February 20, 2013

Record 1 of 10.

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Title:

Random walk as a null model for high-dimensional morphometrics of fossil series: geometrical considerations

Author Full Names:

Bookstein, Fred L.

Source:

PALEOBIOLOGY, 39 (1):52-74; WIN 2013

Abstract:

Over the past quarter-century there has been considerable innovation in methods for assessing the tempo and mode of evolution in paleobiological data sets. The current literature of these methods centers on three competing hypotheses-stasis, random walk, and directional trend-corresponding to an increasing scaling of variance with time interval (unchanging, for stasis; linear, for random walk; quadratic, for trend). For applications to a single trait there are powerful methods for discriminating among these hypotheses; but for multivariate data sets, especially the very high-dimensional multivariate data arising in image-feature-based and morphometric studies, current statistical approaches appear to be of less help. This paper proves that in the limiting case of high-dimensional morphospaces, the principal component or principal coordinate ordination of every sufficiently lengthy isotropic random walk tends to the same geometrical shape, which is not that of an ellipsoid an! d for which the principal components or coordinates are not independent even though they are uncorrelated. Specifically, the "scatter" of PC1 against PC2 is just a parabolic curve. The quantitative characteristics of this specific shape are not described appropriately by the corresponding "covariance structure" or Gaussian model, and the discrepancy may be pertinent to much of the existing literature of methods for differentiating among those three models of evolutionary multivariate time series. From a close examination of this common geometry of the ideal random walk model as seen in its principal components, I suggest a test for stasis, along with a mixed model illustrated by a reanalysis of some data of Gunz et al., and a related test for directional trend. These comments are intended to apply to all high-dimensional morphospaces, not just those arising in geometric morphometrics. Applications of principal components in this context distort high-dimensional data in ways! that have a tendency to mislead; but these distortions can be! interce pted so that studies of tempo and mode can nevertheless proceed.

Record 2 of 10.

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Title:

The inverse water wave problem of bathymetry detection

Author Full Names:

Vasan, Vishal; Deconinck, Bernard

Source:

JOURNAL OF FLUID MECHANICS, 714 562-590; 10.1017/jfm.2012.497 JAN 10 2013

Abstract:

The inverse water wave problem of bathymetry detection is the problem of deducing the bottom topography of the seabed from measurements of the water wave surface. In this paper, we present a fully nonlinear method to address this problem in the context of the Euler equations for inviscid irrotational fluid flow with no further approximation. Given the water wave height and its first two time derivatives, we demonstrate that the bottom topography may be reconstructed from the numerical solution of a set of two coupled non-local equations. Owing to the presence of growing hyperbolic functions in these equations, their numerical solution is increasingly difficult if the length scales involved are such that the water is sufficiently deep. This reflects the ill-posed nature of the inverse problem. A new method for the solution of the forward problem of determining the water wave surface at any time, given the bathymetry, is also presented.

Record 3 of 10.

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Title:

Vertical T cell immunodominance and epitope entropy determine HIV-1 escape

Author Full Names:

Liu, Michael K. P.; Hawkins, Natalie; Ritchie, Adam J.; Ganusov, Vitaly V.; Whale, Victoria; Brackenridge, Simon; Li, Hui; Pavlicek, Jeffrey W.; Cai, Fangping; Rose-Abrahams, Melissa; Treurnicht, Florette; Hraber, Peter; Riou, Catherine; Gray, Clive; Ferrari, Guido; Tanner, Rachel; Ping, Li-Hua; Anderson, Jeffrey A.; Swanstrom, Ronald; Chavi, Core B.; Cohen, Myron; Karim, Salim S. Abdool; Haynes, Barton; Borrow, Persephone; Perelson, Alan S.; Shaw, George M.; Hahn, Beatrice H.; Williamson, Carolyn; Korber, Bette T.; Gao, Feng; Self, Steve; McMichael, Andrew; Goonetilleke, Nilu

Source:

JOURNAL OF CLINICAL INVESTIGATION, 123 (1):380-393; 10.1172/JCI65330 JAN 2013

Abstract:

HIV-1 accumulates mutations in and around reactive epitopes to escape recognition and killing by CD8(+) T cells. Measurements of HIV-1 time to escape should therefore provide information on which parameters are most important for T cell-mediated in vivo control of HIV-1. Primary HIV-1 specific T cell responses were fully mapped in 17 individuals, and the time to virus escape, which ranged from days to years, was measured for each epitope. While higher magnitude of an individual T cell response was associated with more rapid escape, the most significant T cell measure was its relative immunodominance measured in acute infection. This identified subject-level or "vertical" immunodominance as the primary determinant of in vivo CD8(+) T cell pressure in HIV-1 infection. Conversely, escape was slowed significantly by lower population variability, or entropy, of the epitope targeted. Immunodominance and epitope entropy combined to explain half of all the variability in time to esc! ape. These data explain how CD8(+) T cells can exert significant and sustained HIV-1 pressure even when escape is very slow and that within an individual, the impacts of other T cell factors on HIV-1 escape should be considered in the context of immunodominance.

