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Copyright of Rudarsko-Geolosko-Naftni Zbornik is the property of Faculty of Mining, Geology & Petroleum Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present study investigated whether fractal dynamics can be observed during single-leg standing on a slackline. We also examined whether the temporal structure differs with skill level. To address these questions, we compared single-leg standing performance between novices (N=5) and experts (N=5) in terms of fractal dynamics in both ankles (i.e., stance and swing legs), center of mass, and head acceleration time series using detrended fluctuation analysis. Participants were required to perform single-leg standing on a slackline. To collect motion data while slacklining, we used a three-dimensional motion capture system and obtained time-series data on the position. We conducted detrended fluctuation analysis on the original acceleration time series and random shuffled time series to examine the fractal dynamics in each body part's fluctuation. Results suggest that experts showed persistent temporal structure in the swinging leg, center of mass, and head fluctuations in the horizontal direction, while that of novices did not differ from random fluctuations. These findings revealed that experts performing a single-leg standing task on a slackline show fractal dynamics. This might reflect their flexible or adaptive exploratory behavior in the performer-environment system and contribute to the dynamic stability of whole-body dynamic balancing. [ABSTRACT FROM AUTHOR]

This paper intends to assess and test long-term memory in the Euronext stock indexes returns in the search for fractal dynamics that refute the random walk hypothesis. The Hurst exponents estimated through Rescaled-Range and Detrended Fluctuation Analysis evidence long memory in the form of persistence for all markets, with the exception of CAC 40 by the DFA. However, the Rescaled-Range Tests neither reject the absence of long dependency nor reject the existence of short dependency. On the contrary, the Fractional Differencing Test supports the presence of persistence in the PSI 20, ISE 20 and OBX indexes. This suggests that these markets are more prone to predictability, but also trends that may be unexpectedly disrupted by discontinuities, exhibiting dynamics incompatible with random walk behavior and providing evidence against the weak form of efficiency and validity of the asset pricing models. [ABSTRACT FROM AUTHOR]

Cardiovascular disease is among the leading causes of mortality in chronic obstructive pulmonary disease (COPD). Nonlinear heart rate variability (NHRV) measures are markers and predictors of cardiovascular disease, particularly arrhythmias. Our aim was to investigate NHRV in patients with COPD and changes after pulmonary rehabilitation. 20-minute ECGs were used to compare NHRV (a) in 45 healthy individuals and 31 patients with COPD and (b) in 16 patients who completed rehabilitation versus 13 age- and sex-matched control patients. We studied detrended fluctuation analysis (DFA1, DFA2), fractal dimension (low, high, average FD) and sample entropy. Compared to healthy individuals, patients with COPD had lower DFA1 (p=.038). During rehabilitation high FD decreased (p=.018) and DFA2 increased (p=.043). Cluster analysis displayed an increase of DFA1 in the rehabilitation cluster with DFA1 values below 1 (p=.032). NHRV reflects altered autonomic regulation in patients with COPD. Reduced DFA1 in patients with COPD implies a stronger pro-arrhythmic substrate and altered parasympathetic modulation. [ABSTRACT FROM AUTHOR]

Anthropogenic interventions lead to various direct and indirect impacts on natural ecosystems that are often hindered by natural long-term variability, and thus their detection and evaluation remain challenging. Ecological systems are strongly affected by climate variations that typically exhibit long-term correlations capable of imitating or hindering external trends in finite-time observations, thus complicating their detection and correct attribution to either anthropogenic interventions or natural variability. Here we focus on the quantitative assessment of the alterations in the tree-ring width (TRW) of four tree species in response to the changes in the soil water regime following a drainage experiment in a dwarf-shrub type peatland forest. We consider the long-term effects of the intervention, focusing on two characteristic quantities: the durations of clusters when significant discrepancies with relevant controls could be observed in every single consecutive year, and relative trends in the data reflecting long-term, gradual changes in the ecosystem. By extrapolating pre-drainage TRW dynamics and adjusting for recent climate variations using a multivariate model, we simulate surrogate data series that act as additional controls for the post-drainage time period. By comparing the long-term dynamics of the observational TRW data series against both natural and surrogate controls over several decades following the drainage experiment, we evaluate long-term alterations and gradual trends in the tree growth dynamics and reassess the statistical significance of these effects, taking into account long-term correlations in the natural TRW variations. Our results also indicate pronounced alterations in the drought stress response characterized by significant negative trends in the tree growth dynamics following the 2010 heatwave and associated flash drought in the drained area, while no similar effect could be observed in the undrained area, indicating that the increased productivity of the forest ecosystem following the drainage likely comes at the cost of its reduced drought stress resilience. • Long-term correlations in tree-ring and climate records can imitate or hinder trends. • Extrapolated pre-experimental tree-ring data series can be used as surrogate control. • Significance of multi-year discrepancies can be re-evaluated from cluster durations. • Drainage increases productivity of forests at the cost of drought stress resilience. [ABSTRACT FROM AUTHOR]

