This study was designed to examine the biomechanical and physiological responses between cycling on the Axiom stationary ergometer (Axiom, Elite, Fontaniva, Italy) vs. field conditions for both uphill and level ground cycling. Nine cyclists performed cycling bouts in the laboratory on an Axiom stationary ergometer and on their personal road bikes in actual road cycling conditions in the field with three pedaling cadences during uphill and level cycling. Gross efficiency and cycling economy were lower (-10%) for the Axiom stationary ergometer compared with the field. The preferred pedaling cadence was higher for the Axiom stationary ergometer conditions compared with the field conditions only for uphill cycling. Our data suggests that simulated cycling using the Axiom stationary ergometer differs from actual cycling in the field. These results should be taken into account notably for improving the precision of the model of cycling performance, and when it is necessary to compare two cycling test conditions (field/laboratory, using different ergometers).
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http://dx.doi.org/10.1123/jab.28.6.636 | DOI Listing |
Mon Hefte Math
June 2022
Facultat de Matemàtiques i Informàtica, Universitat de Barcelona, Gran via de les Corts Catalanes 585, 08007 Barcelona, Spain.
We study the influence of strong forcing axioms on the complexity of the non-stationary ideal on and its restrictions to certain cofinalities. Our main result shows that the strengthening of Martin's Maximum does not decide whether the restriction of the non-stationary ideal on to sets of ordinals of countable cofinality is -definable by formulas with parameters in . The techniques developed in the proof of this result also allow us to prove analogous results for the full non-stationary ideal on and strong forcing axioms that are compatible with .
View Article and Find Full Text PDFEntropy (Basel)
August 2020
ASML, De Run 6501, 5504 DR Veldhoven, The Netherlands.
Based on the conceptual basis of information theory, we propose a novel mutual information measure-'path-based mutual information'. This information measure results from the representation of a set of random variables as a probabilistic graphical model. The edges in this graph are modeled as discrete memoryless communication channels, that is, the underlying data is ergodic, stationary, and the Markov condition is assumed to be applicable.
View Article and Find Full Text PDFEntropy (Basel)
October 2018
HCSoft Programación S.L., 30007 Murcia, Spain.
Entropy appears in many contexts (thermodynamics, statistical mechanics, information theory, measure-preserving dynamical systems, topological dynamics, etc.) as a measure of different properties (energy that cannot produce work, disorder, uncertainty, randomness, complexity, etc.).
View Article and Find Full Text PDFJ Appl Biomech
December 2012
Laboratoire d'Ingénierie et Sciences des Matériaux (EA 4695), UFR STAPS, Université de Reims-Champagne-Ardenne, Reims, France.
This study was designed to examine the biomechanical and physiological responses between cycling on the Axiom stationary ergometer (Axiom, Elite, Fontaniva, Italy) vs. field conditions for both uphill and level ground cycling. Nine cyclists performed cycling bouts in the laboratory on an Axiom stationary ergometer and on their personal road bikes in actual road cycling conditions in the field with three pedaling cadences during uphill and level cycling.
View Article and Find Full Text PDFJ Clin Neurophysiol
June 2006
Department of Engineering Science, The University of Auckland, Auckland, New Zealand.
Independent component analysis (ICA) has recently been applied to epileptic seizure in the EEG. In this paper, the authors show how the fundamental axioms required for ICA to be valid are broken. Four common cases of childhood seizure are presented and assessed for stationarity and an eigenvalue analysis is applied.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!