherapy alone on QoL among NSCLC patients were considered eligible. Data from RCTs were extracted for random effect pairwise meta-analyses. Pooled relative risk (RR) with 95% confidence interval (CI) was used to quantify the impact of CHM on QoL. NMA was used to explore the most effective CHM for improving QoL when used with chemotherapy. From 14 SRs, 61 RCTs (n = 4247) assessing 11 different CHM were included. Result from pairwise meta-analyses showed 6 CHM (Kang-lai-te injection, Shei-qi-fu-zheng injection, Compound ku-shen injection, Kang-ai injection, Zi-jin-long tablet, and Shen-fu injection) has significant beneficial effect on QoL among NSCLC patients when used with chemotherapy, even after adjustment for publication bias. Pooled RR varied from 1.38 (95% CI: 1.11-1.72, I2 = 0.0%, Kang-lai-te injection) to 3.36 (95% CI: 1.30-8.66, I2 = 0.0%, Zi-jin-long tablet). One trial comparing Hai-shen-su (a protein extract from Tegillarca granosa L.) plus chemotherapy with chemotherapy also demonstrated beneficial effect of combined treatment (RR = 3.13, 95% CI: 1.41-6.98). Results from NMA showed no differences on the comparative effectiveness among CHM, but Hai-shen-su plus chemotherapy has the highest probability (62.3%) of being the best option for improving QoL. Use of CHM on top of chemotherapy can significantly improve QoL in NSCLC patients. Although Hai-shen-su showed the highest probability of being the best add-on to chemotherapy, the effectiveness of all 11 CHM reviewed appeared to be similar. In the future, rigorous placebo controlled trials with proper blinding are needed to confirm the effectiveness of CHM.

Improving pairwise comparison of protein sequences with domain co-occurrence

PubMed Central

Gascuel, Olivier

2018-01-01

Comparing and aligning protein sequences is an essential task in bioinformatics. More specifically, local alignment tools like BLAST are widely used for identifying conserved protein sub-sequences, which likely correspond to protein domains or functional motifs. However, to limit the number of false positives, these tools are used with stringent sequence-similarity thresholds and hence can miss several hits, especially for species that are phylogenetically distant from reference organisms. A solution to this problem is then to integrate additional contextual information to the procedure. Here, we propose to use domain co-occurrence to increase the sensitivity of pairwise sequence comparisons. Domain co-occurrence is a strong feature of proteins, since most protein domains tend to appear with a limited number of other domains on the same protein. We propose a method to take this information into account in a typical BLAST analysis and to construct new domain families on the basis of these results. We used Plasmodium falciparum as a case study to evaluate our method. The experimental findings showed an increase of 14% of the number of significant BLAST hits and an increase of 25% of the proteome area that can be covered with a domain. Our method identified 2240 new domains for which, in most cases, no model of the Pfam database could be linked. Moreover, our study of the quality of the new domains in terms of alignment and physicochemical properties show that they are close to that of standard Pfam domains. Source code of the proposed approach and supplementary data are available at: https://gite.lirmm.fr/menichelli/pairwise-comparison-with-cooccurrence PMID:29293498

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...

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

Linking Parameter Estimates Derived from an Item Response Model through Separate Calibrations. Research Report. ETS RR-09-40

ERIC Educational Resources Information Center

Haberman, Shelby J.

2009-01-01

A regression procedure is developed to link simultaneously a very large number of item response theory (IRT) parameter estimates obtained from a large number of test forms, where each form has been separately calibrated and where forms can be linked on a pairwise basis by means of common items. An application is made to forms in which a…

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.

Inferring species divergence times using pairwise sequential Markovian coalescent modelling and low-coverage genomic data.

PubMed

Cahill, James A; Soares, André E R; Green, Richard E; Shapiro, Beth

2016-07-19

Understanding when species diverged aids in identifying the drivers of speciation, but the end of gene flow between populations can be difficult to ascertain from genetic data. We explore the use of pairwise sequential Markovian coalescent (PSMC) modelling to infer the timing of divergence between species and populations. PSMC plots generated using artificial hybrid genomes show rapid increases in effective population size at the time when the two parent lineages diverge, and this approach has been used previously to infer divergence between human lineages. We show that, even without high coverage or phased input data, PSMC can detect the end of significant gene flow between populations by comparing the PSMC output from artificial hybrids to the output of simulations with known demographic histories. We then apply PSMC to detect divergence times among lineages within two real datasets: great apes and bears within the genus Ursus Our results confirm most previously proposed divergence times for these lineages, and suggest that gene flow between recently diverged lineages may have been common among bears and great apes, including up to one million years of continued gene flow between chimpanzees and bonobos after the formation of the Congo River.This article is part of the themed issue 'Dating species divergences using rocks and clocks'. © 2016 The Author(s).

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.

Application of a time-dependent coalescence process for inferring the history of population size changes from DNA sequence data.

PubMed

Polanski, A; Kimmel, M; Chakraborty, R

1998-05-12

Distribution of pairwise differences of nucleotides from data on a sample of DNA sequences from a given segment of the genome has been used in the past to draw inferences about the past history of population size changes. However, all earlier methods assume a given model of population size changes (such as sudden expansion), parameters of which (e.g., time and amplitude of expansion) are fitted to the observed distributions of nucleotide differences among pairwise comparisons of all DNA sequences in the sample. Our theory indicates that for any time-dependent population size, N(tau) (in which time tau is counted backward from present), a time-dependent coalescence process yields the distribution, p(tau), of the time of coalescence between two DNA sequences randomly drawn from the population. Prediction of p(tau) and N(tau) requires the use of a reverse Laplace transform known to be unstable. Nevertheless, simulated data obtained from three models of monotone population change (stepwise, exponential, and logistic) indicate that the pattern of a past population size change leaves its signature on the pattern of DNA polymorphism. Application of the theory to the published mtDNA sequences indicates that the current mtDNA sequence variation is not inconsistent with a logistic growth of the human population.

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.

Kernel machine methods for integrative analysis of genome-wide methylation and genotyping studies.

PubMed

Zhao, Ni; Zhan, Xiang; Huang, Yen-Tsung; Almli, Lynn M; Smith, Alicia; Epstein, Michael P; Conneely, Karen; Wu, Michael C

2018-03-01

Many large GWAS consortia are expanding to simultaneously examine the joint role of DNA methylation in addition to genotype in the same subjects. However, integrating information from both data types is challenging. In this paper, we propose a composite kernel machine regression model to test the joint epigenetic and genetic effect. Our approach works at the gene level, which allows for a common unit of analysis across different data types. The model compares the pairwise similarities in the phenotype to the pairwise similarities in the genotype and methylation values; and high correspondence is suggestive of association. A composite kernel is constructed to measure the similarities in the genotype and methylation values between pairs of samples. We demonstrate through simulations and real data applications that the proposed approach can correctly control type I error, and is more robust and powerful than using only the genotype or methylation data in detecting trait-associated genes. We applied our method to investigate the genetic and epigenetic regulation of gene expression in response to stressful life events using data that are collected from the Grady Trauma Project. Within the kernel machine testing framework, our methods allow for heterogeneity in effect sizes, nonlinear, and interactive effects, as well as rapid P-value computation. © 2017 WILEY PERIODICALS, INC.

Differences by Veteran/civilian status and gender in associations between childhood adversity and alcohol and drug use disorders.

PubMed

Evans, Elizabeth A; Upchurch, Dawn M; Simpson, Tracy; Hamilton, Alison B; Hoggatt, Katherine J

2018-04-01

To examine differences by US military Veteran status and gender in associations between childhood adversity and DSM-5 lifetime alcohol and drug use disorders (AUD/DUD). We analyzed nationally representative data from 3119 Veterans (n = 379 women; n = 2740 men) and 33,182 civilians (n = 20,066 women; n = 13,116 men) as provided by the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC-III). We used weighted multinomial logistic regression, tested interaction terms, and calculated predicted probabilities by Veteran status and gender, controlling for covariates. To test which specific moderation contrasts were statistically significant, we conducted pairwise comparisons. Among civilians, women had lower AUD and DUD prevalence than men; however, with more childhood adversity, this gender gap narrowed for AUD and widened for DUD. Among Veterans, in contrast, similar proportions of women and men had AUD and DUD; with more childhood adversity, AUD-predicted probability among men surpassed that of women. Childhood adversity elevated AUD probability among civilian women to levels exhibited by Veteran women. Among men, Veterans with more childhood adversity were more likely than civilians to have AUD, and less likely to have DUD. Childhood adversity alters the gender gap in AUD and DUD risk, and in ways that are different for Veterans compared with civilians. Department of Defense, Veterans Affairs, and community health centers can prevent and ameliorate the harmful effects of childhood adversity by adapting existing behavioral health efforts to be trauma informed, Veteran sensitive, and gender tailored.

Global Transcriptome Sequencing Reveals Molecular Profiles of Summer Diapause Induction Stage of Onion Maggot, Delia antiqua (Diptera: Anthomyiidae)

PubMed Central

Ren, Shuang; Hao, You-Jin; Chen, Bin; Yin, You-Ping

2017-01-01

The onion maggot, Delia antiqua, is a worldwide subterranean pest and can enter diapause during the summer and winter seasons. The molecular regulation of the ontogenesis transition remains largely unknown. Here we used high-throughput RNA sequencing to identify candidate genes and processes linked to summer diapause (SD) induction by comparing the transcriptome differences between the most sensitive larval developmental stage of SD and nondiapause (ND). Nine pairwise comparisons were performed, and significantly differentially regulated transcripts were identified. Several functional terms related to lipid, carbohydrate, and energy metabolism, environmental adaption, immune response, and aging were enriched during the most sensitive SD induction period. A subset of genes, including circadian clock genes, were expressed differentially under diapause induction conditions, and there was much more variation in the most sensitive period of ND- than SD-destined larvae. These expression variations probably resulted in a deep restructuring of metabolic pathways. Potential regulatory elements of SD induction including genes related to lipid, carbohydrate, energy metabolism, and environmental adaption. Collectively, our results suggest the circadian clock is one of the key drivers for integrating environmental signals into the SD induction. Our transcriptome analysis provides insight into the fundamental role of the circadian clock in SD induction in this important model insect species, and contributes to the in-depth elucidation of the molecular regulation mechanism of insect diapause induction. PMID:29158334

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

Population-structure and genetic diversity in a haplochromine cichlid fish [corrected] of a satellite lake of Lake Victoria.

PubMed

Abila, Romulus; Barluenga, Marta; Engelken, Johannes; Meyer, Axel; Salzburger, Walter

2004-09-01

The approximately 500 species of the cichlid fish species flock of Lake Victoria, East Africa, have evolved in a record-setting 100,000 years and represent one of the largest adaptive radiations. We examined the population structure of the endangered cichlid species Xystichromis phytophagus from Lake Kanyaboli, a satellite lake to Lake Victoria in the Kenyan Yala wetlands. Two sets of molecular markers were analysed--sequences of the mitochondrial control region as well as six microsatellite loci--and revealed surprisingly high levels of genetic variability in this species. Mitochondrial DNA sequences failed to detect population structuring among the three sample populations. A model-based population assignment test based on microsatellite data revealed that the three populations most probably aggregate into a larger panmictic population. However, values of population pairwise FST indicated moderate levels of genetic differentiation for one population. Eleven distinct mitochondrial haplotypes were found among 205 specimens of X. phytophagus, a relatively high number compared to the total number of 54 haplotypes that were recovered from hundreds of specimens of the entire cichlid species flock of Lake Victoria. Most of the X. phytophagus mitochondrial DNA haplotypes were absent from the main Lake Victoria, corroborating the putative importance of satellite lakes as refugia for haplochromine cichlids that went extinct from the main lake in the last decades and possibly during the Late Pleistocene desiccation of Lake Victoria.

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

NASA Astrophysics Data System (ADS)

Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

2016-09-01

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

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

Decadal trends in a coral community and evidence of changed disturbance regime

NASA Astrophysics Data System (ADS)

Wakeford, M.; Done, T. J.; Johnson, C. R.

2008-03-01

A 23 year data set (1981 2003 inclusive) and the spatially explicit individual-based model “Compete©” were used to investigate the implications of changing disturbance frequency on cover and taxonomic composition of a shallow coral community at Lizard Island, Australia. Near-vertical in situ stereo-photography was used to estimate rates of coral growth, mortality, recruitment and outcomes of pair-wise competitive interactions for 17 physiognomic groups of hard and soft corals. These data were used to parameterise the model, and to quantify impacts of three acute disturbance events that caused significant coral mortality: 1982—a combination of coral bleaching and Crown-of-Thorns starfish; 1990—cyclone waves; and 1996—Crown-of-Thorns starfish. Predicted coral community trajectories were not sensitive to the outcomes of competitive interactions (probably because average coral cover was only 32% and there was strong vertical separation among established corals) or to major changes in recruitment rates. The model trajectory of coral cover matched the observed trajectory accurately until the 1996 disturbance, but only if all coral mortality was confined to the 3 years of acute disturbance. Beyond that date (1997 2003), when the observed community failed to recover, it was necessary to introduce annual chronic background mortality to obtain a good match between modelled and observed coral cover. This qualitative switch in the model may reflect actual loss of resilience in the real community. Simulated over a century, an 8 year disturbance frequency most closely reproduced the mean community composition observed in the field prior to major disturbance events. Shorter intervals between disturbances led to reduced presence of the dominant hard coral groups, and a gradual increase in the slow growing, more resilient soft corals, while longer intervals (up to 16 years) resulted in monopolization by the fastest growing table coral, Acropora hyacinthus.

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.

Neighborhood design and rates of walking and biking to elementary school in 34 California communities.

PubMed

Braza, Mark; Shoemaker, Wendy; Seeley, Anne

2004-01-01

This study evaluates the relationship between neighborhood design and rates of students walking and biking to elementary school. Pairwise correlations and multiple regression models were estimated based on a cross-sectional study of elementary schools and their surrounding neighborhoods. Setting and Subjects. Thirty-four (23%) of 150 California public elementary schools holding October 1999 Walk to School Day events participated in the study. Teachers asked fifth-grade students how they arrived to school 1 week before Walk to School Day. 1990 U.S. Census data measured population density and number of intersections per street mile, whereas 1998-1999 California Department of Education data measured school size, the percentage of students receiving public welfare, and the percentage of students of various ethnicities. Population density (p = .000) and school size (p = .053) were significantly associated with walking and biking rates in regression models controlling for number of intersections per street mile, the percentage of students receiving public welfare, and the percentage of students of various ethnicities. The number of intersections per street mile was associated with walking and biking rates in pairwise correlations (p = .003) but not in regression models. The results support the hypothesis that the walking and biking rates are higher in denser neighborhoods and to smaller schools but do not support the hypothesis that rates are higher in neighborhoods with a high number of intersections per street mile. We suggest that detailed data for a larger sample of students would allow statistical models to isolate the effect of specific design characteristics.

Interspecific Tests of Allelism Reveal the Evolutionary Timing and Pattern of Accumulation of Reproductive Isolation Mutations

PubMed Central

Sherman, Natasha A.; Victorine, Anna; Wang, Richard J.; Moyle, Leonie C.

2014-01-01

Despite extensive theory, little is known about the empirical accumulation and evolutionary timing of mutations that contribute to speciation. Here we combined QTL (Quantitative Trait Loci) analyses of reproductive isolation, with information on species evolutionary relationships, to reconstruct the order and timing of mutations contributing to reproductive isolation between three plant (Solanum) species. To evaluate whether reproductive isolation QTL that appear to coincide in more than one species pair are homologous, we used cross-specific tests of allelism and found evidence for both homologous and lineage-specific (non-homologous) alleles at these co-localized loci. These data, along with isolation QTL unique to single species pairs, indicate that >85% of isolation-causing mutations arose later in the history of divergence between species. Phylogenetically explicit analyses of these data support non-linear models of accumulation of hybrid incompatibility, although the specific best-fit model differs between seed (pairwise interactions) and pollen (multi-locus interactions) sterility traits. Our findings corroborate theory that predicts an acceleration (‘snowballing’) in the accumulation of isolation loci as lineages progressively diverge, and suggest different underlying genetic bases for pollen versus seed sterility. Pollen sterility in particular appears to be due to complex genetic interactions, and we show this is consistent with a snowball model where later arising mutations are more likely to be involved in pairwise or multi-locus interactions that specifically involve ancestral alleles, compared to earlier arising mutations. PMID:25211473

Dynamically heterogenous partitions and phylogenetic inference: an evaluation of analytical strategies with cytochrome b and ND6 gene sequences in cranes.