• Detrended fluctuation analysis was applied to heart failure patients. • Short-term heart rate regulation was impaired in preserved ejection fraction. • Short and long-term heart rate regulation was impaired in heart failure. • This approach may predict autonomic dysfunction in preserved ejection fraction. The impairment of short-term heart rate regulation in patients with heart failure with preserved ejection fraction (HFpEF) can cause acute hemodynamic collapse. Detrended fluctuation analysis (DFA) is a useful tool for the diagnosis of heart diseases and the prediction of mortality. In DFA, the short-term scaling exponent α is decreased in heart failure. However, its change in HFpEF patients remains unclear. Twenty patients diagnosed with HFpEF [defined as brain natriuretic peptide (BNP) >100 pg/mL, ejection fraction (EF) ≥50%, and without significant valvular disease], 20 diagnosed with non-HFpEF (BNP > 100 pg/mL and EF < 50%), and 20 control subjects generally matched for age and gender were enrolled. Holter electrocardiography was performed, and heart rate variability was calculated. In the DFA, the scaling exponents in 1000 beats were calculated for each 15-min segment and the average of all segments was used. We compared both the short-term (<11 beats, α1) and long-term (≥11 beats, α2) scaling exponents among the three groups. In the HFpEF, non-HFpEF, and control groups, α1 was 0.73 ± 0.27, 0.66 ± 0.29, and 1.01 ± 0.20 (p < 0.01), and α2 was 0.95 ± 0.08, 0.88 ± 0.11, and 0.96 ± 0.07 (p < 0.01), respectively. The α1 exponent was significantly decreased in the HFpEF group (p < 0.01 vs. control) and the non-HFpEF group (p < 0.01 vs. control), while the α2 exponent was significantly decreased in the non-HFpEF group only (p < 0.05 vs. HFpEF and control). Short-term heart rate regulation is impaired in patients with HFpEF, while patients with non-HFpEF have both short-term and long-term impairment. [ABSTRACT FROM AUTHOR]

The present study examines the influence of a 10 km race of runners with different performance levels on time-domain measures and non-linear dynamics of HRV. Twenty-two male recreational to elite runners performed a self-paced 10 km race on asphalt with flat profile. The participants were divided into two performance groups based on their 10 km total time with a split at 40 min (fTT: fast total times, sTT: slow total times). During the race (Begin, Mid-Point, End), heart rate and RR-intervals were recorded continuously. Besides HRV time-domain measurements, fractal correlation properties using short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA) were calculated. Mean total time from fTT was significant faster compared to sTT (35:14 ± 03:15 min:sec vs. 46:34 ± 05:46 min:sec). While RMSSD and SDNN diminished strongly during the race with no differences between groups, we observed significant lower values in DFA-alpha1 at Begin for fTT. In comparison of Begin vs. Mid-Point as well as Begin vs. End a significant decrease could be determined in DFA-alpha1 for sTT. The earlier loss of correlation properties during Begin in fTT implies a fastened alteration of cardiac autonomic regulation in order to match an all-out performance attractor for maximal endurance performance. [ABSTRACT FROM AUTHOR]

• We apply Detrended Fluctuation Analysis to time series of metrics on patent collaborations. • These time series show positive, long-term correlation properties at continental scale. • Different qualitative and quantitative behaviors emerge at EU national level. • We shed light on which countries have stronger relationships with the US according to DFA. • Several associations between DFA exponents and national topological features emerge. Within the perimeter of patent collaboration networks, the average distance of collaborations and the number of countries involved per each collaboration have been shown to have increased steadily in time. Less attention, though, has been devoted to assessing whether this growth of cross-country collaborations is stable in time. To address this scientific question we focus on the identification of long-term correlations (i.e. temporal persistence). Our data set consists of time series of yearly average collaboration radii and of cross-border links in the Euro-American subsystem of the global collaboration network for the period 1978–2014. To investigate the fundamental persistence properties of these time series, we use Detrended Fluctuation Analysis, a method that allows us to measure long-term correlations in detrended signals. Also, we devise a general and original procedure to assess the statistical significance of results for short time series. Our results, showing that long-term correlations do exist in the majority of our signals, reinforce the hypothesis of a diminishing role of geographical distance in technological collaborations. Results at national level show that a significant degree of heterogeneity in persistence parameters can be detected within Europe, irrespectively of the efforts towards the set-up of an integrated European Research Area. [ABSTRACT FROM AUTHOR]

