Functional methods for time series prediction: a nonparametric approach

The problem of prediction in time series using nonparametric functional techniques is considered. An extension of the local linear method to regression with functional explanatory variable is proposed. This forecasting method is compared with the functional Nadaraya–Watson method and with finite‐dimensional nonparametric predictors for several real‐time series. Prediction intervals based on the bootstrap and conditional distribution estimation for those nonparametric methods are also compared. Copyright © 2010 John Wiley & Sons, Ltd.     

Expression of an insulin-regulatable glucose carrier in muscle and fat endothelial cells

Insulin rapidly stimulates glucose use in the major target tissues, muscle and fat, by modulating a tissue-specific glucose transporter isoform. Access of glucose to the target tissue is restricted by endothelial cells which line the walls of nonfenestrated capillaries of fat and muscle. Thus, we examined whether the capillary endothelial cells are actively involved in the modulation of glucose availability by these tissues. We report here the abundant expression of the muscle/fat glucose transporter isoform in endothelial cells, using an immunocytochemical analysis with a monoclonal antibody specific for this isoform. This expression is restricted to endothelial cells from the major insulin target tissues, and it is not detected in brain and liver where insulin does not activate glucose transport. The expression of the muscle/fat transporter isoform in endothelial cells is significantly greater than in the neighbouring muscle and fat cells. Following administration of insulin to animals in vivo, there occurs a rapid increase in the number of muscle/fat transporters present in the lumenal plasma membrane of the capillary endothelial cells. These results document that insulin promotes the translocation of the muscle/fat glucose transporter in endothelial cells. It is therefore likely that endothelial cells play an important role in the regulation of glucose use by the major insulin target tissues in normal and diseased states.     

Comparing Several Parametric and Nonparametric Approaches to Time Series Clustering: A Simulation Study

One key point in cluster analysis is to determine a similarity or dissimilarity measure between data objects. When working with time series, the concept of similarity can be established in different ways. In this paper, several non-parametric statistics originally designed to test the equality of the log-spectra of two stochastic processes are proposed as dissimilarity measures between time series data. Their behavior in time series clustering is analyzed throughout a simulation study, and compared with the performance of several model-free and model-based dissimilarity measures. Up to three different classification settings were considered: (i) to distinguish between stationary and non-stationary time series, (ii) to classify different ARMA processes and (iii) to classify several non-linear time series models. As it was expected, the performance of a particular dissimilarity metric strongly depended on the type of processes subjected to clustering. Among all the measures studied, the nonparametric distances showed the most robust behavior.     

From molecular noise to behavioural variability in a single bacterium

The chemotaxis network that governs the motion of Escherichia coli has long been studied to gain a general understanding of signal transduction. Although this pathway is composed of just a few components, it exhibits some essential characteristics of biological complexity, such as adaptation and response to environmental signals. In studying intracellular networks, most experiments and mathematical models have assumed that network properties can be inferred from population measurements. However, this approach masks underlying temporal fluctuations of intracellular signalling events. We have inferred fundamental properties of the chemotaxis network from a noise analysis of behavioural variations in individual bacteria. Here we show that certain properties established by population measurements, such as adapted states, are not conserved at the single-cell level: for timescales ranging from seconds to several minutes, the behaviour of non-stimulated cells exhibit temporal variations much larger than the expected statistical fluctuations. We find that the signalling network itself causes this noise and identify the molecular events that produce it. Small changes in the concentration of one key network component suppress temporal behavioural variability, suggesting that such variability is a selected property of this adaptive system.     

Science of winning soccer: Emergent pattern-forming dynamics in association football

Quantitative analysis is increasingly being used in team sports to better understand performance in these stylized, delineated, complex social systems. Here, the authors provide a first step toward understanding the pattern-forming dynamics that emerge from collective offensive and defensive behavior in team sports. The authors propose a novel method of analysis that captures how teams occupy sub-areas of the field as the ball changes location. The authors use this method to analyze a game of association football (soccer) based upon a hypothesis that local player numerical dominance is key to defensive stability and offensive opportunity. The authors find that the teams consistently allocated more players than their opponents in sub-areas of play closer to their own goal. This is consistent with a predominantly defensive strategy intended to prevent yielding even a single goal. The authors also find differences between the two teams’ strategies: while both adopted the same distribution of defensive, midfield, and attacking players (a 4: 3: 3 system of play), one team was significantly more effective in maintaining both defensive and offensive numerical dominance for defensive stability and offensive opportunity. That team indeed won the match with an advantage of one goal (2 to 1) but the analysis shows the advantage in play was more pervasive than the single goal victory would indicate. The proposed focus on the local dynamics of team collective behavior is distinct from the traditional focus on individual player capability. It supports a broader view in which specific player abilities contribute within the context of the dynamics of multiplayer team coordination and coaching strategy. By applying this complex system analysis to association football, the authors can understand how players’ and teams’ strategies result in successful and unsuccessful relationships between teammates and opponents in the area of play.     

Microstructure and properties of laser direct deposited CuNi17Al3Fe1.5Cr alloy

Thin walls of a copper-base alloy with the nominal composition CuNi17Al3Fe1.5Cr were successfully prepared by laser direct deposition additive manufacturing. The microstructure, as revealed by optical and scanning electron microscopy, indicated that the deposited material was fully dense and with a dendritic microstructure. The dendrites are parallel to the build-up direction, which is also the heat conduction direction during deposition. X-ray diffraction analysis results show that the deposited material is composed of a single phase and a copper-based solid solution. Some precipitate particles of metal silicides were observed in the interdendritic region by scanning electron microscopy. The ultimate tensile strength along the laser scanning direction reaches 735 MPa. The hardness is about Hv_0.1 300.