PubMed

Krajewski, C; Fain, M G; Buckley, L; King, D G

1999-11-01

ki ctes over whether molecular sequence data should be partitioned for phylogenetic analysis often confound two types of heterogeneity among partitions. We distinguish historical heterogeneity (i.e., different partitions have different evolutionary relationships) from dynamic heterogeneity (i.e., different partitions show different patterns of sequence evolution) and explore the impact of the latter on phylogenetic accuracy and precision with a two-gene, mitochondrial data set for cranes. The well-established phylogeny of cranes allows us to contrast tree-based estimates of relevant parameter values with estimates based on pairwise comparisons and to ascertain the effects of incorporating different amounts of process information into phylogenetic estimates. We show that codon positions in the cytochrome b and NADH dehydrogenase subunit 6 genes are dynamically heterogenous under both Poisson and invariable-sites + gamma-rates versions of the F84 model and that heterogeneity includes variation in base composition and transition bias as well as substitution rate. Estimates of transition-bias and relative-rate parameters from pairwise sequence comparisons were comparable to those obtained as tree-based maximum likelihood estimates. Neither rate-category nor mixed-model partitioning strategies resulted in a loss of phylogenetic precision relative to unpartitioned analyses. We suggest that weighted-average distances provide a computationally feasible alternative to direct maximum likelihood estimates of phylogeny for mixed-model analyses of large, dynamically heterogenous data sets. Copyright 1999 Academic Press.

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.

Network reciprocity by coexisting learning and teaching strategies

NASA Astrophysics Data System (ADS)

Tanimoto, Jun; Brede, Markus; Yamauchi, Atsuo

2012-03-01

We propose a network reciprocity model in which an agent probabilistically adopts learning or teaching strategies. In the learning adaptation mechanism, an agent may copy a neighbor's strategy through Fermi pairwise comparison. The teaching adaptation mechanism involves an agent imposing its strategy on a neighbor. Our simulations reveal that the reciprocity is significantly affected by the frequency with which learning and teaching agents coexist in a network and by the structure of the network itself.

Full-Thickness Thermal Injury Delays Wound Closure in a Murine Model

DTIC Science & Technology

2015-01-01

Wu, MS Submitted for publication June 9, 2014. Ac- cepted in revised form August 17, 2014. *Correspondence: Dental and Trauma Re- search Detachment...repeated measures ANOVA with pairwise comparison and Tukey–Kramer adjustment, using JMP statistics software (SAS, Cary , NC). Results were presented as...Microbiologist and the Director of Science, and Rodney K. Chan, MD, is a Plastic Surgeon in the Dental and Trauma Research Detachment at US Army

Systematic chemical-genetic and chemical-chemical interaction datasets for prediction of compound synergism

PubMed Central

Wildenhain, Jan; Spitzer, Michaela; Dolma, Sonam; Jarvik, Nick; White, Rachel; Roy, Marcia; Griffiths, Emma; Bellows, David S.; Wright, Gerard D.; Tyers, Mike

2016-01-01

The network structure of biological systems suggests that effective therapeutic intervention may require combinations of agents that act synergistically. However, a dearth of systematic chemical combination datasets have limited the development of predictive algorithms for chemical synergism. Here, we report two large datasets of linked chemical-genetic and chemical-chemical interactions in the budding yeast Saccharomyces cerevisiae. We screened 5,518 unique compounds against 242 diverse yeast gene deletion strains to generate an extended chemical-genetic matrix (CGM) of 492,126 chemical-gene interaction measurements. This CGM dataset contained 1,434 genotype-specific inhibitors, termed cryptagens. We selected 128 structurally diverse cryptagens and tested all pairwise combinations to generate a benchmark dataset of 8,128 pairwise chemical-chemical interaction tests for synergy prediction, termed the cryptagen matrix (CM). An accompanying database resource called ChemGRID was developed to enable analysis, visualisation and downloads of all data. The CGM and CM datasets will facilitate the benchmarking of computational approaches for synergy prediction, as well as chemical structure-activity relationship models for anti-fungal drug discovery. PMID:27874849

Evolutionary games in the multiverse

PubMed Central

Gokhale, Chaitanya S.; Traulsen, Arne

2010-01-01

Evolutionary game dynamics of two players with two strategies has been studied in great detail. These games have been used to model many biologically relevant scenarios, ranging from social dilemmas in mammals to microbial diversity. Some of these games may, in fact, take place between a number of individuals and not just between two. Here we address one-shot games with multiple players. As long as we have only two strategies, many results from two-player games can be generalized to multiple players. For games with multiple players and more than two strategies, we show that statements derived for pairwise interactions no longer hold. For two-player games with any number of strategies there can be at most one isolated internal equilibrium. For any number of players with any number of strategies , there can be at most isolated internal equilibria. Multiplayer games show a great dynamical complexity that cannot be captured based on pairwise interactions. Our results hold for any game and can easily be applied to specific cases, such as public goods games or multiplayer stag hunts. PMID:20212124

Evolution of genetic architecture under directional selection.

PubMed

Hansen, Thomas F; Alvarez-Castro, José M; Carter, Ashley J R; Hermisson, Joachim; Wagner, Günter P

2006-08-01

We investigate the multilinear epistatic model under mutation-limited directional selection. We confirm previous results that only directional epistasis, in which genes on average reinforce or diminish each other's effects, contribute to the initial evolution of mutational effects. Thus, either canalization or decanalization can occur under directional selection, depending on whether positive or negative epistasis is prevalent. We then focus on the evolution of the epistatic coefficients themselves. In the absence of higher-order epistasis, positive pairwise epistasis will tend to weaken relative to additive effects, while negative pairwise epistasis will tend to become strengthened. Positive third-order epistasis will counteract these effects, while negative third-order epistasis will reinforce them. More generally, gene interactions of all orders have an inherent tendency for negative changes under directional selection, which can only be modified by higher-order directional epistasis. We identify three types of nonadditive quasi-equilibrium architectures that, although not strictly stable, can be maintained for an extended time: (1) nondirectional epistatic architectures; (2) canalized architectures with strong epistasis; and (3) near-additive architectures in which additive effects keep increasing relative to epistasis.

Potential linkage for schizophrenia on chromosome 22q12-q13: A replication study

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

Schwab, S.G.; Bondy, B.; Wildenauer, D.B.

1995-10-09

In an attempt to replicate a potential linkage on chromosome 22q12-q13.1 reported by Pulver et al., we have analyzed 4 microsatellite markers which span this chromosomal region, including the IL2RB locus, for linkage with schizophrenia in 30 families from Israel and Germany. Linkage analysis by pairwise lod score analysis as well as by multipoint analysis did not provide evidence for a single major gene locus. However, a lod score of Z{sub max} = 0.612 was obtained for a dominant model of inheritance with the marker D22S304 at recombination fraction 0.2 by pairwise analysis. In addition, using a nonparametric method, sibmore » pair analysis, a P value of 0.068 corresponding to a lod score of 0.48 was obtained for this marker. This finding, together with those of Pulver et al., is suggestive of a genetic factor in this region, predisposing for schizophrenia in a subset of families. Further studies using nonparametric methods should be conducted in order to clarify this point. 32 refs., 1 fig., 4 tabs.« less

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.

Testing Pairwise Association between Spatially Autocorrelated Variables: A New Approach Using Surrogate Lattice Data

PubMed Central

Deblauwe, Vincent; Kennel, Pol; Couteron, Pierre

2012-01-01

Background Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images), such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r) is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. Methodology/Principal Findings The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions) of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform). Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. Conclusions/Significance The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy). We explore the potential of the method for association tests involving a lattice of binary data and discuss its potential for validation of species distribution models. An implementation of the method in Java for the generation of wavelet-based surrogates is available online as supporting material. PMID:23144961

High-throughput prediction of Acacia and eucalypt lignin syringyl/guaiacyl content using FT-Raman spectroscopy and partial least squares modeling

DOE PAGES

Lupoi, Jason S.; Healey, Adam; Singh, Seema; ...

2015-01-16

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acaciamore » and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. In conclusion, this research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.« less

Conditional High-Order Boltzmann Machines for Supervised Relation Learning.

PubMed

Huang, Yan; Wang, Wei; Wang, Liang; Tan, Tieniu

2017-09-01

Relation learning is a fundamental problem in many vision tasks. Recently, high-order Boltzmann machine and its variants have shown their great potentials in learning various types of data relation in a range of tasks. But most of these models are learned in an unsupervised way, i.e., without using relation class labels, which are not very discriminative for some challenging tasks, e.g., face verification. In this paper, with the goal to perform supervised relation learning, we introduce relation class labels into conventional high-order multiplicative interactions with pairwise input samples, and propose a conditional high-order Boltzmann Machine (CHBM), which can learn to classify the data relation in a binary classification way. To be able to deal with more complex data relation, we develop two improved variants of CHBM: 1) latent CHBM, which jointly performs relation feature learning and classification, by using a set of latent variables to block the pathway from pairwise input samples to output relation labels and 2) gated CHBM, which untangles factors of variation in data relation, by exploiting a set of latent variables to multiplicatively gate the classification of CHBM. To reduce the large number of model parameters generated by the multiplicative interactions, we approximately factorize high-order parameter tensors into multiple matrices. Then, we develop efficient supervised learning algorithms, by first pretraining the models using joint likelihood to provide good parameter initialization, and then finetuning them using conditional likelihood to enhance the discriminant ability. We apply the proposed models to a series of tasks including invariant recognition, face verification, and action similarity labeling. Experimental results demonstrate that by exploiting supervised relation labels, our models can greatly improve the performance.

Tumor segmentation on FDG-PET: usefulness of locally connected conditional random fields

NASA Astrophysics Data System (ADS)

Nishio, Mizuho; Kono, Atsushi K.; Koyama, Hisanobu; Nishii, Tatsuya; Sugimura, Kazuro

2015-03-01

This study aimed to develop software for tumor segmentation on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET). To segment the tumor from the background, we used graph cut, whose segmentation energy was generally divided into two terms: the unary and pairwise terms. Locally connected conditional random fields (LCRF) was proposed for the pairwise term. In LCRF, a three-dimensional cubic window with length L was set for each voxel, and voxels within the window were considered for the pairwise term. To evaluate our method, 64 clinically suspected metastatic bone tumors were tested, which were revealed by FDG-PET. To obtain ground truth, the tumors were manually delineated via consensus of two board-certified radiologists. To compare the LCRF accuracy, other types of segmentation were also applied such as region-growing based on 35%, 40%, and 45% of the tumor maximum standardized uptake value (RG35, RG40, and RG45, respectively), SLIC superpixels (SS), and region-based active contour models (AC). To validate the tumor segmentation accuracy, a dice similarity coefficient (DSC) was calculated between manual segmentation and result of each technique. The DSC difference was tested using the Wilcoxon signed rank test. The mean DSCs of LCRF at L = 3, 5, 7, and 9 were 0.784, 0.801, 0.809, and 0.812, respectively. The mean DSCs of other techniques were RG35, 0.633; RG40, 0.675; RG45, 0.689; SS, 0.709; and AC, 0.758. The DSC differences between LCRF and other techniques were statistically significant (p <0.05). In conclusion, tumor segmentation was more reliably performed with LCRF relative to other techniques.

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.

Bimodal fuzzy analytic hierarchy process (BFAHP) for coronary heart disease risk assessment.

PubMed

Sabahi, Farnaz

2018-04-04

Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important especially when applied to the risk of being affected by deadly diseases such as coronary heart disease (CHD). CHD risk assessment is a stochastic, uncertain, and highly dynamic process influenced by various known and unknown variables. In recent years, there has been a great interest in fuzzy analytic hierarchy process (FAHP), a popular methodology for dealing with uncertainty in MCDM. This paper proposes a new FAHP, bimodal fuzzy analytic hierarchy process (BFAHP) that augments two aspects of knowledge, probability and validity, to fuzzy numbers to better deal with uncertainty. In BFAHP, fuzzy validity is computed by aggregating the validities of relevant risk factors based on expert knowledge and collective intelligence. By considering both soft and statistical data, we compute the fuzzy probability of risk factors using the Bayesian formulation. In BFAHP approach, these fuzzy validities and fuzzy probabilities are used to construct a reciprocal comparison matrix. We then aggregate fuzzy probabilities and fuzzy validities in a pairwise manner for each risk factor and each alternative. BFAHP decides about being affected and not being affected by ranking of high and low risks. For evaluation, the proposed approach is applied to the risk of being affected by CHD using a real dataset of 152 patients of Iranian hospitals. Simulation results confirm that adding validity in a fuzzy manner can accrue more confidence of results and clinically useful especially in the face of incomplete information when compared with actual results. Applying the proposed BFAHP on CHD risk assessment of the dataset, it yields high accuracy rate above 85% for correct prediction. In addition, this paper recognizes that the risk factors of diastolic blood pressure in men and high-density lipoprotein in women are more important in CHD than other risk factors. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

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

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.

Assessing compositional variability through graphical analysis and Bayesian statistical approaches: case studies on transgenic crops.

PubMed

Harrigan, George G; Harrison, Jay M

2012-01-01

New transgenic (GM) crops are subjected to extensive safety assessments that include compositional comparisons with conventional counterparts as a cornerstone of the process. The influence of germplasm, location, environment, and agronomic treatments on compositional variability is, however, often obscured in these pair-wise comparisons. Furthermore, classical statistical significance testing can often provide an incomplete and over-simplified summary of highly responsive variables such as crop composition. In order to more clearly describe the influence of the numerous sources of compositional variation we present an introduction to two alternative but complementary approaches to data analysis and interpretation. These include i) exploratory data analysis (EDA) with its emphasis on visualization and graphics-based approaches and ii) Bayesian statistical methodology that provides easily interpretable and meaningful evaluations of data in terms of probability distributions. The EDA case-studies include analyses of herbicide-tolerant GM soybean and insect-protected GM maize and soybean. Bayesian approaches are presented in an analysis of herbicide-tolerant GM soybean. Advantages of these approaches over classical frequentist significance testing include the more direct interpretation of results in terms of probabilities pertaining to quantities of interest and no confusion over the application of corrections for multiple comparisons. It is concluded that a standardized framework for these methodologies could provide specific advantages through enhanced clarity of presentation and interpretation in comparative assessments of crop composition.

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.

Semiblind channel estimation for MIMO-OFDM systems

NASA Astrophysics Data System (ADS)

Chen, Yi-Sheng; Song, Jyu-Han

2012-12-01

This article proposes a semiblind channel estimation method for multiple-input multiple-output orthogonal frequency-division multiplexing systems based on circular precoding. Relying on the precoding scheme at the transmitters, the autocorrelation matrix of the received data induces a structure relating the outer product of the channel frequency response matrix and precoding coefficients. This structure makes it possible to extract information about channel product matrices, which can be used to form a Hermitian matrix whose positive eigenvalues and corresponding eigenvectors yield the channel impulse response matrix. This article also tests the resistance of the precoding design to finite-sample estimation errors, and explores the effects of the precoding scheme on channel equalization by performing pairwise error probability analysis. The proposed method is immune to channel zero locations, and is reasonably robust to channel order overestimation. The proposed method is applicable to the scenarios in which the number of transmitters exceeds that of the receivers. Simulation results demonstrate the performance of the proposed method and compare it with some existing methods.

Constructing STR multiplexes for individual identification of Hungarian red deer.

PubMed

Szabolcsi, Zoltan; Egyed, Balazs; Zenke, Petra; Padar, Zsolt; Borsy, Adrienn; Steger, Viktor; Pasztor, Erzsebet; Csanyi, Sandor; Buzas, Zsuzsanna; Orosz, Laszlo

2014-07-01

Red deer is the most valuable game of the fauna in Hungary, and there is a strong need for genetic identification of individuals. For this purpose, 10 tetranucleotide STR markers were developed and amplified in two 5-plex systems. The study presented here includes the flanking region sequence analysis and the allele nomenclature of the 10 loci as well as the PCR optimization of the DeerPlex I and II. LD pairwise tests and cross-species similarity analyses showed the 10 loci to be independently inherited. Considerable levels of genetic differences between two subpopulations were recorded, and F(ST) was 0.034 using AMOVA. The average probability of identity (PI(ave)) was at the value of 2.6736 × 10(-15). This low value for PI(ave) nearly eliminates false identification. An illegal hunting case solved by DeerPlex is described herein. The calculated likelihood ratio (LR) illustrates the potential of the 10 red deer microsatellite markers for forensic investigations. © 2014 American Academy of Forensic Sciences.

