Local Dimensionality Reduction for Non-Parametric Regression

Locally-weighted regression is a computationally-efficient technique for non-linear regression. However, for high-dimensional data, this technique becomes numerically brittle and computationally too expensive if many local models need to be maintained simultaneously. Thus, local linear dimensionality reduction combined with locally-weighted regression seems to be a promising solution. In this context, we review linear dimensionalityreduction methods, compare their performance on non-parametric locally-linear regression, and discuss their ability to extend to incremental learning. The considered methods belong to the following three groups: (1) reducing dimensionality only on the input data, (2) modeling the joint input-output data distribution, and (3) optimizing the correlation between projection directions and output data. Group 1 contains principal component regression (PCR); group 2 contains principal component analysis (PCA) in joint input and output space, factor analysis, and probabilistic PCA; and group 3 contains reduced rank regression (RRR) and partial least squares (PLS) regression. Among the tested methods, only group 3 managed to achieve robust performance even for a non-optimal number of components (factors or projection directions). In contrast, group 1 and 2 failed for fewer components since these methods rely on the correct estimate of the true intrinsic dimensionality. In group 3, PLS is the only method for which a computationally-efficient incremental implementation exists

Bayesian Integration and Non-Linear Feedback Control in a Full-Body Motor Task

A large number of experiments have asked to what degree human reaching movements can be understood as being close to optimal in a statistical sense. However, little is known about whether these principles are relevant for other classes of movements. Here we analyzed movement in a task that is similar to surfing or snowboarding. Human subjects stand on a force plate that measures their center of pressure. This center of pressure affects the acceleration of a cursor that is displayed in a noisy fashion (as a cloud of dots) on a projection screen while the subject is incentivized to keep the cursor close to a fixed position. We find that salient aspects of observed behavior are well-described by optimal control models where a Bayesian estimation model (Kalman filter) is combined with an optimal controller (either a Linear-Quadratic-Regulator or Bang-bang controller). We find evidence that subjects integrate information over time taking into account uncertainty. However, behavior in this continuous steering task appears to be a highly non-linear function of the visual feedback. While the nervous system appears to implement Bayes-like mechanisms for a full-body, dynamic task, it may additionally take into account the specific costs and constraints of the task

Co-bedding as a Comfort measure For Twins undergoing painful procedures (CComForT Trial)

<p>Abstract</p> <p>Background</p> <p>Co-bedding, a developmental care strategy, is the practice of caring for diaper clad twins in one incubator (versus separating and caring for each infant in separate incubators), thus creating the opportunity for skin-to-skin contact and touch between the twins. In studies of mothers and their infants, maternal skin-to-skin contact has been shown to decrease procedural pain response according to both behavioral and physiological indicators in very preterm neonates. It is uncertain if this comfort is derived solely from maternal presence or from stabilization of regulatory processes from direct skin contact. The intent of this study is to compare the comfort effect of co-bedding (between twin infants who are co-bedding and those who are not) on infant pain response and physiologic stability during a tissue breaking procedure (heelstick).</p> <p>Methods/Design</p> <p>Medically stable preterm twin infants admitted to the Neonatal Intensive Care Unit will be randomly assigned to a co-bedding group or a standard care group. Pain response will be measured by physiological and videotaped facial reaction using the Premature Infant Pain Profile scale (PIPP). Recovery from the tissue breaking procedure will be determined by the length of time for heart rate and oxygen saturation to return to baseline. Sixty four sets of twins (n = 128) will be recruited into the study. Analysis and inference will be based on the intention-to-treat principle.</p> <p>Discussion</p> <p>If twin contact while co-bedding is determined to have a comforting effect for painful procedures, then changes in current neonatal care practices to include co-bedding may be an inexpensive, non invasive method to help maintain physiologic stability and decrease the long term psychological impact of procedural pain in this high risk population. Knowledge obtained from this study will also add to existing theoretical models with respect to the exact mechanism of comfort through touch.</p> <p>Trial registration</p> <p>NCT00917631</p