Record 4 of 10.

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Title:

Modeling Criminal Careers as Departures From a Unimodal Population Age-Crime Curve: The Case of Marijuana Use

Author Full Names:

Telesca, Donatello; Erosheva, Elena A.; Kreager, Derek A.; Matsueda, Ross L.

Source:

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 107 (500):1427-1440; 10.1080/01621459.2012.716328 DEC 2012

Abstract:

A major aim of longitudinal analyses of life-course data is to describe the within- and between-individual variability in a behavioral outcome, such as crime. Statistical analyses of such data typically draw on mixture and mixed-effects growth models. In this work, we present a functional analytic point of view and develop an alternative method that models individual crime trajectories as departures from a population age crime curve. Drawing on empirical and theoretical claims in criminology, we assume a unimodal population age crime curve and allow individual expected crime trajectories to differ by their levels of offending and patterns of temporal misalignment. We extend Bayesian hierarchical curve registration methods to accommodate count data and to incorporate influence of baseline covariates on individual behavioral trajectories. Analyzing self-reported counts of yearly marijuana use from the Denver Youth Survey, we examine the influence of race and gender categories ! on differences in levels and timing of marijuana smoking. We find that our approach offers a flexible model for longitudinal crime trajectories and allows for a rich array of inferences of interest to criminologists and drug abuse researchers. This article has supplementary materials online.

Record 5 of 10.

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Title:

Experimental Data for Goldfeld's Conjecture over Function Fields

Author Full Names:

Baig, Salman; Hall, Chris

Source:

EXPERIMENTAL MATHEMATICS, 21 (4):362-374; 10.1080/10586458.2012.671638 2012

Abstract:

This paper presents empirical evidence supporting Goldfelds conjecture on the average analytic rank of a family of quadratic twists of a fixed elliptic curve in the function field setting. In particular, we consider representatives of the four classes of nonisogenous elliptic curves over with (q, 6)=1 possessing two places of multiplicative reduction and one place of additive reduction. The case of q=5 provides the largest data set as well as the most convincing evidence that the average analytic rank converges to 1/2, which we also show is a lower bound following an argument of Kowalski. The data were generated via explicit computation of the L-function of these elliptic curves, and we present the key results necessary to implement an algorithm to efficiently compute the L-function of nonisotrivial elliptic curves over by realizing such a curve as a quadratic twist of a pullback of a versal elliptic curve. We also provide a reference for our open-source library ELLFF, which! provides all the necessary functionality to compute such L-functions, and additional data on analytic rank distributions as they pertain to the density conjecture.

Record 6 of 10.

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Title:

Impact of Correlated Neural Activity on Decision-Making Performance

Author Full Names:

Cain, Nicholas; Shea-Brown, Eric

Source:

NEURAL COMPUTATION, 25 (2):289-327; FEB 2013

Abstract:

Stimulus from the environment that guides behavior and informs decisions is encoded in the firing rates of neural populations. Neurons in the populations, however, do not spike independently: spike events are correlated from cell to cell. To what degree does this apparent redundancy have an impact on the accuracy with which decisions can be made and the computations required to optimally decide? We explore these questions for two illustrative models of correlation among cells. Each model is statistically identical at the level of pairwise correlations but differs in higher-order statistics that describe the simultaneous activity of larger cell groups. We find that the presence of correlations can diminish the performance attained by an ideal decision maker to either a small or large extent, depending on the nature of the higher-order correlations. Moreover, although this optimal performance can in some cases be obtained using the standard integration-to-bound operation, in o! thers it requires a nonlinear computation on incoming spikes. Overall, we conclude that a given level of pairwise correlations, even when restricted to identical neural populations, may not always indicate redundancies that diminish decision-making performance.

Record 7 of 10.