A machine learning approach for ranking clusters of docked protein‐protein complexes by pairwise cluster comparison

PubMed Central

Pfeiffenberger, Erik; Chaleil, Raphael A.G.; Moal, Iain H.

2017-01-01

ABSTRACT Reliable identification of near‐native poses of docked protein–protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein–protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near‐native from incorrect clusters. The results show that our approach is able to identify clusters containing near‐native protein–protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528–543. © 2016 Wiley Periodicals, Inc. PMID:27935158

Genetic parameters for different growth scales in GIFT strain of Nile tilapia (Oreochromis niloticus).

PubMed

He, J; Gao, H; Xu, P; Yang, R

2015-12-01

Body weight, length, width and depth at two growth stages were observed for a total of 5015 individuals of GIFT strain, along with a pedigree including 5588 individuals from 104 sires and 162 dams was collected. Multivariate animal models and a random regression model were used to genetically analyse absolute and relative growth scales of these growth traits. In absolute growth scale, the observed growth traits had moderate heritabilities ranging from 0.321 to 0.576, while pairwise ratios between body length, width and depth were lowly inherited and maximum heritability was only 0.146 for length/depth. All genetic correlations were above 0.5 between pairwise growth traits and genetic correlation between length/width and length/depth varied between both growth stages. Based on those estimates, selection index of multiple traits of interest can be formulated in future breeding program to improve genetically body weight and morphology of the GIFT strain. In relative growth scale, heritabilities in relative growths of body length, width and depth to body weight were 0.257, 0.412 and 0.066, respectively, while genetic correlations among these allometry scalings were above 0.8. Genetic analysis for joint allometries of body weight to body length, width and depth will contribute to genetically regulate the growth rate between body shape and body weight. © 2015 Blackwell Verlag GmbH.

Female elk contacts are neither frequency nor density dependent

USGS Publications Warehouse

Cross, Paul C.; Creech, Tyler G.; Ebinger, Michael R.; Manlove, Kezia R.; Irvine, Kathryn M.; Henningsen, John C.; Rogerson, Jared D.; Scurlock, Brandon M.; Creely, Scott

2013-01-01

Identifying drivers of contact rates among individuals is critical to understanding disease dynamics and implementing targeted control measures. We studied the interaction patterns of 149 female elk (Cervus canadensis) distributed across five different regions of western Wyoming over three years, defining a contact as an approach within one body length (∼2 m). Using hierarchical models that account for correlations within individuals, pairs, and groups, we found that pairwise contact rates within a group declined by a factor of three as group sizes increased 33-fold. Per capita contact rates, however, increased with group size according to a power function, such that female elk contact rates fell in between the predictions of density- or frequency-dependent disease models. We found similar patterns for the duration of contacts. Our results suggest that larger elk groups are likely to play a disproportionate role in the disease dynamics of directly transmitted infections in elk. Supplemental feeding of elk had a limited impact on pairwise interaction rates and durations, but per capita rates were more than two times higher on feeding grounds. Our statistical approach decomposes the variation in contact rate into individual, dyadic, and environmental effects, and provides insight into factors that may be targeted by disease control programs. In particular, female elk contact patterns were driven more by environmental factors such as group size than by either individual or dyad effects.

Distantly related lipocalins share two conserved clusters of hydrophobic residues: use in homology modeling

PubMed Central

Adam, Benoit; Charloteaux, Benoit; Beaufays, Jerome; Vanhamme, Luc; Godfroid, Edmond; Brasseur, Robert; Lins, Laurence

2008-01-01

Background Lipocalins are widely distributed in nature and are found in bacteria, plants, arthropoda and vertebra. In hematophagous arthropods, they are implicated in the successful accomplishment of the blood meal, interfering with platelet aggregation, blood coagulation and inflammation and in the transmission of disease parasites such as Trypanosoma cruzi and Borrelia burgdorferi. The pairwise sequence identity is low among this family, often below 30%, despite a well conserved tertiary structure. Under the 30% identity threshold, alignment methods do not correctly assign and align proteins. The only safe way to assign a sequence to that family is by experimental determination. However, these procedures are long and costly and cannot always be applied. A way to circumvent the experimental approach is sequence and structure analyze. To further help in that task, the residues implicated in the stabilisation of the lipocalin fold were determined. This was done by analyzing the conserved interactions for ten lipocalins having a maximum pairwise identity of 28% and various functions. Results It was determined that two hydrophobic clusters of residues are conserved by analysing the ten lipocalin structures and sequences. One cluster is internal to the barrel, involving all strands and the 310 helix. The other is external, involving four strands and the helix lying parallel to the barrel surface. These clusters are also present in RaHBP2, a unusual "outlier" lipocalin from tick Rhipicephalus appendiculatus. This information was used to assess assignment of LIR2 a protein from Ixodes ricinus and to build a 3D model that helps to predict function. FTIR data support the lipocalin fold for this protein. Conclusion By sequence and structural analyzes, two conserved clusters of hydrophobic residues in interactions have been identified in lipocalins. Since the residues implicated are not conserved for function, they should provide the minimal subset necessary to confer the lipocalin fold. This information has been used to assign LIR2 to lipocalins and to investigate its structure/function relationship. This study could be applied to other protein families with low pairwise similarity, such as the structurally related fatty acid binding proteins or avidins. PMID:18190694

Expert Elicitations of 2100 Emission of CO2

NASA Astrophysics Data System (ADS)

Ho, Emily; Bosetti, Valentina; Budescu, David; Keller, Klaus; van Vuuren, Detlef

2017-04-01

Emission scenarios such as Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) are used intensively for climate research (e.g. climate change projections) and policy analysis. While the range of these scenarios provides an indication of uncertainty, these scenarios are typically not associated with probability values. Some studies (e.g. Vuuren et al, 2007; Gillingham et al., 2015) took a different approach associating baseline emission pathways (conditionally) with probability distributions. This paper summarizes three studies where climate change experts were asked to conduct pair-wise comparisons of possible ranges of 2100 greenhouse gas emissions and rate the relative likelihood of the ranges. The elicitation was performed under two sets of assumptions: 1) a situation where no climate policies are introduced beyond the ones already in place (baseline scenario), and 2) a situation in which countries have ratified the voluntary policies in line with the long term target embedded in the 2015 Paris Agreement. These indirect relative judgments were used to construct subjective cumulative distribution functions. We show that by using a ratio scaling method that invokes relative likelihoods of scenarios, a subjective probability distribution can be derived for each expert that expresses their beliefs in the projected greenhouse gas emissions range in 2100. This method is shown to elicit stable estimates that require minimal adjustment and is relatively invariant to the partition of the domain of interest. Experts also rated the method as being easy and intuitive to use. We also report results of a study that allowed participants to choose their own ranges of greenhouse gas emissions to remove potential anchoring bias. We discuss the implications of the use of this method for facilitating comparison and communication of beliefs among diverse users of climate science research.

Leads Detection Using Mixture Statistical Distribution Based CRF Algorithm from Sentinel-1 Dual Polarization SAR Imagery

NASA Astrophysics Data System (ADS)

Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting

2017-04-01

Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a pixel spacing of 40 meters near Prydz Bay area, East Antarctica. Main work is listed as follows: 1) A mixture statistical distribution based CRF algorithm has been developed for leads detection from Sentinel-1A dual polarization images. 2) The assessment of the proposed mixture statistical distribution based CRF method and single distribution based CRF algorithm has been presented. 3) The preferable parameters sets including statistical distributions, the aspect ratio threshold and spatial smoothing window size have been provided. In the future, the proposed algorithm will be developed for the operational Sentinel series data sets processing due to its less time consuming cost and high accuracy in leads detection.

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

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

Length-scale crossover of the hydrophobic interaction in a coarse-grained water model

NASA Astrophysics Data System (ADS)

Chaimovich, Aviel; Shell, M. Scott

2013-11-01

It has been difficult to establish a clear connection between the hydrophobic interaction among small molecules typically studied in molecular simulations (a weak, oscillatory force) and that found between large, macroscopic surfaces in experiments (a strong, monotonic force). Here, we show that both types of interaction can emerge with a simple, core-softened water model that captures water's unique pairwise structure. As in hydrophobic hydration, we find that the hydrophobic interaction manifests a length-scale dependence, exhibiting distinct driving forces in the molecular and macroscopic regimes. Moreover, the ability of this simple model to capture both regimes suggests that several features of the hydrophobic force can be understood merely through water's pair correlations.

Length-scale crossover of the hydrophobic interaction in a coarse-grained water model.

PubMed

Chaimovich, Aviel; Shell, M Scott

2013-11-01

It has been difficult to establish a clear connection between the hydrophobic interaction among small molecules typically studied in molecular simulations (a weak, oscillatory force) and that found between large, macroscopic surfaces in experiments (a strong, monotonic force). Here, we show that both types of interaction can emerge with a simple, core-softened water model that captures water's unique pairwise structure. As in hydrophobic hydration, we find that the hydrophobic interaction manifests a length-scale dependence, exhibiting distinct driving forces in the molecular and macroscopic regimes. Moreover, the ability of this simple model to capture both regimes suggests that several features of the hydrophobic force can be understood merely through water's pair correlations.

How good are indirect tests at detecting recombination in human mtDNA?

PubMed

White, Daniel James; Bryant, David; Gemmell, Neil John

2013-07-08

Empirical proof of human mitochondrial DNA (mtDNA) recombination in somatic tissues was obtained in 2004; however, a lack of irrefutable evidence exists for recombination in human mtDNA at the population level. Our inability to demonstrate convincingly a signal of recombination in population data sets of human mtDNA sequence may be due, in part, to the ineffectiveness of current indirect tests. Previously, we tested some well-established indirect tests of recombination (linkage disequilibrium vs. distance using D' and r(2), Homoplasy Test, Pairwise Homoplasy Index, Neighborhood Similarity Score, and Max χ(2)) on sequence data derived from the only empirically confirmed case of human mtDNA recombination thus far and demonstrated that some methods were unable to detect recombination. Here, we assess the performance of these six well-established tests and explore what characteristics specific to human mtDNA sequence may affect their efficacy by simulating sequence under various parameters with levels of recombination (ρ) that vary around an empirically derived estimate for human mtDNA (population parameter ρ = 5.492). No test performed infallibly under any of our scenarios, and error rates varied across tests, whereas detection rates increased substantially with ρ values > 5.492. Under a model of evolution that incorporates parameters specific to human mtDNA, including rate heterogeneity, population expansion, and ρ = 5.492, successful detection rates are limited to a range of 7-70% across tests with an acceptable level of false-positive results: the neighborhood similarity score incompatibility test performed best overall under these parameters. Population growth seems to have the greatest impact on recombination detection probabilities across all models tested, likely due to its impact on sequence diversity. The implications of our findings on our current understanding of mtDNA recombination in humans are discussed.

Peripheral chemoreceptors tune inspiratory drive via tonic expiratory neuron hubs in the medullary ventral respiratory column network.

PubMed

Segers, L S; Nuding, S C; Ott, M M; Dean, J B; Bolser, D C; O'Connor, R; Morris, K F; Lindsey, B G

2015-01-01

Models of brain stem ventral respiratory column (VRC) circuits typically emphasize populations of neurons, each active during a particular phase of the respiratory cycle. We have proposed that "tonic" pericolumnar expiratory (t-E) neurons tune breathing during baroreceptor-evoked reductions and central chemoreceptor-evoked enhancements of inspiratory (I) drive. The aims of this study were to further characterize the coordinated activity of t-E neurons and test the hypothesis that peripheral chemoreceptors also modulate drive via inhibition of t-E neurons and disinhibition of their inspiratory neuron targets. Spike trains of 828 VRC neurons were acquired by multielectrode arrays along with phrenic nerve signals from 22 decerebrate, vagotomized, neuromuscularly blocked, artificially ventilated adult cats. Forty-eight of 191 t-E neurons fired synchronously with another t-E neuron as indicated by cross-correlogram central peaks; 32 of the 39 synchronous pairs were elements of groups with mutual pairwise correlations. Gravitational clustering identified fluctuations in t-E neuron synchrony. A network model supported the prediction that inhibitory populations with spike synchrony reduce target neuron firing probabilities, resulting in offset or central correlogram troughs. In five animals, stimulation of carotid chemoreceptors evoked changes in the firing rates of 179 of 240 neurons. Thirty-two neuron pairs had correlogram troughs consistent with convergent and divergent t-E inhibition of I cells and disinhibitory enhancement of drive. Four of 10 t-E neurons that responded to sequential stimulation of peripheral and central chemoreceptors triggered 25 cross-correlograms with offset features. The results support the hypothesis that multiple afferent systems dynamically tune inspiratory drive in part via coordinated t-E neurons. Copyright © 2015 the American Physiological Society.

Cost-effectiveness of non-vitamin K antagonist oral anticoagulants for atrial fibrillation in Portugal.

PubMed

Costa, João; Fiorentino, Francesca; Caldeira, Daniel; Inês, Mónica; Lopes Pereira, Catarina; Pinheiro, Luís; Vaz-Carneiro, António; Borges, Margarida; Gouveia, Miguel

2015-12-01

Recently, three novel non-vitamin K antagonist oral anticoagulants received approval for reimbursement in Portugal for patients with non-valvular atrial fibrillation (AF). It is therefore important to evaluate the relative cost-effectiveness of these new oral anticoagulants in Portuguese AF patients. A Markov model was used to analyze disease progression over a lifetime horizon. Relative efficacy data for stroke (ischemic and hemorrhagic), bleeding (intracranial, other major bleeding and clinically relevant non-major bleeding), myocardial infarction and treatment discontinuation were obtained by pairwise indirect comparisons between apixaban, dabigatran and rivaroxaban using warfarin as a common comparator. Data on resource use were obtained from the database of diagnosis-related groups and an expert panel. Model outputs included life years gained, quality-adjusted life years (QALYs), direct healthcare costs and incremental cost-effectiveness ratios (ICERs). Apixaban provided the most life years gained and QALYs. The ICERs of apixaban compared to warfarin and dabigatran were €5529/QALY and €9163/QALY, respectively. Apixaban was dominant over rivaroxaban (greater health gains and lower costs). The results were robust over a wide range of inputs in sensitivity analyses. Apixaban had a 70% probability of being cost-effective (at a threshold of €20 000/QALY) compared to all the other therapeutic options. Apixaban is a cost-effective alternative to warfarin and dabigatran and is dominant over rivaroxaban in AF patients from the perspective of the Portuguese national healthcare system. These conclusions are based on indirect comparisons, but despite this limitation, the information is useful for healthcare decision-makers. Copyright © 2015 Sociedade Portuguesa de Cardiologia. Published by Elsevier España. All rights reserved.

Partitioning the Genetic Diversity of a Virus Family: Approach and Evaluation through a Case Study of Picornaviruses

PubMed Central

Lauber, Chris

2012-01-01

The recent advent of genome sequences as the only source available to classify many newly discovered viruses challenges the development of virus taxonomy by expert virologists who traditionally rely on extensive virus characterization. In this proof-of-principle study, we address this issue by presenting a computational approach (DEmARC) to classify viruses of a family into groups at hierarchical levels using a sole criterion—intervirus genetic divergence. To quantify genetic divergence, we used pairwise evolutionary distances (PEDs) estimated by maximum likelihood inference on a multiple alignment of family-wide conserved proteins. PEDs were calculated for all virus pairs, and the resulting distribution was modeled via a mixture of probability density functions. The model enables the quantitative inference of regions of distance discontinuity in the family-wide PED distribution, which define the levels of hierarchy. For each level, a limit on genetic divergence, below which two viruses join the same group, was objectively selected among a set of candidates by minimizing violations of intragroup PEDs to the limit. In a case study, we applied the procedure to hundreds of genome sequences of picornaviruses and extensively evaluated it by modulating four key parameters. It was found that the genetics-based classification largely tolerates variations in virus sampling and multiple alignment construction but is affected by the choice of protein and the measure of genetic divergence. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3905–3915, 2012), we analyze the substantial insight gained with the genetics-based classification approach by comparing it with the expert-based picornavirus taxonomy. PMID:22278230

How Good Are Indirect Tests at Detecting Recombination in Human mtDNA?

