Fractal Structure and Entropy Production within the Central Nervous System

Seely, Andrew J. E.; Newman, Kimberley D.; Herry, Christophe L.

doi:10.3390/e16084497

Cited by 21 publications

(11 citation statements)

References 132 publications

(236 reference statements)

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“…Identical patterns to the rise and fall of entropy production seen through the deteriorating path to aging are also observed in healthy versus ill individuals [236]. Namely, a decrease in cortical complexity (i.e., fractal dimension [244] of the central nervous system) with illness correlating with metabolic decline in glucose metabolism is observed in ill individuals [236,[245][246][247].…”

Section: The Second Law Health Illness Aging and Deathmentioning

confidence: 99%

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Thermodynamics: The Unique Universal Science

Haddad

2017

Entropy

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Thermodynamics is a physical branch of science that governs the thermal behavior of dynamical systems from those as simple as refrigerators to those as complex as our expanding universe. The laws of thermodynamics involving conservation of energy and nonconservation of entropy are, without a doubt, two of the most useful and general laws in all sciences. The first law of thermodynamics, according to which energy cannot be created or destroyed, merely transformed from one form to another, and the second law of thermodynamics, according to which the usable energy in an adiabatically isolated dynamical system is always diminishing in spite of the fact that energy is conserved, have had an impact far beyond science and engineering. In this paper, we trace the history of thermodynamics from its classical to its postmodern forms, and present a tutorial and didactic exposition of thermodynamics as it pertains to some of the deepest secrets of the universe.

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Section: The Second Law Health Illness Aging and Deathmentioning

confidence: 99%

“…Additionally, heat production occurs during oxygen intake with metabolism breaking down macromolecules (e.g., carbohydrates, lipids, and proteins) to free high-quality chemical energy to produce work. In both cases, this heat dissipation leads to entropy production [234][235][236].…”

Section: The Second Law Health Illness Aging and Deathmentioning

confidence: 99%

Thermodynamics: The Unique Universal Science

Haddad

2017

Entropy

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“…Entropy has been used not only in the context of CS, but also in many other scientific areas [3,29,43]. In information theory, entropy was introduced by Shannon for studying the amount of information contained in a message.…”

Section: Entropymentioning

confidence: 99%

Integer and fractional-order entropy analysis of earthquake data series

Lopes

Machado

2015

Nonlinear Dyn

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This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen-Shannon divergence are used to analyze and com-pare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advan-tage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and JensenShannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distrib-utions.

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“…Entropy has been used not only in the context of CS, but also in many other scientific areas [23][24][25]. In information theory, entropy was introduced by Shannon for studying the amount of information contained in a message.…”

Section: Entropymentioning

confidence: 99%

Multidimensional Scaling Visualization Using Parametric Similarity Indices

Machado

Galhano

2015

Entropy

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In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, and we generate the corresponding MDS maps of 'points'. Third, we use Procrustes analysis to linearly transform the MDS charts for maximum superposition and to build a global MDS map of "shapes". This final plot captures the time evolution of the phenomena and is sensitive to the PSI adopted. The generalized correlation, the Minkowski distance and four entropy-based indices are tested. The proposed approach is applied to the Dow Jones Industrial Average stock market index and the Europe Brent Spot Price FOB time-series.

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Fractal Structure and Entropy Production within the Central Nervous System

Cited by 21 publications

References 132 publications

Thermodynamics: The Unique Universal Science

Thermodynamics: The Unique Universal Science

Integer and fractional-order entropy analysis of earthquake data series

Multidimensional Scaling Visualization Using Parametric Similarity Indices

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