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Title:

Deducing Multidecadal Anthropogenic Global Warming Trends Using Multiple Regression Analysis

Author Full Names:

Zhou, Jiansong; Tung, Ka-Kit

Source:

JOURNAL OF THE ATMOSPHERIC SCIENCES, 70 (1):3-8; 10.1175/JAS-D-12-0208.1 JAN 2013

Abstract:

To unmask the anthropogenic global warming trend imbedded in the climate data, multiple linear regression analysis is often employed to filter out short-term fluctuations caused by El Nino-Southern Oscillation (ENSO), volcano aerosols, and solar forcing. These fluctuations are unimportant as far as their impact on the deduced multidecadal anthropogenic trends is concerned: ENSO and volcano aerosols have very little multidecadal trend. Solar variations do have a secular trend, but it is very small and uncertain. What is important, but is left out of all multiple regression analysis of global warming so far, is a long-period oscillation called the Atlantic multidecadal oscillation (AMO). When the AMO index is included as a regressor (i.e., explanatory variable), the deduced multidecadal anthropogenic global warming trend is so impacted that previously deduced anthropogenic warming rates need to be substantially revised. The deduced net anthropogenic global warming trend has be! en remarkably steady and statistically significant for the past 100 yr.

Record 8 of 10.

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Title:

Observed Tropospheric Temperature Response to 11-yr Solar Cycle and What It Reveals about Mechanisms

Author Full Names:

Zhou, Jiansong; Tung, Ka-Kit

Source:

JOURNAL OF THE ATMOSPHERIC SCIENCES, 70 (1):9-14; 10.1175/JAS-D-12-0214.1 JAN 2013

Abstract:

Using 54 yr of NCEP reanalysis global data from 1000 to 10 hPa, this study establishes the existence and the statistical significance of the zonal-mean temperature response to the 11-yr solar cycle throughout the troposphere and parts of the lower stratosphere. Two types of statistical analysis are used: the composite-mean difference projection method, which tests the existence of the solar cycle signal level by level, and the adaptive AR(p)-t test, which tells if a particular local feature is statistically significant at the 95% confidence level. A larger area of statistical significance than that in previous published work is obtained, due to the longer record and a better trend removal process. It reveals a spatial pattern consistent with a "bottom up" mechanism, involving evaporative feedback near the tropical ocean surface and tropical vertical convection, latent heating of the tropical upper troposphere, and poleward large-scale heat transport to the polar regions. It ! provides an alternative to the currently favored "top down" mechanism involving stratospheric ozone heating.

Record 9 of 10.

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Title:

Fast Inference for the Latent Space Network Model Using a Case-Control Approximate Likelihood

Author Full Names:

Raftery, Adrian E.; Niu, Xiaoyue; Hoff, Peter D.; Yeung, Ka Yee

Source:

JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 21 (4):901-919; SI 10.1080/10618600.2012.679240 DEC 2012

Abstract:

Network models are widely used in social sciences and genome sciences. The latent space model proposed by Hoff et al. (2002), and extended by Handcock et al. (2007) to incorporate clustering, provides a visually interpretable model-based spatial representation of relational data and takes account of several intrinsic network properties. Due to the structure of the likelihood function of the latent space model, the computational cost is of order O(N-2), where N is the number of nodes. This makes it infeasible for large networks. In this article, we propose an approximation of the log-likelihood function. We adapt the case-control idea from epidemiology and construct a case-control log-likelihood, Which is an unbiased estimator of the log-full likelihood. Replacing the full likelihood by the case-control likelihood in the Markov chain Monte Carlo estimation of the latent space model reduces the computational time from O(N-2) to O(N), making it feasible for large networks. We e! valuate its performance using simulated and real data. We fit the model to a large protein-protein interaction data using the case-control likelihood and use the model fitted link probabilities to identify false positive links. Supplemental materials are available online.

Record 10 of 10.

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Title:

Measuring Microsatellite Conservation in Mammalian Evolution with a Phylogenetic Birth-Death Model

Author Full Names:

Sawaya, Sterling M.; Lennon, Dustin; Buschiazzo, Emmanuel; Gemmell, Neil; Minin, Vladimir N.

Source:

GENOME BIOLOGY AND EVOLUTION, 4 (6):748-759; 10.1093/gbe/evs050 2012

Abstract:

Microsatellites make up similar to 3% of the human genome, and there is increasing evidence that some microsatellites can have important functions and can be conserved by selection. To investigate this conservation, we performed a genome-wide analysis of human microsatellites and measured their conservation using a binary character birth-death model on a mammalian phylogeny. Using a maximum likelihood method to estimate birth and death rates for different types of microsatellites, we show that the rates at which microsatellites are gained and lost in mammals depend on their sequence composition, length, and position in the genome. Additionally, we use a mixture model to account for unequal death rates among microsatellites across the human genome. We use this model to assign a probability-based conservation score to each microsatellite. We found that microsatellites near the transcription start sites of genes are often highly conserved, and that distance from a microsatellit! e to the nearest transcription start site is a good predictor of the microsatellite conservation score. An analysis of gene ontology terms for genes that contain microsatellites near their transcription start site reveals that regulatory genes involved in growth and development are highly enriched with conserved microsatellites.