PubMed Central

White, Daniel James; Bryant, David; Gemmell, Neil John

2013-01-01

Empirical proof of human mitochondrial DNA (mtDNA) recombination in somatic tissues was obtained in 2004; however, a lack of irrefutable evidence exists for recombination in human mtDNA at the population level. Our inability to demonstrate convincingly a signal of recombination in population data sets of human mtDNA sequence may be due, in part, to the ineffectiveness of current indirect tests. Previously, we tested some well-established indirect tests of recombination (linkage disequilibrium vs. distance using D′ and r2, Homoplasy Test, Pairwise Homoplasy Index, Neighborhood Similarity Score, and Max χ2) on sequence data derived from the only empirically confirmed case of human mtDNA recombination thus far and demonstrated that some methods were unable to detect recombination. Here, we assess the performance of these six well-established tests and explore what characteristics specific to human mtDNA sequence may affect their efficacy by simulating sequence under various parameters with levels of recombination (ρ) that vary around an empirically derived estimate for human mtDNA (population parameter ρ = 5.492). No test performed infallibly under any of our scenarios, and error rates varied across tests, whereas detection rates increased substantially with ρ values > 5.492. Under a model of evolution that incorporates parameters specific to human mtDNA, including rate heterogeneity, population expansion, and ρ = 5.492, successful detection rates are limited to a range of 7−70% across tests with an acceptable level of false-positive results: the neighborhood similarity score incompatibility test performed best overall under these parameters. Population growth seems to have the greatest impact on recombination detection probabilities across all models tested, likely due to its impact on sequence diversity. The implications of our findings on our current understanding of mtDNA recombination in humans are discussed. PMID:23665874

Cannibalism as an interacting phenotype: precannibalistic aggression is influenced by social partners in the endangered Socorro Isopod (Thermosphaeroma thermophilum).

PubMed

Bleakley, B H; Welter, S M; McCauley-Cole, K; Shuster, S M; Moore, A J

2013-04-01

Models for the evolution of cannibalism highlight the importance of asymmetries between individuals in initiating cannibalistic attacks. Studies may include measures of body size but typically group individuals into size/age classes or compare populations. Such broad comparisons may obscure the details of interactions that ultimately determine how socially contingent characteristics evolve. We propose that understanding cannibalism is facilitated by using an interacting phenotypes perspective that includes the influences of the phenotype of a social partner on the behaviour of a focal individual and focuses on variation in individual pairwise interactions. We investigated how relative body size, a composite trait between a focal individual and its social partner, and the sex of the partners influenced precannibalistic aggression in the endangered Socorro isopod, Thermosphaeroma thermophilum. We also investigated whether differences in mating interest among males and females influenced cannibalism in mixed sex pairs. We studied these questions in three populations that differ markedly in range of body size and opportunities for interactions among individuals. We found that relative body size influences the probability of and latency to attack. We observed differences in the likelihood of and latency to attack based on both an individual's sex and the sex of its partner but found no evidence of sexual conflict. The instigation of precannibalistic aggression in these isopods is therefore a property of both an individual and its social partner. Our results suggest that interacting phenotype models would be improved by incorporating a new conditional ψ, which describes the strength of a social partner's influence on focal behaviour. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Peripheral chemoreceptors tune inspiratory drive via tonic expiratory neuron hubs in the medullary ventral respiratory column network

PubMed Central

Segers, L. S.; Nuding, S. C.; Ott, M. M.; Dean, J. B.; Bolser, D. C.; O'Connor, R.; Morris, K. F.

2014-01-01

Models of brain stem ventral respiratory column (VRC) circuits typically emphasize populations of neurons, each active during a particular phase of the respiratory cycle. We have proposed that “tonic” pericolumnar expiratory (t-E) neurons tune breathing during baroreceptor-evoked reductions and central chemoreceptor-evoked enhancements of inspiratory (I) drive. The aims of this study were to further characterize the coordinated activity of t-E neurons and test the hypothesis that peripheral chemoreceptors also modulate drive via inhibition of t-E neurons and disinhibition of their inspiratory neuron targets. Spike trains of 828 VRC neurons were acquired by multielectrode arrays along with phrenic nerve signals from 22 decerebrate, vagotomized, neuromuscularly blocked, artificially ventilated adult cats. Forty-eight of 191 t-E neurons fired synchronously with another t-E neuron as indicated by cross-correlogram central peaks; 32 of the 39 synchronous pairs were elements of groups with mutual pairwise correlations. Gravitational clustering identified fluctuations in t-E neuron synchrony. A network model supported the prediction that inhibitory populations with spike synchrony reduce target neuron firing probabilities, resulting in offset or central correlogram troughs. In five animals, stimulation of carotid chemoreceptors evoked changes in the firing rates of 179 of 240 neurons. Thirty-two neuron pairs had correlogram troughs consistent with convergent and divergent t-E inhibition of I cells and disinhibitory enhancement of drive. Four of 10 t-E neurons that responded to sequential stimulation of peripheral and central chemoreceptors triggered 25 cross-correlograms with offset features. The results support the hypothesis that multiple afferent systems dynamically tune inspiratory drive in part via coordinated t-E neurons. PMID:25343784

Structured prediction models for RNN based sequence labeling in clinical text.

PubMed

Jagannatha, Abhyuday N; Yu, Hong

2016-11-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies for structured prediction in order to improve the exact phrase detection of various medical entities.

Structured prediction models for RNN based sequence labeling in clinical text

PubMed Central

Jagannatha, Abhyuday N; Yu, Hong

2016-01-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies1 for structured prediction in order to improve the exact phrase detection of various medical entities. PMID:28004040

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

A New Framework for Analysis of Coevolutionary Systems-Directed Graph Representation and Random Walks.

PubMed

Chong, Siang Yew; Tiňo, Peter; He, Jun; Yao, Xin

2017-11-20

Studying coevolutionary systems in the context of simplified models (i.e., games with pairwise interactions between coevolving solutions modeled as self plays) remains an open challenge since the rich underlying structures associated with pairwise-comparison-based fitness measures are often not taken fully into account. Although cyclic dynamics have been demonstrated in several contexts (such as intransitivity in coevolutionary problems), there is no complete characterization of cycle structures and their effects on coevolutionary search. We develop a new framework to address this issue. At the core of our approach is the directed graph (digraph) representation of coevolutionary problems that fully captures structures in the relations between candidate solutions. Coevolutionary processes are modeled as a specific type of Markov chains-random walks on digraphs. Using this framework, we show that coevolutionary problems admit a qualitative characterization: a coevolutionary problem is either solvable (there is a subset of solutions that dominates the remaining candidate solutions) or not. This has an implication on coevolutionary search. We further develop our framework that provides the means to construct quantitative tools for analysis of coevolutionary processes and demonstrate their applications through case studies. We show that coevolution of solvable problems corresponds to an absorbing Markov chain for which we can compute the expected hitting time of the absorbing class. Otherwise, coevolution will cycle indefinitely and the quantity of interest will be the limiting invariant distribution of the Markov chain. We also provide an index for characterizing complexity in coevolutionary problems and show how they can be generated in a controlled manner.

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.

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

PubMed Central

Beleva Guthrie, Violeta; Masica, David L; Fraser, Andrew; Federico, Joseph; Fan, Yunfan; Camps, Manel; Karchin, Rachel

2018-01-01

Abstract The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure. PMID:29522102

Solar hydrogen by thermochemical water splitting cycles: design, modeling, and demonstration of a novel receiver/reactor for the high temperature decomposition of zno using concentrated sunlight

NASA Astrophysics Data System (ADS)

Kaiser, Zachary David Epping

Documenting the presence of rare bat species can be difficult. The current summer survey protocol for the federally endangered Indiana bat ( Myotis sodalis) requires passive acoustic sampling with directional microphones (e.g., Anabats), but there are still questions about best practices for choosing survey sites and appropriate detector models. Indiana bats are capable of foraging in an array of cover types, including structurally-complex, interior forests. Further, data acquisition among different commercially available bat detectors is likely highly variable, due to the use of proprietary microphones with different frequency responses, sensitivities, and directionality. We paired omnidirectional Wildlife Acoustic SM2BAT+ (SM2) and directional Titley Scientific Anabat SD2 (Anabat) detectors at 71 random points near Indianapolis, Indiana from May-August 2012-2013 to compare data acquisition by phonic group (low, mid, Myotis) and to determine what factors affect probability of detection and site occupancy for Indiana bats when sampling with acoustics near an active maternity colony (0.20--8.39 km away). Weatherproofing for Anabat microphones was 45° angle PVC tubes and for SM2 microphones was their foam shielding; microphones were paired at 2 m and 5 m heights. Habitat and landscape covariates were measured in the field or via ArcGIS. We adjusted file parameters to make SM2 and Anabat data comparable. Files were identified using Bat Call ID software, with visual inspection of Indiana bat calls. The effects of detector type, phonic group, height, and their interactions on mean files recorded per site were assessed using generalized estimating equations and LSD pairwise comparisons. We reduced probability of detection (p) and site occupancy (ψ) model covariates with Pearson's correlation and PCA. We used Presence 6.1 software and Akaike's Information Criteria to assess models for p and ψ. Anabats and SM2s did not perform equally. Anabats recorded more low and midrange files, but fewer Myotis files per site than SM2s. When comparing the same model of detectors, deployment height did not impact data acquisition. Weatherproofing may limit the ability of Anabats to record Myotis, but Anabat microphones may have greater detection ranges for low and midrange bats. Indiana bat detections were low for both detector types, representing only 4.4% of identifiable bat files recorded by SM2s. We detected Indiana bats at 43.7% of sampled sites and on 31.4% of detector-nights; detectability increased as "forest closure" and mean nightly temperature increased, likely due to reduced clutter and increased bat activity, respectively. Proximity to colony trees and specific cover types generally did not affect occupancy, suggesting that Indiana bats use a variety of cover types in this landscape. Omnidirectional SMX-US microphones may be more appropriate for Indiana bat surveys than directional Anabat microphones. However, we conclude that 2 nights of passive acoustic sampling per site may be insufficient for reliably detecting this species when it is present. In turn, the use of acoustic monitoring as a means to document presence or probable absence should be reassessed.

Heat transport in Rayleigh–Bénard convection and angular momentum transport in Taylor–Couette flow: a comparative study

PubMed Central

Brauckmann, Hannes J.

2017-01-01

Rayleigh–Bénard convection and Taylor–Couette flow are two canonical flows that have many properties in common. We here compare the two flows in detail for parameter values where the Nusselt numbers, i.e. the thermal transport and the angular momentum transport normalized by the corresponding laminar values, coincide. We study turbulent Rayleigh–Bénard convection in air at Rayleigh number Ra=107 and Taylor–Couette flow at shear Reynolds number ReS=2×104 for two different mean rotation rates but the same Nusselt numbers. For individual pairwise related fields and convective currents, we compare the probability density functions normalized by the corresponding root mean square values and taken at different distances from the wall. We find one rotation number for which there is very good agreement between the mean profiles of the two corresponding quantities temperature and angular momentum. Similarly, there is good agreement between the fluctuations in temperature and velocity components. For the heat and angular momentum currents, there are differences in the fluctuations outside the boundary layers that increase with overall rotation and can be related to differences in the flow structures in the boundary layer and in the bulk. The study extends the similarities between the two flows from global quantities to local quantities and reveals the effects of rotation on the transport. This article is part of the themed issue ‘Toward the development of high-fidelity models of wall turbulence at large Reynolds number’. PMID:28167575

Generating log-normal mock catalog of galaxies in redshift space

NASA Astrophysics Data System (ADS)

Agrawal, Aniket; Makiya, Ryu; Chiang, Chi-Ting; Jeong, Donghui; Saito, Shun; Komatsu, Eiichiro

2017-10-01

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear bias relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.

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.

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

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.

Hilbert-Schmidt Measure of Pairwise Quantum Discord for Three-Qubit X States

NASA Astrophysics Data System (ADS)

Daoud, M.; Laamara, R. Ahl; Seddik, S.

2015-10-01

The Hilbert-Schmidt distance between a mixed three-qubit state and its closest state is used to quantify the amount of pairwise quantum correlations in a tripartite system. Analytical expressions of geometric quantum discord are derived. A particular attention is devoted to two special classes of three-qubit X states. They include three-qubit states of W, GHZ and Bell type. We also discuss the monogamy property of geometric quantum discord in some mixed three-qubit systems.

Absolute calibration of a charge-coupled device camera with twin beams

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

Meda, A.; Ruo-Berchera, I., E-mail: i.ruoberchera@inrim.it; Degiovanni, I. P.

2014-09-08

We report on the absolute calibration of a Charge-Coupled Device (CCD) camera by exploiting quantum correlation. This method exploits a certain number of spatial pairwise quantum correlated modes produced by spontaneous parametric-down-conversion. We develop a measurement model accounting for all the uncertainty contributions, and we reach the relative uncertainty of 0.3% in low photon flux regime. This represents a significant step forward for the characterization of (scientific) CCDs used in mesoscopic light regime.

Using sobol sequences for planning computer experiments

NASA Astrophysics Data System (ADS)

Statnikov, I. N.; Firsov, G. I.

2017-12-01

Discusses the use for research of problems of multicriteria synthesis of dynamic systems method of Planning LP-search (PLP-search), which not only allows on the basis of the simulation model experiments to revise the parameter space within specified ranges of their change, but also through special randomized nature of the planning of these experiments is to apply a quantitative statistical evaluation of influence of change of varied parameters and their pairwise combinations to analyze properties of the dynamic system.Start your abstract here...

Application of the Refined Integral Method in the mathematical modeling of drug delivery from one-layer torus-shaped devices.

PubMed

Helbling, Ignacio M; Ibarra, Juan C D; Luna, Julio A

2012-02-28

A mathematical modeling of controlled release of drug from one-layer torus-shaped devices is presented. Analytical solutions based on Refined Integral Method (RIM) are derived. The validity and utility of the model are ascertained by comparison of the simulation results with matrix-type vaginal rings experimental release data reported in the literature. For the comparisons, the pair-wise procedure is used to measure quantitatively the fit of the theoretical predictions to the experimental data. A good agreement between the model prediction and the experimental data is observed. A comparison with a previously reported model is also presented. More accurate results are achieved for small A/C(s) ratios. Copyright © 2011 Elsevier B.V. All rights reserved.

Bayesian Image Segmentations by Potts Prior and Loopy Belief Propagation

NASA Astrophysics Data System (ADS)

Tanaka, Kazuyuki; Kataoka, Shun; Yasuda, Muneki; Waizumi, Yuji; Hsu, Chiou-Ting

2014-12-01

This paper presents a Bayesian image segmentation model based on Potts prior and loopy belief propagation. The proposed Bayesian model involves several terms, including the pairwise interactions of Potts models, and the average vectors and covariant matrices of Gauss distributions in color image modeling. These terms are often referred to as hyperparameters in statistical machine learning theory. In order to determine these hyperparameters, we propose a new scheme for hyperparameter estimation based on conditional maximization of entropy in the Potts prior. The algorithm is given based on loopy belief propagation. In addition, we compare our conditional maximum entropy framework with the conventional maximum likelihood framework, and also clarify how the first order phase transitions in loopy belief propagations for Potts models influence our hyperparameter estimation procedures.

Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

DOE PAGES

Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; ...

2015-06-04

Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstratemore » prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.« less

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

PubMed Central

2015-01-01

Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies. PMID:26113956

Trajectory Based Behavior Analysis for User Verification

NASA Astrophysics Data System (ADS)

Pao, Hsing-Kuo; Lin, Hong-Yi; Chen, Kuan-Ta; Fadlil, Junaidillah

Many of our activities on computer need a verification step for authorized access. The goal of verification is to tell apart the true account owner from intruders. We propose a general approach for user verification based on user trajectory inputs. The approach is labor-free for users and is likely to avoid the possible copy or simulation from other non-authorized users or even automatic programs like bots. Our study focuses on finding the hidden patterns embedded in the trajectories produced by account users. We employ a Markov chain model with Gaussian distribution in its transitions to describe the behavior in the trajectory. To distinguish between two trajectories, we propose a novel dissimilarity measure combined with a manifold learnt tuning for catching the pairwise relationship. Based on the pairwise relationship, we plug-in any effective classification or clustering methods for the detection of unauthorized access. The method can also be applied for the task of recognition, predicting the trajectory type without pre-defined identity. Given a trajectory input, the results show that the proposed method can accurately verify the user identity, or suggest whom owns the trajectory if the input identity is not provided.

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.

