Detecting periodicity in experimental data using linear modeling techniques

Fourier spectral estimates and, to a lesser extent, the autocorrelation function are the primary tools to detect periodicities in experimental data in the physical and biological sciences. We propose a new method which is more reliable than traditional techniques, and is able to make clear identification of periodic behavior when traditional techniques do not. This technique is based on an information theoretic reduction of linear (autoregressive) models so that only the essential features of an autoregressive model are retained. These models we call reduced autoregressive models (RARM). The essential features of reduced autoregressive models include any periodicity present in the data. We provide theoretical and numerical evidence from both experimental and artificial data, to demonstrate that this technique will reliably detect periodicities if and only if they are present in the data. There are strong information theoretic arguments to support the statement that RARM detects periodicities if they are present. Surrogate data techniques are used to ensure the converse. Furthermore, our calculations demonstrate that RARM is more robust, more accurate, and more sensitive, than traditional spectral techniques.Comment: 10 pages (revtex) and 6 figures. To appear in Phys Rev E. Modified styl

Delay-Coordinates Embeddings as a Data Mining Tool for Denoising Speech Signals

In this paper we utilize techniques from the theory of non-linear dynamical systems to define a notion of embedding threshold estimators. More specifically we use delay-coordinates embeddings of sets of coefficients of the measured signal (in some chosen frame) as a data mining tool to separate structures that are likely to be generated by signals belonging to some predetermined data set. We describe a particular variation of the embedding threshold estimator implemented in a windowed Fourier frame, and we apply it to speech signals heavily corrupted with the addition of several types of white noise. Our experimental work seems to suggest that, after training on the data sets of interest,these estimators perform well for a variety of white noise processes and noise intensity levels. The method is compared, for the case of Gaussian white noise, to a block thresholding estimator

Factors modulating the secretion of thyrotropin and other hormones of the thyroid axis.

The first portion of this paper is devoted to an overview of the normal function of the hypothalamo-pituitary-thyroid axis. This section emphasizes areas of current research interest and it identifies several sites and mechanisms that are potentially important interfaces with toxins or toxic mechanisms. We then describe an in vitro technique for the continuous superfusion of enzymatically dispersed pituitary cells; this approach is particularly valuable in studying the dynamics of the TSH responses to the factors known (or suspected) to regulate TSH secretion in vivo. Using this technique, we have found that 10(-5)M prostaglandin (PG)I2 stimulates TSH secretion without altering the response to TRH (10(-8)M), and that this stimulation is not due to its rapid conversion to 6-keto PGF1 alpha. In contrast PGs of the E series (PGE1 and PGE2, 10(-5)M) increase responsiveness to TRH but have no effect alone. We found no effects of any of the other prostanoids tested (PGs A2, B2, F1 alpha, F2 alpha, thromboxanes A2 and B2, and the endoperoxide analog, U-44069. Somatostain (10(-9)M inhibits TRH-induced TSH secretion, but does not alter the responsiveness to PGI2. These findings suggest that somatostatin blocks TSH secretion at a point that is functionally prior to the involvement of the PGs, and perhaps does so by blocking synthesis or limiting availability of selected PGs

Dynamical modeling of collective behavior from pigeon flight data: flock cohesion and dispersion

Several models of flocking have been promoted based on simulations with qualitatively naturalistic behavior. In this paper we provide the first direct application of computational modeling methods to infer flocking behavior from experimental field data. We show that this approach is able to infer general rules for interaction, or lack of interaction, among members of a flock or, more generally, any community. Using experimental field measurements of homing pigeons in flight we demonstrate the existence of a basic distance dependent attraction/repulsion relationship and show that this rule is sufficient to explain collective behavior observed in nature. Positional data of individuals over time are used as input data to a computational algorithm capable of building complex nonlinear functions that can represent the system behavior. Topological nearest neighbor interactions are considered to characterize the components within this model. The efficacy of this method is demonstrated with simulated noisy data generated from the classical (two dimensional) Vicsek model. When applied to experimental data from homing pigeon flights we show that the more complex three dimensional models are capable of predicting and simulating trajectories, as well as exhibiting realistic collective dynamics. The simulations of the reconstructed models are used to extract properties of the collective behavior in pigeons, and how it is affected by changing the initial conditions of the system. Our results demonstrate that this approach may be applied to construct models capable of simulating trajectories and collective dynamics using experimental field measurements of herd movement. From these models, the behavior of the individual agents (animals) may be inferred

