Fractal structure in the color distribution of natural images

The colorimetric organization of RGB color images is investigated through the computation of the correlation integral of their three-dimensional histogram. For natural color images, as a common behavior, the correlation integral is found to follow a power law, with a noninteger exponent characteristic of a given image. This behavior identifies a fractal or multiscale self-similar distribution of the colors contained in typical natural images. This finding of a possible fractal structure in the colorimetric organization of natural images complement other fractal properties previously observed in their spatial organization. Such fractal colorimetric properties may be helpful to the characterization and modeling of natural images, and may contribute to progress in vision

Fine and ultrafine particle number and size measurements from industrial combustion processes : primary emissions field data

This study is to our knowledge the first to present the results of on-line measurements of residual nanoparticle numbers downstream of the flue gas treatment systems of a wide variety of medium- and large-scale industrial installations. Where available, a semi-quantitative elemental composition of the sampled particles is carried out using a Scanning Electron Microscope coupled with an Energy Dispersive Spectrometer (SEM-EDS). The semi-quantitative elemental composition as a function of the particle size is presented. EU's Best Available Technology documents (BAT) show removal efficiencies of Electrostatic Precipitator (ESP) and bag filter dedusting systems exceeding 99% when expressed in terms of weight. Their efficiency decreases slightly for particles smaller than 1 mu m but when expressed in terms of weight, still exceeds 99% for bag filters and 96% for ESP. This study reveals that in terms of particle numbers, residual nanoparticles (NP) leaving the dedusting systems dominate by several orders of magnitude. In terms of weight, all installations respect their emission limit values and the contribution of NP to weight concentrations is negligible, despite their dominance in terms of numbers. Current World Health Organisation regulations are expressed in terms of PM2.5 wt concentrations and therefore do not reflect the presence or absence of a high number of NP. This study suggests that research is needed on possible additional guidelines related to NP given their possible toxicity and high potential to easily enter the blood stream when inhaled by humans

Multifractality, sample entropy, and wavelet analyses for age-related changes in the peripheral cardiovascular system: Preliminary results

Using signal processing measures we evaluate the effect of aging on the peripheral cardiovascular system. Laser Doppler flowmetry (LDF) signals, reflecting the microvascular perfusion, are recorded on the forearm of 27 healthy subjects between 20–30, 40–50, or 60–70 years old. Wavelet-based representations, Hölder exponents, and sample entropy values are computed for each time series. The results indicate a possible modification of the peripheral cardiovascular system with aging. Thus, the endothelial-related metabolic activity decreases, but not significantly, with aging. Furthermore, LDF signals are more monofractal for elderly subjects than for young people for whom LDF signals are weakly multifractal: the average range of Hölder exponents computed with a parametric generalized quadratic variation based estimation method is 0.13 for subjects between 20 and 30 years old and 0.06 for subjects between 60 and 70 years old. Moreover, the average mean sample entropy value of LDF signals slightly decreases with age: it is 1.34 for subjects between 20 and 30 years old and 1.19 for subjects between 60 and 70 years old. Our results could assist in gaining knowledge on the relationship between microvascular system status and age and could also lead to a more accurate age-related nonlinear modeling

Multiscale Analysis of Microvascular Blood Flow: A Multiscale Entropy Study of Laser Doppler Flowmetry Time Series

Processes regulating the cardiovascular system (CVS) are numerous. Each possesses several temporal scales. Their interactions lead to interdependences across multiple scales. For the CVS analysis, different multiscale studies have been proposed, mostly performed on heart rate variability signals (HRV) reflecting the central CVS; only few were dedicated to data from the peripheral CVS, such as laser Doppler flowmetry (LDF) signals. Very recently, a study implemented the first computation of multiscale entropy for LDF signals. A nonmonotonic evolution of multiscale entropy with two distinctive scales was reported, leading to a markedly different behavior from the one of HRV. Our goal herein is to confirm these results and to go forward in the investigations on origins of this behavior. For this purpose, 12 LDF signals recorded simultaneously on the two forearms of six healthy subjects are processed. This is performed before and after application of physiological scales-based filters aiming at isolating previously found frequency bands linked to physiological activities. The results obtained with signals recorded simultaneously on two different sites of each subject show a probable central origin for the nonmonotonic behavior. The filtering results lead to the suggestion that origins of the distinctive scales could be dominated by the cardiac activity

Fisher information and Shannon entropy for on-line detection of transient signal high-values in laser Doppler flowmetry signals of healthy subjects

Laser Doppler flowmetry (LDF) is an easy-to-use method for the assessment of microcirculatory blood flow in tissues. However, LDF recordings very often present TRAnsient Signal High-values (TRASH), generally of a few seconds. These TRASH can come from tissue motions, optical fibre movements, movements of the probe head relative to the tissue, etc. They often lead to difficulties in signal global interpretations. In order to test the possibility of detecting automatically these TRASH for their removal, we process noisy and noiseless LDF signals with two indices from information theory, namely Fisher information and Shannon entropy. For this purpose, LDF signals from 13 healthy subjects are recorded at rest, during vascular occlusion of 3 min, and during post-occlusive hyperaemia. Computation of Fisher information and Shannon entropy values shows that, when calibrated, these two indices can be complementary to detect TRASH and be insensitive to the rapid increases of blood flow induced by post-occlusive hyperaemia. Moreover, the real-time algorithm has the advantage of being easy to implement and does not require any frequency analysis. This study opens new fields of application for Fisher information and Shannon entropy: LDF \u27denoising\u27