A Small World of Neuronal Synchrony

PubMed Central

Yu, Shan; Huang, Debin; Singer, Wolf

2008-01-01

A small-world network has been suggested to be an efficient solution for achieving both modular and global processing—a property highly desirable for brain computations. Here, we investigated functional networks of cortical neurons using correlation analysis to identify functional connectivity. To reconstruct the interaction network, we applied the Ising model based on the principle of maximum entropy. This allowed us to assess the interactions by measuring pairwise correlations and to assess the strength of coupling from the degree of synchrony. Visual responses were recorded in visual cortex of anesthetized cats, simultaneously from up to 24 neurons. First, pairwise correlations captured most of the patterns in the population's activity and, therefore, provided a reliable basis for the reconstruction of the interaction networks. Second, and most importantly, the resulting networks had small-world properties; the average path lengths were as short as in simulated random networks, but the clustering coefficients were larger. Neurons differed considerably with respect to the number and strength of interactions, suggesting the existence of “hubs” in the network. Notably, there was no evidence for scale-free properties. These results suggest that cortical networks are optimized for the coexistence of local and global computations: feature detection and feature integration or binding. PMID:18400792

A density functional approach to ferrogels

NASA Astrophysics Data System (ADS)

Cremer, P.; Heinen, M.; Menzel, A. M.; Löwen, H.

2017-07-01

Ferrogels consist of magnetic colloidal particles embedded in an elastic polymer matrix. As a consequence, their structural and rheological properties are governed by a competition between magnetic particle-particle interactions and mechanical matrix elasticity. Typically, the particles are permanently fixed within the matrix, which makes them distinguishable by their positions. Over time, particle neighbors do not change due to the fixation by the matrix. Here we present a classical density functional approach for such ferrogels. We map the elastic matrix-induced interactions between neighboring colloidal particles distinguishable by their positions onto effective pairwise interactions between indistinguishable particles similar to a ‘pairwise pseudopotential’. Using Monte-Carlo computer simulations, we demonstrate for one-dimensional dipole-spring models of ferrogels that this mapping is justified. We then use the pseudopotential as an input into classical density functional theory of inhomogeneous fluids and predict the bulk elastic modulus of the ferrogel under various conditions. In addition, we propose the use of an ‘external pseudopotential’ when one switches from the viewpoint of a one-dimensional dipole-spring object to a one-dimensional chain embedded in an infinitely extended bulk matrix. Our mapping approach paves the way to describe various inhomogeneous situations of ferrogels using classical density functional concepts of inhomogeneous fluids.

Analyzing brain networks with PCA and conditional Granger causality.

PubMed

Zhou, Zhenyu; Chen, Yonghong; Ding, Mingzhou; Wright, Paul; Lu, Zuhong; Liu, Yijun

2009-07-01

Identifying directional influences in anatomical and functional circuits presents one of the greatest challenges for understanding neural computations in the brain. Granger causality mapping (GCM) derived from vector autoregressive models of data has been employed for this purpose, revealing complex temporal and spatial dynamics underlying cognitive processes. However, the traditional GCM methods are computationally expensive, as signals from thousands of voxels within selected regions of interest (ROIs) are individually processed, and being based on pairwise Granger causality, they lack the ability to distinguish direct from indirect connectivity among brain regions. In this work a new algorithm called PCA based conditional GCM is proposed to overcome these problems. The algorithm implements the following two procedures: (i) dimensionality reduction in ROIs of interest with principle component analysis (PCA), and (ii) estimation of the direct causal influences in local brain networks, using conditional Granger causality. Our results show that the proposed method achieves greater accuracy in detecting network connectivity than the commonly used pairwise Granger causality method. Furthermore, the use of PCA components in conjunction with conditional GCM greatly reduces the computational cost relative to the use of individual voxel time series. Copyright 2009 Wiley-Liss, Inc

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.

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.

Assessment of Geographic and Host-Associated Population Variations of the Carob Moth, Ectomyelois ceratoniae, on Pomegranate, Fig, Pistachio and Walnut, Using AFLP Markers

PubMed Central

Mozaffarian, Fariba; Mardi, Mohsen; Sarafrazi, Alimorad; Nouri Ganbalani, Gadir

2008-01-01

The carob moth, Ectomyelois ceratoniae (Zeller 1839) (Lepidoptera: Pyralidae) is the most important pest of pomegranate, Punica granatum L. (Myrtales: Ponicaceae), in Iran. In this study, 6 amplified fragment length polymorphism primer combinations were used to survey the genetic structure of the geographic and putative host-associated populations of this pest in Iran. An AMOVA was performed on test populations. Pairwise differences, Mantel test, multidimensional analysis, cluster analysis and migration rate were calculated for 5 geographic populations of E. ceratoniae sharing the same host, pomegranate. In another part of the study, 3 comparisons were performed on pairwise populations that were collected on different hosts (pomegranate, fig, pistachio and walnut) in same geographic regions. The results showed high within population variation (85.51% of total variation), however geographic populations differed significantly. The Mantel test did not show correlations between genetic and geographic distances. The probable factors that affect genetic distances are discussed. Multidimensional scaling analysis, migration rate and cluster analysis on geographic populations showed that the Arsanjan population was the most different from the others while the Saveh population was more similar to the Sabzevar population. The comparisons didn't show any host fidelity in test populations. It seems that the ability of E. ceratoniae to broaden its host range with no fidelity to hosts can decrease the efficiency of common control methods that are used on pomegranate. The results of this study suggest that in spite of the effects of geographic barriers, high within-population genetic variation, migration rate and gene flow can provide the opportunity for emerging new phenotypes or behaviors in pest populations, such as broadening host range, changing egg lying places, or changing over-wintering sites to adapt to difficult conditions such as those caused by intensive control methods. PMID:20345296

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).

Capturing changes in flood risk with Bayesian approaches for flood damage assessment

NASA Astrophysics Data System (ADS)

Vogel, Kristin; Schröter, Kai; Kreibich, Heidi; Thieken, Annegret; Müller, Meike; Sieg, Tobias; Laudan, Jonas; Kienzler, Sarah; Weise, Laura; Merz, Bruno; Scherbaum, Frank

2016-04-01

Flood risk is a function of hazard as well as of exposure and vulnerability. All three components are under change over space and time and have to be considered for reliable damage estimations and risk analyses, since this is the basis for an efficient, adaptable risk management. Hitherto, models for estimating flood damage are comparatively simple and cannot sufficiently account for changing conditions. The Bayesian network approach allows for a multivariate modeling of complex systems without relying on expert knowledge about physical constraints. In a Bayesian network each model component is considered to be a random variable. The way of interactions between those variables can be learned from observations or be defined by expert knowledge. Even a combination of both is possible. Moreover, the probabilistic framework captures uncertainties related to the prediction and provides a probability distribution for the damage instead of a point estimate. The graphical representation of Bayesian networks helps to study the change of probabilities for changing circumstances and may thus simplify the communication between scientists and public authorities. In the framework of the DFG-Research Training Group "NatRiskChange" we aim to develop Bayesian networks for flood damage and vulnerability assessments of residential buildings and companies under changing conditions. A Bayesian network learned from data, collected over the last 15 years in flooded regions in the Elbe and Danube catchments (Germany), reveals the impact of many variables like building characteristics, precaution and warning situation on flood damage to residential buildings. While the handling of incomplete and hybrid (discrete mixed with continuous) data are the most challenging issues in the study on residential buildings, a similar study, that focuses on the vulnerability of small to medium sized companies, bears new challenges. Relying on a much smaller data set for the determination of the model parameters, overly complex models should be avoided. A so called Markov Blanket approach aims at the identification of the most relevant factors and constructs a Bayesian network based on those findings. With our approach we want to exploit a major advantage of Bayesian networks which is their ability to consider dependencies not only pairwise, but to capture the joint effects and interactions of driving forces. Hence, the flood damage network does not only show the impact of precaution on the building damage separately, but also reveals the mutual effects of precaution and the quality of warning for a variety of flood settings. Thus, it allows for a consideration of changing conditions and different courses of action and forms a novel and valuable tool for decision support. This study is funded by the Deutsche Forschungsgemeinschaft (DFG) within the research training program GRK 2043/1 "NatRiskChange - Natural hazards and risks in a changing world" at the University of Potsdam.

ChIP-PIT: Enhancing the Analysis of ChIP-Seq Data Using Convex-Relaxed Pair-Wise Interaction Tensor Decomposition.

PubMed

Zhu, Lin; Guo, Wei-Li; Deng, Su-Ping; Huang, De-Shuang

2016-01-01

In recent years, thanks to the efforts of individual scientists and research consortiums, a huge amount of chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experimental data have been accumulated. Instead of investigating them independently, several recent studies have convincingly demonstrated that a wealth of scientific insights can be gained by integrative analysis of these ChIP-seq data. However, when used for the purpose of integrative analysis, a serious drawback of current ChIP-seq technique is that it is still expensive and time-consuming to generate ChIP-seq datasets of high standard. Most researchers are therefore unable to obtain complete ChIP-seq data for several TFs in a wide variety of cell lines, which considerably limits the understanding of transcriptional regulation pattern. In this paper, we propose a novel method called ChIP-PIT to overcome the aforementioned limitation. In ChIP-PIT, ChIP-seq data corresponding to a diverse collection of cell types, TFs and genes are fused together using the three-mode pair-wise interaction tensor (PIT) model, and the prediction of unperformed ChIP-seq experimental results is formulated as a tensor completion problem. Computationally, we propose efficient first-order method based on extensions of coordinate descent method to learn the optimal solution of ChIP-PIT, which makes it particularly suitable for the analysis of massive scale ChIP-seq data. Experimental evaluation the ENCODE data illustrate the usefulness of the proposed model.

The Associative Structure of Memory for Multi-Element Events

PubMed Central

2013-01-01

The hippocampus is thought to be an associative memory “convergence zone,” binding together the multimodal elements of an experienced event into a single engram. This predicts a degree of dependency between the retrieval of the different elements comprising an event. We present data from a series of studies designed to address this prediction. Participants vividly imagined a series of person–location–object events, and memory for these events was assessed across multiple trials of cued retrieval. Consistent with the prediction, a significant level of dependency was found between the retrieval of different elements from the same event. Furthermore, the level of dependency was sensitive both to retrieval task, with higher dependency during cued recall than cued recognition, and to subjective confidence. We propose a simple model, in which events are stored as multiple pairwise associations between individual event elements, and dependency is captured by a common factor that varies across events. This factor may relate to between-events modulation of the strength of encoding, or to a process of within-event “pattern completion” at retrieval. The model predicts the quantitative pattern of dependency in the data when changes in the level of guessing with retrieval task and confidence are taken into account. Thus, we find direct behavioral support for the idea that memory for complex multimodal events depends on the pairwise associations of their constituent elements and that retrieval of the various elements corresponding to the same event reflects a common factor that varies from event to event. PMID:23915127

Amino Acid Properties Conserved in Molecular Evolution

PubMed Central

Rudnicki, Witold R.; Mroczek, Teresa; Cudek, Paweł

2014-01-01

That amino acid properties are responsible for the way protein molecules evolve is natural and is also reasonably well supported both by the structure of the genetic code and, to a large extent, by the experimental measures of the amino acid similarity. Nevertheless, there remains a significant gap between observed similarity matrices and their reconstructions from amino acid properties. Therefore, we introduce a simple theoretical model of amino acid similarity matrices, which allows splitting the matrix into two parts – one that depends only on mutabilities of amino acids and another that depends on pairwise similarities between them. Then the new synthetic amino acid properties are derived from the pairwise similarities and used to reconstruct similarity matrices covering a wide range of information entropies. Our model allows us to explain up to 94% of the variability in the BLOSUM family of the amino acids similarity matrices in terms of amino acid properties. The new properties derived from amino acid similarity matrices correlate highly with properties known to be important for molecular evolution such as hydrophobicity, size, shape and charge of amino acids. This result closes the gap in our understanding of the influence of amino acids on evolution at the molecular level. The methods were applied to the single family of similarity matrices used often in general sequence homology searches, but it is general and can be used also for more specific matrices. The new synthetic properties can be used in analyzes of protein sequences in various biological applications. PMID:24967708

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

A Cross-Language Study of Acoustic Predictors of Speech Intelligibility in Individuals With Parkinson's Disease

PubMed Central

Choi, Yaelin

2017-01-01

Purpose The present study aimed to compare acoustic models of speech intelligibility in individuals with the same disease (Parkinson's disease [PD]) and presumably similar underlying neuropathologies but with different native languages (American English [AE] and Korean). Method A total of 48 speakers from the 4 speaker groups (AE speakers with PD, Korean speakers with PD, healthy English speakers, and healthy Korean speakers) were asked to read a paragraph in their native languages. Four acoustic variables were analyzed: acoustic vowel space, voice onset time contrast scores, normalized pairwise variability index, and articulation rate. Speech intelligibility scores were obtained from scaled estimates of sentences extracted from the paragraph. Results The findings indicated that the multiple regression models of speech intelligibility were different in Korean and AE, even with the same set of predictor variables and with speakers matched on speech intelligibility across languages. Analysis of the descriptive data for the acoustic variables showed the expected compression of the vowel space in speakers with PD in both languages, lower normalized pairwise variability index scores in Korean compared with AE, and no differences within or across language in articulation rate. Conclusions The results indicate that the basis of an intelligibility deficit in dysarthria is likely to depend on the native language of the speaker and listener. Additional research is required to explore other potential predictor variables, as well as additional language comparisons to pursue cross-linguistic considerations in classification and diagnosis of dysarthria types. PMID:28821018

Prioritizing tiger conservation through landscape genetics and habitat linkages.

PubMed

Yumnam, Bibek; Jhala, Yadvendradev V; Qureshi, Qamar; Maldonado, Jesus E; Gopal, Rajesh; Saini, Swati; Srinivas, Y; Fleischer, Robert C

2014-01-01

Even with global support for tiger (Panthera tigris) conservation their survival is threatened by poaching, habitat loss and isolation. Currently about 3,000 wild tigers persist in small fragmented populations within seven percent of their historic range. Identifying and securing habitat linkages that connect source populations for maintaining landscape-level gene flow is an important long-term conservation strategy for endangered carnivores. However, habitat corridors that link regional tiger populations are often lost to development projects due to lack of objective evidence on their importance. Here, we use individual based genetic analysis in combination with landscape permeability models to identify and prioritize movement corridors across seven tiger populations within the Central Indian Landscape. By using a panel of 11 microsatellites we identified 169 individual tigers from 587 scat and 17 tissue samples. We detected four genetic clusters within Central India with limited gene flow among three of them. Bayesian and likelihood analyses identified 17 tigers as having recent immigrant ancestry. Spatially explicit tiger occupancy obtained from extensive landscape-scale surveys across 76,913 km(2) of forest habitat was found to be only 21,290 km(2). After accounting for detection bias, the covariates that best explained tiger occupancy were large, remote, dense forest patches; large ungulate abundance, and low human footprint. We used tiger occupancy probability to parameterize habitat permeability for modeling habitat linkages using least-cost and circuit theory pathway analyses. Pairwise genetic differences (FST) between populations were better explained by modeled linkage costs (r>0.5, p<0.05) compared to Euclidean distances, which was in consonance with observed habitat fragmentation. The results of our study highlight that many corridors may still be functional as there is evidence of contemporary migration. Conservation efforts should provide legal status to corridors, use smart green infrastructure to mitigate development impacts, and restore habitats where connectivity has been lost.

Contextual Interactions in Grating Plaid Configurations Are Explained by Natural Image Statistics and Neural Modeling

PubMed Central

Ernst, Udo A.; Schiffer, Alina; Persike, Malte; Meinhardt, Günter

2016-01-01

Processing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in early visual areas may form the early substrate of these local feature bindings. To investigate local interaction structures in visual cortex, we combined psychophysical experiments with computational modeling and natural scene analysis. We first measured contrast thresholds for 2 × 2 grating patch arrangements (plaids), which differed in spatial frequency composition (low, high, or mixed), number of grating patch co-alignments (0, 1, or 2), and inter-patch distances (1° and 2° of visual angle). Contrast thresholds for the different configurations were compared to the prediction of probability summation (PS) among detector families tuned to the four retinal positions. For 1° distance the thresholds for all configurations were larger than predicted by PS, indicating inhibitory interactions. For 2° distance, thresholds were significantly lower compared to PS when the plaids were homogeneous in spatial frequency and orientation, but not when spatial frequencies were mixed or there was at least one misalignment. Next, we constructed a neural population model with horizontal laminar structure, which reproduced the detection thresholds after adaptation of connection weights. Consistent with prior work, contextual interactions were medium-range inhibition and long-range, orientation-specific excitation. However, inclusion of orientation-specific, inhibitory interactions between populations with different spatial frequency preferences were crucial for explaining detection thresholds. Finally, for all plaid configurations we computed their likelihood of occurrence in natural images. The likelihoods turned out to be inversely related to the detection thresholds obtained at larger inter-patch distances. However, likelihoods were almost independent of inter-patch distance, implying that natural image statistics could not explain the crowding-like results at short distances. This failure of natural image statistics to resolve the patch distance modulation of plaid visibility remains a challenge to the approach. PMID:27757076

Prioritizing Tiger Conservation through Landscape Genetics and Habitat Linkages

PubMed Central

Yumnam, Bibek; Jhala, Yadvendradev V.; Qureshi, Qamar; Maldonado, Jesus E.; Gopal, Rajesh; Saini, Swati; Srinivas, Y.; Fleischer, Robert C.