Episodic medication adherence in adolescents and young adults with perinatally acquired HIV: a within-participants approach

Due to the success of antiretroviral (ART) medications, young people living with perinatally acquired HIV (PHIV+) are now surviving into adolescence and young adulthood. Understanding factors influencing ART non-adherence in this group is important in developing effective adherence interventions. Most studies of ART adherence in HIV-positive populations assess differences in adherence levels and adherence predictors between participants, over a period of time (global adherence). Many individuals living with HIV, however, including PHIV+ young people, take medication inconsistently. To investigate this pattern of adherence, a within-participants design, focussing on specific episodes of adherence and non-adherence, is suitable (episodic adherence). A within-participants design was used with 29 PHIV+ young people (17 female, median age 17 years, range 14–22 years), enrolled in the UK Adolescents and Adults Living with Perinatal HIV cohort study. Participants were eligible if they could identify one dose of medication taken and one dose they had missed in the previous two months. For each of the two episodes (one adherent, one non-adherent), behavioural factors (whom they were with, location, routine, day, reminders) and psychological factors at the time of the episode (information about medication, adherence motivation, perceived behavioural skills to adhere to medication – derived from the Information-Motivation-Behavioural Skills (IMB) Model – and affect) were assessed in a questionnaire. Non-adherence was significantly associated with weekend days (Friday to Sunday versus Monday to Thursday, p = .001), lack of routine (p = .004), and being out of the home (p = .003), but not with whom the young person was with or whether they were reminded to take medication. Non-adherence was associated with lower levels of behavioural skills (p < .001), and lower positive affect (p = .005). Non-adherence was not significantly associated with negative affect, information about ART, or ART motivation. The use of situationally specific strategies to enhance adherence in young people who take their medication inconsistently is proposed

Model for the structure function constant for index of refraction fluctuations in Rayleigh-Benard turbulence

A model for the structure function constant associated with index of refraction fluctuations in Rayleigh-Benard turbulence is developed. The model is based upon the following assumptions: (1) the turbulence is homogeneous and isotropic at or near the mid-plane, (2) the rate of production is in balance with the rate of dissipation, (3) an inertial region exists, and (4) estimates for the rate of dissipation of temperature fluctuations and of turbulent kinetic energy can be made by assuming that the large-scale turbulence is dissipated in one eddy turnover time. From these assumptions, the dependence of the structure function on the geometry, heat flux, and the properties of the fluid is obtained. The model predicts that the normalized structure function constant is independent of the Rayleigh number. To verify the model, numerical simulations of Rayleigh-Benard turbulence were performed using two different approaches: an in-house code based on a pseudo-spectral method, and a finite volume code which employs a model for the smallest scales of the turbulence. The model was found to agree with the results of the simulations, thereby lending support for the assumptions underlying the theory.Comment: 25 pages, 10 figures, 1 tabl

The Lean Index: Operational "Lean" Metrics for the Wood Products Industry

No standard definition for lean production exists today, especially specific to the wood products industries. From a management point of view, even the more straightforward management issues surrounding the concept of "lean" are complex. This exploratory research seeks to develop a methodology for quantitative and objective assessment of the leanness of any wood products operation. Factor analysis is a statistical approach that describes the patterns of relationships among quantifiable predictor variables, with the goal of identifying variables that cannot be directly measured, such as the leanness of a company. Using this technique, a factor model was identified and a factor score, or "Lean Index," was developed. For the nine wood products companies included in this study, the average Lean Index is demonstrated to be 5.07, ranging from a low of 2.33 to a high of 12.00. Based on the quantified standards of lean production developed in this study, (1) primary wood products operations are inherently leaner than secondary wood products operations; (2) process throughput variables explain approximately twice the total variance of all consumed resources, compared to process support variables; and (3) energy consumption is shown to be the single most significant contributor to the leanness of any wood products company