Estimation of Lyapunov spectra from space-time data

A method to estimate Lyapunov spectra from spatio-temporal data is presented, which is well-suited to be applied to experimental situations. It allows to characterize the high-dimensional chaotic states, with possibly a large number of positive Lyapunov exponents, observed in spatio-temporal chaos. The method is applied to data from a coupled map lattice

Practical implementation of nonlinear time series methods: The TISEAN package

Nonlinear time series analysis is becoming a more and more reliable tool for the study of complicated dynamics from measurements. The concept of low-dimensional chaos has proven to be fruitful in the understanding of many complex phenomena despite the fact that very few natural systems have actually been found to be low dimensional deterministic in the sense of the theory. In order to evaluate the long term usefulness of the nonlinear time series approach as inspired by chaos theory, it will be important that the corresponding methods become more widely accessible. This paper, while not a proper review on nonlinear time series analysis, tries to make a contribution to this process by describing the actual implementation of the algorithms, and their proper usage. Most of the methods require the choice of certain parameters for each specific time series application. We will try to give guidance in this respect. The scope and selection of topics in this article, as well as the implementational choices that have been made, correspond to the contents of the software package TISEAN which is publicly available from http://www.mpipks-dresden.mpg.de/~tisean . In fact, this paper can be seen as an extended manual for the TISEAN programs. It fills the gap between the technical documentation and the existing literature, providing the necessary entry points for a more thorough study of the theoretical background.Comment: 27 pages, 21 figures, downloadable software at http://www.mpipks-dresden.mpg.de/~tisea

Analysis of Vocal Disorders in a Feature Space

This paper provides a way to classify vocal disorders for clinical applications. This goal is achieved by means of geometric signal separation in a feature space. Typical quantities from chaos theory (like entropy, correlation dimension and first lyapunov exponent) and some conventional ones (like autocorrelation and spectral factor) are analysed and evaluated, in order to provide entries for the feature vectors. A way of quantifying the amount of disorder is proposed by means of an healthy index that measures the distance of a voice sample from the centre of mass of both healthy and sick clusters in the feature space. A successful application of the geometrical signal separation is reported, concerning distinction between normal and disordered phonation.Comment: 12 pages, 3 figures, accepted for publication in Medical Engineering & Physic

Identifying and modelling delay feedback systems

Systems with delayed feedback can possess chaotic attractors with extremely high dimension, even if only a few physical degrees of freedom are involved. We propose a state space reconstruction from time series data of a scalar observable, coming along with a novel method to identify and model such systems, if a single variable is fed back. Making use of special properties of the feedback structure, we can understand the structure of the system by constructing equivalent equations of motion in spaces with dimensions which can be much smaller than the dimension of the chaotic attractor. We verify our method using both numerical and experimental data

Research for policy:A study on improving the contribution of scientific knowledge to evidence-informed health policy

Research for Policy: A study on improving the contribution of scientific knowledge to evidence-informed health The approach of evidence-informed health policy-making is generally considered as the best means of safeguarding public health: governments should take into account the best available research evidence in health policy-making. Most countries have established a National Public Health Institute (NPHI) to support their government in essential public health operations by activities such as health protection, population health assessment and research to produce evidence for policy-making. However, NPHI-researchers experience that achieving contributions to health policy-making appears to be more difficult than one would expect in view of the NPHI’s mission. In the body of scientific literature on knowledge utilization, alignment between researchers and policy-makers is recognized as an important key for enhancing contributions of scientific knowledge to policy-making. In this study, we focused on research projects, conducted by a NPHI in commission of governmental organizations. We investigated how alignment in such projects is achieved and how alignment can be improved. Our aim was to determine what a practical approach is to enhance knowledge contributions from NPHIs to evidence-informed health policy-making In three case studies, we analyzed in detail the process of a NPHI research project by using Contribution Mapping, a method developed by Kok and Schuit (2012). We identified eight key areas that require special attention during the alignment with policy-makers, the alignment areas 'goal'; 'tasks and authority'; 'quality'; 'consultative structure'; 'vertical alignment'; 'organizational environment'; 'presentation' and 'relevance and timing'. The case studies revealed that achieving alignment between researchers and policy-makers needs continuous efforts and often much more time than anticipated. Although alignment is important, scientific independence is also an important value to safeguard. Thus, researchers need insights on the role of scientific knowledge in policy-making and support of their organization in undertaking alignment efforts. Due to the ever-changing context of a research project, alignment can also be easily lost. Vertical alignment in the own organization is of major importance for achieving adequate horizontal alignment at every organizational level. Since every situation asks for specific alignment efforts, generic alignment efforts cannot be determined beforehand. Instead, researchers should regularly reflect on the alignment areas during the course of their research project. Based on our findings, we developed a reflection instrument to support researchers in reflection on alignment. The R4P tool consists of open reflection questions with examples from case studies and a possible solution to the outlined problem. This allows researchers (but also policy makers) to determine systematically which alignment efforts are required at the given moment. To conclude, NPHIs and also other knowledge institutes should acknowledge that reaching alignment needs much more effort, time and resources than often presumed. Research and knowledge production in commission of governmental organizations to serve evidence-informed health policy is in fact a delicate balancing act between alignment and independence. By organizing the institute in a way that facilitates and supports this balancing act, the NPHI may optimize its contributions to health policy. Ingrid Hegger, scientific officer at the National Institute for Public Health and the Environment RIVM, will defend her thesis on this study on Wednesday, September 6, 2017 at 4 pm in the aula of Tilburg University. Promotores: Prof.Dr.Ing.Hans van Oers (Tilburg University) and Prof.Dr.Ir. Jantine Schuit (VU University Amsterdam); Co-promotor: Dr. Susan Janssen (National Institute for Public Health and the Environment RIVM)