2014-01-01

Even with global support for tiger (Panthera tigris) conservation their survival is threatened by poaching, habitat loss and isolation. Currently about 3,000 wild tigers persist in small fragmented populations within seven percent of their historic range. Identifying and securing habitat linkages that connect source populations for maintaining landscape-level gene flow is an important long-term conservation strategy for endangered carnivores. However, habitat corridors that link regional tiger populations are often lost to development projects due to lack of objective evidence on their importance. Here, we use individual based genetic analysis in combination with landscape permeability models to identify and prioritize movement corridors across seven tiger populations within the Central Indian Landscape. By using a panel of 11 microsatellites we identified 169 individual tigers from 587 scat and 17 tissue samples. We detected four genetic clusters within Central India with limited gene flow among three of them. Bayesian and likelihood analyses identified 17 tigers as having recent immigrant ancestry. Spatially explicit tiger occupancy obtained from extensive landscape-scale surveys across 76,913 km2 of forest habitat was found to be only 21,290 km2. After accounting for detection bias, the covariates that best explained tiger occupancy were large, remote, dense forest patches; large ungulate abundance, and low human footprint. We used tiger occupancy probability to parameterize habitat permeability for modeling habitat linkages using least-cost and circuit theory pathway analyses. Pairwise genetic differences (F ST) between populations were better explained by modeled linkage costs (r>0.5, p<0.05) compared to Euclidean distances, which was in consonance with observed habitat fragmentation. The results of our study highlight that many corridors may still be functional as there is evidence of contemporary migration. Conservation efforts should provide legal status to corridors, use smart green infrastructure to mitigate development impacts, and restore habitats where connectivity has been lost. PMID:25393234

Adaptation in Coding by Large Populations of Neurons in the Retina

NASA Astrophysics Data System (ADS)

Ioffe, Mark L.

A comprehensive theory of neural computation requires an understanding of the statistical properties of the neural population code. The focus of this work is the experimental study and theoretical analysis of the statistical properties of neural activity in the tiger salamander retina. This is an accessible yet complex system, for which we control the visual input and record from a substantial portion--greater than a half--of the ganglion cell population generating the spiking output. Our experiments probe adaptation of the retina to visual statistics: a central feature of sensory systems which have to adjust their limited dynamic range to a far larger space of possible inputs. In Chapter 1 we place our work in context with a brief overview of the relevant background. In Chapter 2 we describe the experimental methodology of recording from 100+ ganglion cells in the tiger salamander retina. In Chapter 3 we first present the measurements of adaptation of individual cells to changes in stimulation statistics and then investigate whether pairwise correlations in fluctuations of ganglion cell activity change across different stimulation conditions. We then transition to a study of the population-level probability distribution of the retinal response captured with maximum-entropy models. Convergence of the model inference is presented in Chapter 4. In Chapter 5 we first test the empirical presence of a phase transition in such models fitting the retinal response to different experimental conditions, and then proceed to develop other characterizations which are sensitive to complexity in the interaction matrix. This includes an analysis of the dynamics of sampling at finite temperature, which demonstrates a range of subtle attractor-like properties in the energy landscape. These are largely conserved when ambient illumination is varied 1000-fold, a result not necessarily apparent from the measured low-order statistics of the distribution. Our results form a consistent picture which is discussed at the end of Chapter 5. We conclude with a few future directions related to this thesis.

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.

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.

Bayesics

NASA Astrophysics Data System (ADS)

Skilling, John

2005-11-01

This tutorial gives a basic overview of Bayesian methodology, from its axiomatic foundation through the conventional development of data analysis and model selection to its rôle in quantum mechanics, and ending with some comments on inference in general human affairs. The central theme is that probability calculus is the unique language within which we can develop models of our surroundings that have predictive capability. These models are patterns of belief; there is no need to claim external reality. 1. Logic and probability 2. Probability and inference 3. Probability and model selection 4. Prior probabilities 5. Probability and frequency 6. Probability and quantum mechanics 7. Probability and fundamentalism 8. Probability and deception 9. Prediction and truth

Gender differences in the effects of childhood adversity on alcohol, drug, and polysubstance-related disorders.

PubMed

Evans, Elizabeth A; Grella, Christine E; Upchurch, Dawn M

2017-07-01

To examine gender differences in the associations between childhood adversity and different types of substance use disorders and whether gender moderates these relationships. We analyzed data from 19,209 women and 13,898 men as provided by Wave 2 (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) to examine whether gender moderates the associations between childhood adversity and DSM-IV defined lifetime occurrence of alcohol, drug, and polysubstance-related disorders. We used multinomial logistic regression, weighted to be representative of the US adult civilian, noninstitutionalized population, and we calculated predicted probabilities by gender, controlling for covariates. To test which specific moderation contrasts were statistically significant, we conducted pair-wise comparisons corrected for multiple comparisons using Bonferroni's method. For each type of substance use disorder, risk was increased by more exposure to childhood adversity, and women had a lower risk than men. However, moderation effects revealed that with more experiences of childhood adversity, the gender gap in predicted probability for a disorder narrowed in relation to alcohol, it converged in relation to drugs such that risk among women surpassed that among men, and it widened in relation to polysubstances. Knowledge regarding substance-specific gender differences associated with childhood adversity exposure can inform evidence-based treatments. It may also be useful for shaping other types of gender-sensitive public health initiatives to ameliorate or prevent different types of substance use disorders.

Large- and small-scale constraints on power spectra in Omega = 1 universes

NASA Technical Reports Server (NTRS)

Gelb, James M.; Gradwohl, Ben-Ami; Frieman, Joshua A.

1993-01-01

The CDM model of structure formation, normalized on large scales, leads to excessive pairwise velocity dispersions on small scales. In an attempt to circumvent this problem, we study three scenarios (all with Omega = 1) with more large-scale and less small-scale power than the standard CDM model: (1) cold dark matter with significantly reduced small-scale power (inspired by models with an admixture of cold and hot dark matter); (2) cold dark matter with a non-scale-invariant power spectrum; and (3) cold dark matter with coupling of dark matter to a long-range vector field. When normalized to COBE on large scales, such models do lead to reduced velocities on small scales and they produce fewer halos compared with CDM. However, models with sufficiently low small-scale velocities apparently fail to produce an adequate number of halos.

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.

Acoustic classification of zooplankton

NASA Astrophysics Data System (ADS)

Martin Traykovski, Linda V.

1998-11-01

Work on the forward problem in zooplankton bioacoustics has resulted in the identification of three categories of acoustic scatterers: elastic-shelled (e.g. pteropods), fluid-like (e.g. euphausiids), and gas-bearing (e.g. siphonophores). The relationship between backscattered energy and animal biomass has been shown to vary by a factor of ~19,000 across these categories, so that to make accurate estimates of zooplankton biomass from acoustic backscatter measurements of the ocean, the acoustic characteristics of the species of interest must be well-understood. This thesis describes the development of both feature based and model based classification techniques to invert broadband acoustic echoes from individual zooplankton for scatterer type, as well as for particular parameters such as animal orientation. The feature based Empirical Orthogonal Function Classifier (EOFC) discriminates scatterer types by identifying characteristic modes of variability in the echo spectra, exploiting only the inherent characteristic structure of the acoustic signatures. The model based Model Parameterisation Classifier (MPC) classifies based on correlation of observed echo spectra with simplified parameterisations of theoretical scattering models for the three classes. The Covariance Mean Variance Classifiers (CMVC) are a set of advanced model based techniques which exploit the full complexity of the theoretical models by searching the entire physical model parameter space without employing simplifying parameterisations. Three different CMVC algorithms were developed: the Integrated Score Classifier (ISC), the Pairwise Score Classifier (PSC) and the Bayesian Probability Classifier (BPC); these classifiers assign observations to a class based on similarities in covariance, mean, and variance, while accounting for model ambiguity and validity. These feature based and model based inversion techniques were successfully applied to several thousand echoes acquired from broadband (~350 kHz-750 kHz) insonifications of live zooplankton collected on Georges Bank and the Gulf of Maine to determine scatterer class. CMVC techniques were also applied to echoes from fluid-like zooplankton (Antarctic krill) to invert for angle of orientation using generic and animal-specific theoretical and empirical models. Application of these inversion techniques in situ will allow correct apportionment of backscattered energy to animal biomass, significantly improving estimates of zooplankton biomass based on acoustic surveys. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

Effects of Brief Psychoeducational Program on Stigma in Malaysian Pre-clinical Medical Students: A Randomized Controlled Trial.

PubMed

Fernandez, Aaron; Tan, Kit-Aun; Knaak, Stephanie; Chew, Boon How; Ghazali, Sazlina Shariff

2016-12-01

If presented with serious mental illness (SMI), individuals' low help-seeking behaviors and poor adherence to treatment are associated with negative stereotypes and attitudes of healthcare providers. In this study, we examined the effects of a brief psychoeducational program on reducing stigma in pre-clinical medical students. One hundred and two pre-clinical medical students (20-23 years old) were randomly assigned to face-to-face contact + educational lecture (n = 51) condition or video-based contact + educational lecture (n = 51) condition. Measures of pre-clinical medical students' mental illness-related stigma using the Opening Minds Stigma Scale for Health Care Providers (OMS-HC) were administered at pre-, post-treatment, and 1-month follow-up. A 2 (condition: face-to-face contact + educational lecture, video-based contact + educational lecture) by 3 (time: pre-treatment, post-treatment, and 1-month follow-up) mixed model MANOVA was conducted on the Attitudes, Disclosure and Help-Seeking, and Social Distance OMS-HC subscales. Participants' scores on all subscales changed significantly across time, regardless of conditions. To determine how participants' scores changed significantly over time on each subscale, Bonferroni follow-up comparisons were performed to access pairwise differences for the main effect of time. Specifically, pairwise comparisons produced a significant reduction in Social Distance subscale between pre-treatment and post-treatment and between pre-treatment and 1-month follow-up, and a significant increase between post-treatment and 1-month follow-up, regardless of conditions. With respect to the Attitudes and Disclosure and Help-Seeking subscales, pairwise comparisons produced a significant reduction in scores between pre-treatment and post-treatment and a significant increase between post-treatment and 1-month follow-up. Our findings provide additional evidence that educational lecture on mental illness, coupled with either face-to-face contact or video-based contact, is predictive of positive outcomes in anti-stigma programs targeting future healthcare providers.

Protein side chain conformation predictions with an MMGBSA energy function.

PubMed

Gaillard, Thomas; Panel, Nicolas; Simonson, Thomas

2016-06-01

The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an "MMGBSA" energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803-819. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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

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

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

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 for modeling of free surface flow 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 rough surfaces in a shape of a sinusoidal functionmore » and made of rectangular bars placed on top of a flat surface. 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. Next, 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 classical lotus effect. We demonstrate that linear scaling relationships between Bond and capillary number for droplet flow on flat surfaces also hold for flow on rough surfaces.« less

Pairwise mixture model for unmixing partial volume effect in multi-voxel MR spectroscopy of brain tumour patients

NASA Astrophysics Data System (ADS)

Olliverre, Nathan; Asad, Muhammad; Yang, Guang; Howe, Franklyn; Slabaugh, Gregory

2017-03-01

Multi-Voxel Magnetic Resonance Spectroscopy (MV-MRS) provides an important and insightful technique for the examination of the chemical composition of brain tissue, making it an attractive medical imaging modality for the examination of brain tumours. MRS, however, is affected by the issue of the Partial Volume Effect (PVE), where the signals of multiple tissue types can be found within a single voxel and provides an obstacle to the interpretation of the data. The PVE results from the low resolution achieved in MV-MRS images relating to the signal to noise ratio (SNR). To counteract PVE, this paper proposes a novel Pairwise Mixture Model (PMM), that extends a recently reported Signal Mixture Model (SMM) for representing the MV-MRS signal as normal, low or high grade tissue types. Inspired by Conditional Random Field (CRF) and its continuous variant the PMM incorporates the surrounding voxel neighbourhood into an optimisation problem, the solution of which provides an estimation to a set of coefficients. The values of the estimated coefficients represents the amount of each tissue type (normal, low or high) found within a voxel. These coefficients can then be visualised as a nosological rendering using a coloured grid representing the MV-MRS image overlaid on top of a structural image, such as a Magnetic Resonance Image (MRI). Experimental results show an accuracy of 92.69% in classifying patient tumours as either low or high grade compared against the histopathology for each patient. Compared to 91.96% achieved by the SMM, the proposed PMM method demonstrates the importance of incorporating spatial coherence into the estimation as well as its potential clinical usage.

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

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.

Probability based models for estimation of wildfire risk

Treesearch

Haiganoush Preisler; D. R. Brillinger; R. E. Burgan; John Benoit

2004-01-01

We present a probability-based model for estimating fire risk. Risk is defined using three probabilities: the probability of fire occurrence; the conditional probability of a large fire given ignition; and the unconditional probability of a large fire. The model is based on grouped data at the 1 km²-day cell level. We fit a spatially and temporally explicit non-...

Generalized Born Models of Macromolecular Solvation Effects

NASA Astrophysics Data System (ADS)

Bashford, Donald; Case, David A.

2000-10-01

It would often be useful in computer simulations to use a simple description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation, and approximations to such models that avoid the need to solve the Poisson equation are attractive because of their computational efficiency. Here we give an overview of one such approximation, the generalized Born model, which is simple and fast enough to be used for molecular dynamics simulations of proteins and nucleic acids. We discuss its strengths and weaknesses, both for its fidelity to the underlying continuum model and for its ability to replace explicit consideration of solvent molecules in macromolecular simulations. We focus particularly on versions of the generalized Born model that have a pair-wise analytical form, and therefore fit most naturally into conventional molecular mechanics calculations.

Dynamic Infinite Mixed-Membership Stochastic Blockmodel.

PubMed

Fan, Xuhui; Cao, Longbing; Xu, Richard Yi Da

2015-09-01

Directional and pairwise measurements are often used to model interactions in a social network setting. The mixed-membership stochastic blockmodel (MMSB) was a seminal work in this area, and its ability has been extended. However, models such as MMSB face particular challenges in modeling dynamic networks, for example, with the unknown number of communities. Accordingly, this paper proposes a dynamic infinite mixed-membership stochastic blockmodel, a generalized framework that extends the existing work to potentially infinite communities inside a network in dynamic settings (i.e., networks are observed over time). Additional model parameters are introduced to reflect the degree of persistence among one's memberships at consecutive time stamps. Under this framework, two specific models, namely mixture time variant and mixture time invariant models, are proposed to depict two different time correlation structures. Two effective posterior sampling strategies and their results are presented, respectively, using synthetic and real-world data.

Structure of colloidosomes with tunable particle density: Simulation versus experiment

NASA Astrophysics Data System (ADS)

Fantoni, Riccardo; Salari, Johannes W. O.; Klumperman, Bert

2012-06-01

Colloidosomes are created in the laboratory from a Pickering emulsion of water droplets in oil. The colloidosomes have approximately the same diameter and by choosing (hairy) particles of different diameters it is possible to control the particle density on the droplets. The experiment is performed at room temperature. The radial distribution function of the assembly of (primary) particles on the water droplet is measured in the laboratory and in a computer experiment of a fluid model of particles with pairwise interactions on the surface of a sphere.