The potential for immunoglobulins and host defense peptides (HDPs) to reduce the use of antibiotics in animal production

Abstract Innate defense mechanisms are aimed at quickly containing and removing infectious microorganisms and involve local stromal and immune cell activation, neutrophil recruitment and activation and the induction of host defense peptides (defensins and cathelicidins), acute phase proteins and complement activation. As an alternative to antibiotics, innate immune mechanisms are highly relevant as they offer rapid general ways to, at least partially, protect against infections and enable the build-up of a sufficient adaptive immune response. This review describes two classes of promising alternatives to antibiotics based on components of the innate host defense. First we describe immunoglobulins applied to mimic the way in which they work in the newborn as locally acting broadly active defense molecules enforcing innate immunity barriers. Secondly, the potential of host defense peptides with different modes of action, used directly, induced in situ or used as vaccine adjuvants is described

Movement Timing and Invariance Arise from Several Geometries

Human movements show several prominent features; movement duration is nearly independent of movement size (the isochrony principle), instantaneous speed depends on movement curvature (captured by the 2/3 power law), and complex movements are composed of simpler elements (movement compositionality). No existing theory can successfully account for all of these features, and the nature of the underlying motion primitives is still unknown. Also unknown is how the brain selects movement duration. Here we present a new theory of movement timing based on geometrical invariance. We propose that movement duration and compositionality arise from cooperation among Euclidian, equi-affine and full affine geometries. Each geometry posses a canonical measure of distance along curves, an invariant arc-length parameter. We suggest that for continuous movements, the actual movement duration reflects a particular tensorial mixture of these canonical parameters. Near geometrical singularities, specific combinations are selected to compensate for time expansion or compression in individual parameters. The theory was mathematically formulated using Cartan's moving frame method. Its predictions were tested on three data sets: drawings of elliptical curves, locomotion and drawing trajectories of complex figural forms (cloverleaves, lemniscates and limaçons, with varying ratios between the sizes of the large versus the small loops). Our theory accounted well for the kinematic and temporal features of these movements, in most cases better than the constrained Minimum Jerk model, even when taking into account the number of estimated free parameters. During both drawing and locomotion equi-affine geometry was the most dominant geometry, with affine geometry second most important during drawing; Euclidian geometry was second most important during locomotion. We further discuss the implications of this theory: the origin of the dominance of equi-affine geometry, the possibility that the brain uses different mixtures of these geometries to encode movement duration and speed, and the ontogeny of such representations

Chloroplast DNA Microsatellites Reveal Contrasting Phylogeographic Structure in Mahogany (Swietenia macrophylla King, Meliaceae) from Amazonia and Central America

Big-leaf mahogany (Swietenia macrophylla) is one of the most valuable and overharvested timber trees of tropical America. A description of the organization of genetic variation across its broad range would be useful for management of genetic diversity and for understanding its demographic history. Here we report on a phylogeographic analysis of mahogany based on six polymorphic cpDNA simple sequence repeat loci (cpSSRs) genotyped in 16 populations distributed across the Brazilian Amazon and Mesoamerica (N = 245 individuals). Of the 31 cpDNA haplotypes identified, 15 occurred in Amazonia and 16 in Mesoamerica with no single haplotype shared between the two regions. The populations from Central America showed moderate differentiation (FST = 0.36) while within population genetic diversity was generally high (mean Nei's HE = 0.639). In contrast, the Amazonian populations were strongly differentiated (FST = 0.95) and contained low haplotype diversity (mean HE = 0.176), with the exception of the highly diverse Marajoara population from the Eastern Amazon (HE = 0.925). SAMOVA identified a single Mesoamerican phylogroup and four Amazonian phylogroups, indicating stronger phylogeographic structure within Amazonia. The results demonstrate high levels of cpDNA variation and differentiation of regional S. macrophylla populations, and provide the first evidence of a major phylogeographic break between Mesoamerican and South American mahogany populations