Dataset Information

The Analysis of the Influence of Odorant's Complexity on Fractal Dynamics of Human Respiration.

ABSTRACT: One of the major challenges in olfaction research is to relate the structural features of the odorants to different features of olfactory system. However, no relationship has been yet discovered between the structure of the olfactory stimulus, and the structure of respiratory signal. This study reveals the plasticity of human respiratory signal in relation to 'complex' olfactory stimulus (odorant). We demonstrated that fractal temporal structure of respiration dynamics shifts towards the properties of the odorants used. The results show for the first time that more structurally complex a monomolecular odorant will result in less fractal respiratory signal. On the other hand, odorant with higher entropy will result the respiratory signal with lower entropy. The capability observed in this research can be further investigated and applied for treatment of patients with different respiratory diseases.

SUBMITTER: Namazi H

PROVIDER: S-EPMC4886627 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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The Analysis of the Influence of Odorant's Complexity on Fractal Dynamics of Human Respiration.

Namazi Hamidreza H Akrami Amin A Kulish Vladimir V VV

Scientific reports 20160531

One of the major challenges in olfaction research is to relate the structural features of the odorants to different features of olfactory system. However, no relationship has been yet discovered between the structure of the olfactory stimulus, and the structure of respiratory signal. This study reveals the plasticity of human respiratory signal in relation to 'complex' olfactory stimulus (odorant). We demonstrated that fractal temporal structure of respiration dynamics shifts towards the propert ...[more]

PMID: 27244590

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Project description:OBJECTIVES:To analyse trends in the academic literature applying complexity science to healthcare, focusing specifically on bibliometric characteristics and indicators of influence. DESIGN:This study reports a bibliometric analysis via a systematic search of the academic literature applying complexity science to healthcare. METHOD:A search of four academic databases was performed on 19 April 2018. Article details were downloaded and screened against inclusion criteria (peer-reviewed journal articles applying complexity science to healthcare). Publication and content data were then collected from included articles, with analysis focusing on trends over time in the types and topics of articles, and where they are published. We also analysed the influence of this body of work through citation and network analyses. RESULTS:Articles on complexity science in healthcare were published in 268 journals, though a much smaller subset was responsible for a substantial proportion of this literature. USA contributed the largest number of articles, followed by the UK, Canada and Australia. Over time, the number of empirical and review articles increased, relative to non-empirical contributions. However, in general, non-empirical literature was more influential, with a series of introductory conceptual papers being the most influential based on both overall citations and their use as index references within a citation network. The most common topics of focus were health systems and organisations generally, and education, with recent uptake in research, policy, and change and improvement. CONCLUSIONS:This study identified changes in the types of articles on complexity science in healthcare published over time, and their content. There was evidence to suggest a shift from conceptual work to the application of concrete improvement strategies and increasingly in-depth examination of complex healthcare systems. We also identified variation in the influence of this literature at article level, and to a lesser extent by topic of focus.

Dataset Information

The Analysis of the Influence of Odorant's Complexity on Fractal Dynamics of Human Respiration.

Publications

The Analysis of the Influence of Odorant's Complexity on Fractal Dynamics of Human Respiration.

Similar Datasets

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