PLANETESIMAL FORMATION BY GRAVITATIONAL INSTABILITY OF A POROUS DUST DISK

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

Michikoshi, Shugo; Kokubo, Eiichiro, E-mail: michikos@ccs.tsukuba.ac.jp, E-mail: kokubo@th.nao.ac.jp

2016-07-10

It has recently been proposed that porous icy dust aggregates are formed by the pairwise accretion of dust aggregates beyond the snowline. We calculate the equilibrium random velocity of porous dust aggregates, taking into account mutual gravitational scattering, collisions, gas drag, and turbulent stirring and scattering. We find that the disk of porous dust aggregates becomes gravitationally unstable as the aggregates evolve through gravitational compression in the minimum-mass solar nebula model for a reasonable range of turbulence strength, which leads to rapid formation of planetesimals.

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.

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.

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.

Population and forensic data for three sets of forensic genetic markers in four ethnic groups from Iran: Persians, Lurs, Kurds and Azeris.

PubMed

Poulsen, L; Farzad, M Sharafi; Børsting, C; Tomas, C; Pereira, V; Morling, N

2015-07-01

A total of 255 individuals (Persians, Lurs, Kurds and Azeris) from Iran were typed for three sets of forensic genetic markers with the NGM SElect™, DIPplex(®) and Argus X-12 kits. Statistically significant deviations (P≤0.002) from Hardy-Weinberg expectations were observed for the insertion-deletion markers HLD97 and HLD93 after Holm-Šidák correction. Statistically significant (P<0.05) levels of linkage disequilibrium were observed between markers within two of the four studied X-chromosomal linkage groups. AMOVA analyses of the three sets of markers did not show population structure when the individuals were grouped according to their ethnic group. The Iranian population grouped closely to populations living geographically near to Iran based on pairwise FST distances. The matching probabilities ranged from 1 in 3.2×10(7) males by using haplotype frequencies of four X-chromosomal haplogroups to 1 in 3.4×10(21) individuals for the 16 autosomal STRs. Copyright © 2015. Published by Elsevier Ireland Ltd.

Estimating the degree of identity by descent in consanguineous couples.

PubMed

Carr, Ian M; Markham, Sir Alexander F; Pena, Sérgio D J

2011-12-01

In some clinical and research settings, it is often necessary to identify the true level of "identity by descent" (IBD) between two individuals. However, as the individuals become more distantly related, it is increasingly difficult to accurately calculate this value. Consequently, we have developed a computer program that uses genome-wide SNP genotype data from related individuals to estimate the size and extent of IBD in their genomes. In addition, the software can compare a couple's IBD regions with either the autozygous regions of a relative affected by an autosomal recessive disease of unknown cause, or the IBD regions in the parents of the affected relative. It is then possible to calculate the probability of one of the couple's children suffering from the same disease. The software works by finding SNPs that exclude any possible IBD and then identifies regions that lack these SNPs, while exceeding a minimum size and number of SNPs. The accuracy of the algorithm was established by estimating the pairwise IBD between different members of a large pedigree with varying known coefficients of genetic relationship (CGR). © 2011 Wiley Periodicals, Inc.

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.

Evaluation of lattice sums by the Poisson sum formula

NASA Technical Reports Server (NTRS)

Ray, R. D.

1975-01-01

The Poisson sum formula was applied to the problem of summing pairwise interactions between an observer molecule and a semi-infinite regular array of solid state molecules. The transformed sum is often much more rapidly convergent than the original sum, and forms a Fourier series in the solid surface coordinates. The method is applicable to a variety of solid state structures and functional forms of the pairwise potential. As an illustration of the method, the electric field above the (100) face of the CsCl structure is calculated and compared to earlier results obtained by direct summation.

Evaluation of a proposed method for representing drug terminology.

PubMed Central

Cimino, J. J.; McNamara, T. J.; Meredith, T.; Broverman, C. A.; Eckert, K. C.; Moore, M.; Tyree, D. J.

1999-01-01

In the absence of a single, standard, multipurpose terminology for representing medications, the HL7 Vocabulary Technical Committee has sought to develop a model for such terms in a way that will provide a unified method for representing them and supporting interoperability among various terminology systems. We evaluated the preliminary model by obtaining terms, represented in our model, from three leading vendors of pharmacy system knowledge bases. A total of 2303 terms were obtained, and 3982 pair-wise comparisons were possible. We found that the components of the term descriptions matched 68-87% of the time and that the overall descriptions matched 53% of the time. The evaluation has identified a number of areas in the model where more rigorous definitions will be needed in order to improve the matching rate. This paper discusses the implications of these results. PMID:10566318

Control surface in aerial triangulation

NASA Astrophysics Data System (ADS)

Jaw, Jen-Jer

With the increased availability of surface-related sensors, the collection of surface information becomes easier and more straightforward than ever before. In this study, the author proposes a model in which the surface information is integrated into the aerial triangulation workflow by hypothesizing plane observations in the object space, the estimated object points via photo measurements (or matching) together with the adjusted surface points would provide a better point group describing the surface. The algorithms require no special structure of surface points and involve no interpolation process. The suggested measuring strategy (pairwise measurements) results in a quite fluent and favorable working environment when taking measurements. Furthermore, the extension of the model employing the the surface plane finds itself useful in tying photo models. The proposed model has been proven working by the simulation and carried out in the photogrammetric laboratory.

Development of a Multimetric Indicator of Pelagic Zooplankton ...

EPA Pesticide Factsheets

We used zooplankton data collected for the 2012 National Lakes Assessment (NLA) to develop multimetric indices (MMIs) for five aggregated ecoregions of the conterminous USA (Coastal Plains, Eastern Highlands, Plains, Upper Midwest, and Western Mountains and Xeric [“West’]). We classified candidate metrics into six categories: We evaluated the performance of candidate metrics, and used metrics that had passed these screens to calculate all possible candidate MMIs that included at least one metric from each category. We selected the candidate MMI that had high responsiveness, a reasonable value for repeatability, low mean pairwise correlation among component metrics, and, when possible, a maximum pairwise correlation among component metrics that was <0.7. We were able to develop MMIs that were sufficiently responsive and repeatable to assess ecological condition for the NLA without the need to reduce the effects of natural variation using models. We did not observe effects of either lake size, lake origin, or site depth on the MMIs. The MMIs appear to respond more strongly to increased nutrient concentrations than to shoreline habitat conditions. Improving our understanding of how zooplankton assemblages respond to increased human disturbance, and obtaining more complete autecological information for zooplankton taxa would likely improve MMIs developed for future assessments. Using zooplankton assemblage data from the 2012 National Lakes Assessment (NLA),

Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region

USGS Publications Warehouse

Zischke, Mitchell T.; Bunnell, David B.; Troy, Cary D.; Berglund, Eric K.; Caroffino, David C.; Ebener, Mark P.; He, Ji X.; Sitar, Shawn P.; Hook, Tomas O.

2017-01-01

Spatially separated fish populations may display synchrony in annual recruitment if the factors that drive recruitment success, particularly abiotic factors such as temperature, are synchronised across broad spatial scales. We examined inter-annual variation in recruitment among lake whitefish (Coregonus clupeaformis) populations in lakes Huron, Michigan and Superior using fishery-dependent and -independent data from 1971 to 2014. Relative year-class strength (RYCS) was calculated from catch-curve residuals for each year class across multiple sampling years. Pairwise comparison of RYCS among datasets revealed no significant associations either within or between lakes, suggesting that recruitment of lake whitefish is spatially asynchronous. There was no consistent correlation between pairwise agreement and the distance between datasets, and models to estimate the spatial scale of recruitment synchrony did not fit well to these data. This suggests that inter-annual recruitment variation of lake whitefish is asynchronous across broad spatial scales in the Great Lakes. While our method primarily evaluated year-to-year recruitment variation, it is plausible that recruitment of lake whitefish varies at coarser temporal scales (e.g. decadal). Nonetheless, our findings differ from research on some other Coregonus species and suggest that local biotic or density-dependent factors may contribute strongly to lake whitefish recruitment rather than inter-annual variability in broad-scale abiotic factors.

Kernel Machine SNP-set Testing under Multiple Candidate Kernels

PubMed Central

Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

2013-01-01

Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

The prophylactic effect of Viscum album in streptozotocin-induced diabetic rats

PubMed Central

Turkkan, Asuman; Savas, Hasan Basri; Yavuz, Berire; Yigit, Ayse; Uz, Efkan; Bayram, Nezire Asli; Kale, Banu

2016-01-01

OBJECTIVE: Viscum album (VA) is a species of mistletoe in the family Santalaceae that is thought to have therapeutic properties for several diseases, including diabetes. In the present study, conventional experimental rat model was used with diabetes induced with streptozotocin (STZ) to evaluate effect of VA on lipid peroxidation and antioxidant system. METHODS: Total of 32 adult, male Sprague-Dawley rats were divided into 4 groups of 8 rats: Control group, STZ group, VA group, and group administered VA+STZ. VA extract was 100 mg/kg preparation delivered once a day by oral gavage for 10 days. Single dose of 55 mg/kg STZ citrate buffer (0.1 M, pH 4.5) was administered intraperitoneally to induce diabetes. Fasting blood glucose level was measured and recorded. Animals were sacrificed, and catalase (CAT), malondialdehyde (MDA), and protein present in liver and kidney tissue samples were measured. Activity of CAT, an antioxidant enzyme, was studied according to the Aebi method. MDA, a product of lipid peroxidation, was analyzed using Draper and Hadley spectrophotometric procedure. Protein level was determined using supernatant and extract of tissue homogenates according to Lowry method. Data were assessed using one-way analysis of variance and pairwise comparisons between groups. Post-hoc analysis included Dunnet test, Duncan test, and least significant difference test. P<0.05 was considered significant probability value. RESULTS: Oxidative stress is associated with diabetic complications. VA administered to diabetic rats reduced oxidative stress and improved their general condition. CONCLUSION: Further studies are needed to enhance understanding of potential antidiabetic and antioxidant effects of VA. PMID:28058393

Comparative efficacy and acceptability of pharmacological treatments for post-traumatic stress disorder in adults: a network meta-analysis.

PubMed

Cipriani, Andrea; Williams, Taryn; Nikolakopoulou, Adriani; Salanti, Georgia; Chaimani, Anna; Ipser, Jonathan; Cowen, Phil J; Geddes, John R; Stein, Dan J

2017-12-19

Guidelines about post-traumatic stress disorder (PTSD) recommend broad categories of drugs, but uncertainty remains about what pharmacological treatment to select among all available compounds. Cochrane Central Register of Controlled Trials register, MEDLINE, PsycINFO, National PTSD Center Pilots database, PubMed, trial registries, and databases of pharmaceutical companies were searched until February 2016 for double-blind randomised trials comparing any pharmacological intervention or placebo as oral therapy in adults with PTSD. Initially, we performed standard pairwise meta-analyses using a random effects model. We then carried out a network meta-analysis. The main outcome measures were mean change on a standardised scale and all-cause dropout rate. Acute treatment was defined as 8-week follow up. Desipramine, fluoxetine, paroxetine, phenelzine, risperidone, sertraline, and venlafaxine were more effective than placebo; phenelzine was better than many other active treatments and was the only drug, which was significantly better than placebo in terms of dropouts (odds ratio 7.50, 95% CI 1.72-32.80). Mirtazapine yielded a relatively high rank for efficacy, but the respective value for acceptability was not among the best treatments. Divalproex had overall the worst ranking. The efficacy and acceptability hierarchies generated by our study were robust against many sources of bias. The differences between drugs and placebo were small, with the only exception of phenelzine. Considering the small amount of available data, these results are probably not robust enough to suggest phenelzine as a drug of choice. However, findings from this review reinforce the idea that phenelzine should be prioritised in future trials in PTSD.

Heat transport in Rayleigh-Bénard convection and angular momentum transport in Taylor-Couette flow: a comparative study.

PubMed

Brauckmann, Hannes J; Eckhardt, Bruno; Schumacher, Jörg

2017-03-13

Rayleigh-Bénard convection and Taylor-Couette flow are two canonical flows that have many properties in common. We here compare the two flows in detail for parameter values where the Nusselt numbers, i.e. the thermal transport and the angular momentum transport normalized by the corresponding laminar values, coincide. We study turbulent Rayleigh-Bénard convection in air at Rayleigh number Ra=10 7 and Taylor-Couette flow at shear Reynolds number Re S =2×10 4 for two different mean rotation rates but the same Nusselt numbers. For individual pairwise related fields and convective currents, we compare the probability density functions normalized by the corresponding root mean square values and taken at different distances from the wall. We find one rotation number for which there is very good agreement between the mean profiles of the two corresponding quantities temperature and angular momentum. Similarly, there is good agreement between the fluctuations in temperature and velocity components. For the heat and angular momentum currents, there are differences in the fluctuations outside the boundary layers that increase with overall rotation and can be related to differences in the flow structures in the boundary layer and in the bulk. The study extends the similarities between the two flows from global quantities to local quantities and reveals the effects of rotation on the transport.This article is part of the themed issue 'Toward the development of high-fidelity models of wall turbulence at large Reynolds number'. © 2017 The Author(s).

Generating log-normal mock catalog of galaxies in redshift space

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

Agrawal, Aniket; Makiya, Ryu; Saito, Shun

We present a public code to generate a mock galaxy catalog in redshift space assuming a log-normal probability density function (PDF) of galaxy and matter density fields. We draw galaxies by Poisson-sampling the log-normal field, and calculate the velocity field from the linearised continuity equation of matter fields, assuming zero vorticity. This procedure yields a PDF of the pairwise velocity fields that is qualitatively similar to that of N-body simulations. We check fidelity of the catalog, showing that the measured two-point correlation function and power spectrum in real space agree with the input precisely. We find that a linear biasmore » relation in the power spectrum does not guarantee a linear bias relation in the density contrasts, leading to a cross-correlation coefficient of matter and galaxies deviating from unity on small scales. We also find that linearising the Jacobian of the real-to-redshift space mapping provides a poor model for the two-point statistics in redshift space. That is, non-linear redshift-space distortion is dominated by non-linearity in the Jacobian. The power spectrum in redshift space shows a damping on small scales that is qualitatively similar to that of the well-known Fingers-of-God (FoG) effect due to random velocities, except that the log-normal mock does not include random velocities. This damping is a consequence of non-linearity in the Jacobian, and thus attributing the damping of the power spectrum solely to FoG, as commonly done in the literature, is misleading.« less

Multisite Interactions in Lattice-Gas Models

NASA Astrophysics Data System (ADS)

Einstein, T. L.; Sathiyanarayanan, R.

For detailed applications of lattice-gas models to surface systems, multisite interactions often play at least as significant a role as interactions between pairs of adatoms that are separated by a few lattice spacings. We recall that trio (3-adatom, non-pairwise) interactions do not inevitably create phase boundary asymmetries about half coverage. We discuss a sophisticated application to an experimental system and describe refinements in extracting lattice-gas energies from calculations of total energies of several different ordered overlayers. We describe how lateral relaxations complicate matters when there is direct interaction between the adatoms, an issue that is important when examining the angular dependence of step line tensions. We discuss the connector model as an alternative viewpoint and close with a brief account of recent work on organic molecule overlayers.

Probability Theory Plus Noise: Descriptive Estimation and Inferential Judgment.

PubMed

Costello, Fintan; Watts, Paul

2018-01-01

We describe a computational model of two central aspects of people's probabilistic reasoning: descriptive probability estimation and inferential probability judgment. This model assumes that people's reasoning follows standard frequentist probability theory, but it is subject to random noise. This random noise has a regressive effect in descriptive probability estimation, moving probability estimates away from normative probabilities and toward the center of the probability scale. This random noise has an anti-regressive effect in inferential judgement, however. These regressive and anti-regressive effects explain various reliable and systematic biases seen in people's descriptive probability estimation and inferential probability judgment. This model predicts that these contrary effects will tend to cancel out in tasks that involve both descriptive estimation and inferential judgement, leading to unbiased responses in those tasks. We test this model by applying it to one such task, described by Gallistel et al. ). Participants' median responses in this task were unbiased, agreeing with normative probability theory over the full range of responses. Our model captures the pattern of unbiased responses in this task, while simultaneously explaining systematic biases away from normatively correct probabilities seen in other tasks. Copyright © 2018 Cognitive Science Society, Inc.

NoFold: RNA structure clustering without folding or alignment.

