Marginal nonparametric inference for waiting times in multistage models : hypothesis testing and regression.

Marginal inference for waiting times in multi-stage time-to-event models is complicated by right censoring of observations as well as the prior history of events in the model. In general, complications arise due to the evolution of the censoring process in so called calendar time , contrasted with the evolution of the waiting time process conditional upon entry into a given stage. Developments in inference for survival data under dependent censoring have been extended to the multi-stage framework, and non parametric estimators for the cumulative hazard function and survival function for waiting times analogous of the classical Nelson-Aalen and Kaplan-Meier estimators for survival data have been developed. These estimators were derived under the principle of weighting the basic at-risk and event counting processes by the inverse probability of censoring. We extend this concept to K-sample hypothesis testing and non parametric regression, and define test statistics and regression coefficient estimators analogous to the log-rank test and Aalen\u27s nonparametric linear regression estimators for survival data. We examine the asymptotic distribution of these statistics, and justify their use via simulation studies and analyses of real data sets

Prediction of Maximal Oxygen Consumption from Rating of Perceived Exertion (RPE) using a Modified Total-body Recumbent Stepper

International Journal of Exercise Science 8(4): 414-424, 2015. Exercise training is crucial to improve cardiovascular health and quality of life in people with spinal cord injuries (SCI). A key limitation is the lack of validated submaximal tests to evaluate and predict cardiovascular fitness in this population. The purpose of this study was to validate a submaximal test to predict maximal oxygen consumption for individuals with SCI. Ten able-bodied participants and two individuals with SCI completed a rating of perceived exertion (RPE)-based submaximal oxygen consumption test and a graded maximal oxygen consumption test on a NuStep T4 recumbent stepper. Prediction of VO2max from an RPE-based protocol is feasible and can produce reliable predicted VO2max values in the able bodied population. This study is a proof of concept to the implementation of a submaximal test protocol using a total body recumbent stepper to predict VO2max in able-bodied individuals. Additionally, this study shows evidence of feasibility of performing this test in SCI individuals

Dataset on Psychosocial Risk Factors in Cases of Fatal and Near-Fatal Physical Child Abuse

This article presents the psychosocial risk factors identified in the cases of 20 children less than four years of age who were victims of fatal or near-fatal physical abuse during a 12 month period in the Commonwealth of Kentucky. These data are related to the article “History, injury, and psychosocial risk factor commonalities among cases of fatal and near-fatal physical child abuse” (Pierce et al., 2017) [1]

Tomographic Separation of Composite Spectra. IX. The Massive Close Binary HD 115071

We present the first orbital elements for the massive close binary, HD 115071, a double-lined spectroscopic binary in a circular orbit with a period of 2.73135 +/- 0.00003 days. The orbital semiamplitudes indicate a mass ratio of M_2/M_1 = 0.58 +/- 0.02 and yet the stars have similar luminosities. We used a Doppler tomography algorithm to reconstruct the individual component optical spectra, and we applied well known criteria to arrive at classifications of O9.5 V and B0.2 III for the primary and secondary, respectively. We present models of the Hipparcos light curve of the ellipsoidal variations caused by the tidal distortion of the secondary, and the best fit model for a Roche-filling secondary occurs for an inclination of i = 48.7 +/- 2.1 degrees. The resulting masses are 11.6 +/- 1.1 and 6.7 +/- 0.7 solar masses for the primary and secondary, respectively, so that both stars are very overluminous for their mass. The system is one of only a few known semi-detached, Algol-type binaries that contain O-stars. We suggest that the binary has recently emerged from extensive mass transfer (possibly through a delayed contact and common envelope process).Comment: Submitted to Ap

Tomographic Separation of Composite Spectra. X. The Massive Close Binary HD 101131

We present the first orbital elements for the massive close binary, HD 101131, one of the brightest objects in the young, open cluster, IC 2944. This system is a double-lined spectroscopic binary in an elliptical orbit with a period of 9.64659 +/- 0.00012 days. It is a young system of unevolved stars (approximately 2 million years old) that are well within their critical Roche surfaces. We use a Doppler tomography algorithm to reconstruct the individual component optical spectra, and we apply well known criteria to arrive at classifications of O6.5 V((f)) and O8.5 V for the primary and secondary, respectively. We compare the reconstructed spectra of the components to single star, spectrum standards to determine a flux ratio of f_2/f_1 = 0.55 +/- 0.08 in the V-band. Both components are rotating faster than synchronously. We estimate the temperatures and luminosities of the components from the observed spectral classifications, composite V magnitude, and cluster distance modulus. The lower limits on the masses derived from the orbital elements and the lack of eclipses are 25 solar masses and 14 solar masses for the primary and secondary, respectively. These limits are consistent with the larger masses estimated from the positions of the stars in the Hertzsprung-Russell diagram and evolutionary tracks for single stars.Comment: 17 pages, 3 figures, submitted to Ap

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

What Is a Representative Brain? Neuroscience Meets Population Science

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain–behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective—population neuroscience—that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

The Science of Pronominal Usage: He and It in Co-Reference to Inanimate Objects in Late Middle English Texts on Alchemy

This is the author's accepted manuscript. The published version can be found at http://dx.doi.org/10.1177/0075424210384225This article explores the variation between he and it in coreference to inanimate entities (such as mercury, sulfur, and salt). Using alchemical texts from the fifteenth century as material, the article demonstrates that there was much more variation in pronominal reference in this period than has previously been shown. Of the possible explanations suggested by previous research, the earlier grammatical gender system and transference from Latin do not seem to play a role, while pronoun clustering and pronominal reanalysis appear to influence the quantitative distribution. The scale of individuation used by Siemund and Stenroos to explain similar usage is shown not to be a straightforward predictor. Other factors such as personification and perceived similarities between animate and inanimate entities may affect the degree of perceived individuation. The choice of he over she seems to be influenced by pronominal reanalysis and straightforward personification in some cases. In other instances, it is speculated that the he usage reflects (stereotypical) gender conceptions in the Middle Ages