PubMed

Middleton, Sarah A; Kim, Junhyong

2014-11-01

Structures that recur across multiple different transcripts, called structure motifs, often perform a similar function-for example, recruiting a specific RNA-binding protein that then regulates translation, splicing, or subcellular localization. Identifying common motifs between coregulated transcripts may therefore yield significant insight into their binding partners and mechanism of regulation. However, as most methods for clustering structures are based on folding individual sequences or doing many pairwise alignments, this results in a tradeoff between speed and accuracy that can be problematic for large-scale data sets. Here we describe a novel method for comparing and characterizing RNA secondary structures that does not require folding or pairwise alignment of the input sequences. Our method uses the idea of constructing a distance function between two objects by their respective distances to a collection of empirical examples or models, which in our case consists of 1973 Rfam family covariance models. Using this as a basis for measuring structural similarity, we developed a clustering pipeline called NoFold to automatically identify and annotate structure motifs within large sequence data sets. We demonstrate that NoFold can simultaneously identify multiple structure motifs with an average sensitivity of 0.80 and precision of 0.98 and generally exceeds the performance of existing methods. We also perform a cross-validation analysis of the entire set of Rfam families, achieving an average sensitivity of 0.57. We apply NoFold to identify motifs enriched in dendritically localized transcripts and report 213 enriched motifs, including both known and novel structures. © 2014 Middleton and Kim; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

iGLASS: An Improvement to the GLASS Method for Estimating Species Trees from Gene Trees

PubMed Central

Rosenberg, Noah A.

2012-01-01

Abstract Several methods have been designed to infer species trees from gene trees while taking into account gene tree/species tree discordance. Although some of these methods provide consistent species tree topology estimates under a standard model, most either do not estimate branch lengths or are computationally slow. An exception, the GLASS method of Mossel and Roch, is consistent for the species tree topology, estimates branch lengths, and is computationally fast. However, GLASS systematically overestimates divergence times, leading to biased estimates of species tree branch lengths. By assuming a multispecies coalescent model in which multiple lineages are sampled from each of two taxa at L independent loci, we derive the distribution of the waiting time until the first interspecific coalescence occurs between the two taxa, considering all loci and measuring from the divergence time. We then use the mean of this distribution to derive a correction to the GLASS estimator of pairwise divergence times. We show that our improved estimator, which we call iGLASS, consistently estimates the divergence time between a pair of taxa as the number of loci approaches infinity, and that it is an unbiased estimator of divergence times when one lineage is sampled per taxon. We also show that many commonly used clustering methods can be combined with the iGLASS estimator of pairwise divergence times to produce a consistent estimator of the species tree topology. Through simulations, we show that iGLASS can greatly reduce the bias and mean squared error in obtaining estimates of divergence times in a species tree. PMID:22216756

Smoothed dissipative particle dynamics model for mesoscopic multiphase flows in the presence of thermal fluctuations

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

Lei, Huan; Baker, Nathan A.; Wu, Lei

2016-08-05

Thermal fluctuations cause perturbations of fluid-fluid interfaces and highly nonlinear hydrodynamics in multiphase flows. In this work, we develop a novel multiphase smoothed dissipative particle dynamics model. This model accounts for both bulk hydrodynamics and interfacial fluctuations. Interfacial surface tension is modeled by imposing a pairwise force between SDPD particles. We show that the relationship between the model parameters and surface tension, previously derived under the assumption of zero thermal fluctuation, is accurate for fluid systems at low temperature but overestimates the surface tension for intermediate and large thermal fluctuations. To analyze the effect of thermal fluctuations on surface tension,more » we construct a coarse-grained Euler lattice model based on the mean field theory and derive a semi-analytical formula to directly relate the surface tension to model parameters for a wide range of temperatures and model resolutions. We demonstrate that the present method correctly models the dynamic processes, such as bubble coalescence and capillary spectra across the interface.« less

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.

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

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

UQ for Decision Making: How (at least five) Kinds of Probability Might Come Into Play

NASA Astrophysics Data System (ADS)

Smith, L. A.

2013-12-01

In 1959 IJ Good published the discussion "Kinds of Probability" in Science. Good identified (at least) five kinds. The need for (at least) a sixth kind of probability when quantifying uncertainty in the context of climate science is discussed. This discussion brings out the differences in weather-like forecasting tasks and climate-links tasks, with a focus on the effective use both of science and of modelling in support of decision making. Good also introduced the idea of a "Dynamic probability" a probability one expects to change without any additional empirical evidence; the probabilities assigned by a chess playing program when it is only half thorough its analysis being an example. This case is contrasted with the case of "Mature probabilities" where a forecast algorithm (or model) has converged on its asymptotic probabilities and the question hinges in whether or not those probabilities are expected to change significantly before the event in question occurs, even in the absence of new empirical evidence. If so, then how might one report and deploy such immature probabilities in scientific-support of decision-making rationally? Mature Probability is suggested as a useful sixth kind, although Good would doubtlessly argue that we can get by with just one, effective communication with decision makers may be enhanced by speaking as if the others existed. This again highlights the distinction between weather-like contexts and climate-like contexts. In the former context one has access to a relevant climatology (a relevant, arguably informative distribution prior to any model simulations), in the latter context that information is not available although one can fall back on the scientific basis upon which the model itself rests, and estimate the probability that the model output is in fact misinformative. This subjective "probability of a big surprise" is one way to communicate the probability of model-based information holding in practice, the probability that the information the model-based probability is conditioned on holds. It is argued that no model-based climate-like probability forecast is complete without a quantitative estimate of its own irrelevance, and that the clear identification of model-based probability forecasts as mature or immature, are critical elements for maintaining the credibility of science-based decision support, and can shape uncertainty quantification more widely.

Probability Weighting Functions Derived from Hyperbolic Time Discounting: Psychophysical Models and Their Individual Level Testing.

PubMed

Takemura, Kazuhisa; Murakami, Hajime

2016-01-01

A probability weighting function (w(p)) is considered to be a nonlinear function of probability (p) in behavioral decision theory. This study proposes a psychophysical model of probability weighting functions derived from a hyperbolic time discounting model and a geometric distribution. The aim of the study is to show probability weighting functions from the point of view of waiting time for a decision maker. Since the expected value of a geometrically distributed random variable X is 1/p, we formulized the probability weighting function of the expected value model for hyperbolic time discounting as w(p) = (1 - k log p)(-1). Moreover, the probability weighting function is derived from Loewenstein and Prelec's (1992) generalized hyperbolic time discounting model. The latter model is proved to be equivalent to the hyperbolic-logarithmic weighting function considered by Prelec (1998) and Luce (2001). In this study, we derive a model from the generalized hyperbolic time discounting model assuming Fechner's (1860) psychophysical law of time and a geometric distribution of trials. In addition, we develop median models of hyperbolic time discounting and generalized hyperbolic time discounting. To illustrate the fitness of each model, a psychological experiment was conducted to assess the probability weighting and value functions at the level of the individual participant. The participants were 50 university students. The results of individual analysis indicated that the expected value model of generalized hyperbolic discounting fitted better than previous probability weighting decision-making models. The theoretical implications of this finding are discussed.

Bivariate categorical data analysis using normal linear conditional multinomial probability model.

PubMed

Sun, Bingrui; Sutradhar, Brajendra

2015-02-10

Bivariate multinomial data such as the left and right eyes retinopathy status data are analyzed either by using a joint bivariate probability model or by exploiting certain odds ratio-based association models. However, the joint bivariate probability model yields marginal probabilities, which are complicated functions of marginal and association parameters for both variables, and the odds ratio-based association model treats the odds ratios involved in the joint probabilities as 'working' parameters, which are consequently estimated through certain arbitrary 'working' regression models. Also, this later odds ratio-based model does not provide any easy interpretations of the correlations between two categorical variables. On the basis of pre-specified marginal probabilities, in this paper, we develop a bivariate normal type linear conditional multinomial probability model to understand the correlations between two categorical variables. The parameters involved in the model are consistently estimated using the optimal likelihood and generalized quasi-likelihood approaches. The proposed model and the inferences are illustrated through an intensive simulation study as well as an analysis of the well-known Wisconsin Diabetic Retinopathy status data. Copyright © 2014 John Wiley & Sons, Ltd.

On the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners.

PubMed

Chen, Kevin T; Izquierdo-Garcia, David; Poynton, Clare B; Chonde, Daniel B; Catana, Ciprian

2017-03-01

To propose an MR-based method for generating continuous-valued head attenuation maps and to assess its accuracy and reproducibility. Demonstrating that novel MR-based photon attenuation correction methods are both accurate and reproducible is essential prior to using them routinely in research and clinical studies on integrated PET/MR scanners. Continuous-valued linear attenuation coefficient maps ("μ-maps") were generated by combining atlases that provided the prior probability of voxel positions belonging to a certain tissue class (air, soft tissue, or bone) and an MR intensity-based likelihood classifier to produce posterior probability maps of tissue classes. These probabilities were used as weights to generate the μ-maps. The accuracy of this probabilistic atlas-based continuous-valued μ-map ("PAC-map") generation method was assessed by calculating the voxel-wise absolute relative change (RC) between the MR-based and scaled CT-based attenuation-corrected PET images. To assess reproducibility, we performed pair-wise comparisons of the RC values obtained from the PET images reconstructed using the μ-maps generated from the data acquired at three time points. The proposed method produced continuous-valued μ-maps that qualitatively reflected the variable anatomy in patients with brain tumor and agreed well with the scaled CT-based μ-maps. The absolute RC comparing the resulting PET volumes was 1.76 ± 2.33 %, quantitatively demonstrating that the method is accurate. Additionally, we also showed that the method is highly reproducible, the mean RC value for the PET images reconstructed using the μ-maps obtained at the three visits being 0.65 ± 0.95 %. Accurate and highly reproducible continuous-valued head μ-maps can be generated from MR data using a probabilistic atlas-based approach.

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

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

Climate sensitivity estimated from temperature reconstructions of the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Schmittner, A.; Urban, N.; Shakun, J. D.; Mahowald, N. M.; Clark, P. U.; Bartlein, P. J.; Mix, A. C.; Rosell-Melé, A.

2011-12-01

In 1959 IJ Good published the discussion "Kinds of Probability" in Science. Good identified (at least) five kinds. The need for (at least) a sixth kind of probability when quantifying uncertainty in the context of climate science is discussed. This discussion brings out the differences in weather-like forecasting tasks and climate-links tasks, with a focus on the effective use both of science and of modelling in support of decision making. Good also introduced the idea of a "Dynamic probability" a probability one expects to change without any additional empirical evidence; the probabilities assigned by a chess playing program when it is only half thorough its analysis being an example. This case is contrasted with the case of "Mature probabilities" where a forecast algorithm (or model) has converged on its asymptotic probabilities and the question hinges in whether or not those probabilities are expected to change significantly before the event in question occurs, even in the absence of new empirical evidence. If so, then how might one report and deploy such immature probabilities in scientific-support of decision-making rationally? Mature Probability is suggested as a useful sixth kind, although Good would doubtlessly argue that we can get by with just one, effective communication with decision makers may be enhanced by speaking as if the others existed. This again highlights the distinction between weather-like contexts and climate-like contexts. In the former context one has access to a relevant climatology (a relevant, arguably informative distribution prior to any model simulations), in the latter context that information is not available although one can fall back on the scientific basis upon which the model itself rests, and estimate the probability that the model output is in fact misinformative. This subjective "probability of a big surprise" is one way to communicate the probability of model-based information holding in practice, the probability that the information the model-based probability is conditioned on holds. It is argued that no model-based climate-like probability forecast is complete without a quantitative estimate of its own irrelevance, and that the clear identification of model-based probability forecasts as mature or immature, are critical elements for maintaining the credibility of science-based decision support, and can shape uncertainty quantification more widely.

On the quantification and efficient propagation of imprecise probabilities resulting from small datasets

NASA Astrophysics Data System (ADS)

Zhang, Jiaxin; Shields, Michael D.

2018-01-01

This paper addresses the problem of uncertainty quantification and propagation when data for characterizing probability distributions are scarce. We propose a methodology wherein the full uncertainty associated with probability model form and parameter estimation are retained and efficiently propagated. This is achieved by applying the information-theoretic multimodel inference method to identify plausible candidate probability densities and associated probabilities that each method is the best model in the Kullback-Leibler sense. The joint parameter densities for each plausible model are then estimated using Bayes' rule. We then propagate this full set of probability models by estimating an optimal importance sampling density that is representative of all plausible models, propagating this density, and reweighting the samples according to each of the candidate probability models. This is in contrast with conventional methods that try to identify a single probability model that encapsulates the full uncertainty caused by lack of data and consequently underestimate uncertainty. The result is a complete probabilistic description of both aleatory and epistemic uncertainty achieved with several orders of magnitude reduction in computational cost. It is shown how the model can be updated to adaptively accommodate added data and added candidate probability models. The method is applied for uncertainty analysis of plate buckling strength where it is demonstrated how dataset size affects the confidence (or lack thereof) we can place in statistical estimates of response when data are lacking.

The impact of fibromyalgia on health status according to the types, demographic background and pain index.

PubMed

Ghavidel-Parsa, Banafsheh; Bidari, Ali; Maafi, Alireza A; Hassankhani, Amir; Hajiabbasi, Asghar; Montazeri, Ali; Sanaei, Omid; Ghalehbaghi, Babak

2016-01-01

To compare fibromyalgia (FM) core symptoms, FM impact severity and health status between the recently defined type A and type B of fibromyalgia. To compare disease impact and health status between FM patients and non-FM chronic pain control group. Finally, to compare health related quality of life and disease symptom severity by demographic background and widespread pain index (WPI). A total of 284 consecutive FM patients and 96 non-FM control patients were enrolled. The information of four questionnaires including the Fibromyalgia Survey Questionnaire (FSQ), the Fibromyalgia Impact Questionnaire (FIQ), the 12-item Short Form Health Survey (SF-12) and questionnaires regarding demographic features were collected from a local FM registry. Of all FM patients, 102 (94%) and 7 (6%) were type A and B, respectively. We found statistically significant differences in symptomatology, the FIQ scores and the SF-12 subscales across two type and control groups (p<0.001). However, when we compared these scores pairwise, except WPI there were no significant differences in other scores between type A and B. Also, there were no significant differences in FIQ and SF-12 scores across different age or educational status groups. Interestingly, patients with higher WPI had significantly higher FIQ (overall, symptom, and total) scores, worse PCS-12 and MCS-12 scores, and vice versa. Type B constitutes a minor but important component of FM that probably has a marked impact on the patient's perceived illness severity and quality of life. Further, WPI probably is the most important single indicator of disease severity and quality of life in FM.

Geometric measure of pairwise quantum discord for superpositions of multipartite generalized coherent states

NASA Astrophysics Data System (ADS)

Daoud, M.; Ahl Laamara, R.

2012-07-01

We give the explicit expressions of the pairwise quantum correlations present in superpositions of multipartite coherent states. A special attention is devoted to the evaluation of the geometric quantum discord. The dynamics of quantum correlations under a dephasing channel is analyzed. A comparison of geometric measure of quantum discord with that of concurrence shows that quantum discord in multipartite coherent states is more resilient to dissipative environments than is quantum entanglement. To illustrate our results, we consider some special superpositions of Weyl-Heisenberg, SU(2) and SU(1,1) coherent states which interpolate between Werner and Greenberger-Horne-Zeilinger states.

Anisotropic Invariance and the Distribution of Quantum Correlations.

PubMed

Cheng, Shuming; Hall, Michael J W

2017-01-06

We report the discovery of two new invariants for three-qubit states which, similarly to the three-tangle, are invariant under local unitary transformations and permutations of the parties. These quantities have a direct interpretation in terms of the anisotropy of pairwise spin correlations. Applications include a universal ordering of pairwise quantum correlation measures for pure three-qubit states; trade-off relations for anisotropy, three-tangle and Bell nonlocality; strong monogamy relations for Bell inequalities, Einstein-Podolsky-Rosen steering inequalities, geometric discord and fidelity of remote state preparation (including results for arbitrary three-party states); and a statistical and reference-frame-independent form of quantum secret sharing.

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.

Anisotropic Invariance and the Distribution of Quantum Correlations

NASA Astrophysics Data System (ADS)

Cheng, Shuming; Hall, Michael J. W.

2017-01-01

We report the discovery of two new invariants for three-qubit states which, similarly to the three-tangle, are invariant under local unitary transformations and permutations of the parties. These quantities have a direct interpretation in terms of the anisotropy of pairwise spin correlations. Applications include a universal ordering of pairwise quantum correlation measures for pure three-qubit states; trade-off relations for anisotropy, three-tangle and Bell nonlocality; strong monogamy relations for Bell inequalities, Einstein-Podolsky-Rosen steering inequalities, geometric discord and fidelity of remote state preparation (including results for arbitrary three-party states); and a statistical and reference-frame-independent form of quantum secret sharing.

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.

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.