Abstract State estimation is a widely adopted soft sensing technique that incorporates predictions from an accurate model of the process and measurements to provide reliable estimates of unmeasured variables. The reliability of such estimators is threatened by measurement related challenges and model inaccuracies. In this article, a method for benchmarking of state estimation techniques is proposed. This method can be used to quantify the performance and hence reliability of an estimator. The Hurst exponents of a posteriori filtering errors are analyzed to characterize a benchmark (minimum mean squared error) estimator, similar to the minimum variance control benchmark developed for control loops. A distance metric is then used to quantify the extent of deviation of an estimator from the benchmark. The proposed technique is developed for linear systems and extended to non-linear systems with single as well as multiple measurable variables. Simulation studies are carried out with Kalman based as well as Monte Carlo based estimators whose computational details are significantly different. Results reveal that the technique serves as a tool that can quantify the performance and assess the reliability of a state estimator. The strengths and limitations of the proposed technique are discussed with guidelines on applications and deployment of the technique in a real life system. Highlights • State estimation is a widely used soft sensing tool. • The performance of an estimator is dependent on modeling accuracy and approximations. • A method for benchmarking the performance of estimators along with a measure of performance with respect to the benchmark are proposed. • The method is independent of the nature of the system and computational details of the estimator. [ABSTRACT FROM AUTHOR]

Rapid advancement in computer vision technologies provides increasing opportunities for the quantitative characterization of animal behavior, although reduction of their analysis to several scalar metrics appears a common limitation for the representation of complex behavioral patterns. Here we suggest an alternative approach to the quantitative assessment of animal behavioral patterns by parameterization of a generalized scalable model based on fractional Brownian motion using detrended fluctuation analysis of the observational movement trajectories and validate it using novel tank test data. In a zebrafish model representative movement patterns are characterized by two asymptotic regimes, with persistent increments at small scales and antipersistent increments at large scales. A single crossover between these asymptotic regimes that appears a single free parameter of the animal movement model acts as a complementary behavioral indicator leading to a more explicit characterization of both stimulative and sedative effects. We show explicitly that the model can be also used for a robust estimation of interpretable scalar metrics commonly used in behavioral analysis leading to the emphasized differences between experimental groups. We believe that this approach, due to its universality, robustness and clear physical interpretation, is a perspective tool for the analysis of animal behavior complexity under various experimental and natural conditions. [Display omitted] • Animal movements in confined space are represented by two asymptotic scaling regimes. • One-parameter model based on fractional Brownian motion represents animal movements. • Crossover position between scaling regimes reflects stimulative and sedative effects. • The model based approach leads to a more robust estimates of animal movement metrics. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of Beijing Institute of Technology is the property of Beijing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study proposes the following two methods applying two-dimensional DFA (detrended fluctuation analysis) and two-dimensional FFT (fast Fourier transform) algorithm: (1) a method for finding pleasant photographs of local tourist spots, and (2) a method for generating music from these photographs. We define “pleasant image” as the photograph containing 1/ f noise components since it has been suggested that the 1/ f -noise structure in visual art as well as in music can stimulate the perception of pleasant. The method for extracting music from the picture is developed as follows: (a) the image is divided into some squares and frequency components are extracted from each square by two-dimensional FFT, and then (b) the frequency components of each square are transformed into musical pitches. A method to arrange the music by reflecting features of the image is also provided. [ABSTRACT FROM AUTHOR]

Background: In the Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT), a significant fraction of the patients with congestive heart failure ultimately did not die suddenly of arrhythmic causes. Patients with CHF will benefit from better tools to identify if implantable cardioverter-defibrillator (ICD) therapy is needed.Objectives: We aimed to identify predictor variables from baseline SCD-HeFT patients' R-R intervals that correlate to arrhythmic sudden cardiac death (SCD) and mortality and to design an ICD therapy screening test.Methods: Ten predictor variables were extracted from prerandomization Holter data from 475 patients enrolled in the ICD arm of the SCD-HeFT by using novel and traditional heart rate variability methods. All variables were correlated to SCD using the Mann-Whitney-Wilcoxon test and receiver operating characteristic analysis. ICD therapy screening tests were designed by minimizing the cost of false classifications. Survival analysis, including log-rank test and Cox models, was also performed.Results: A short-term fractal exponent, α1, and a long-term fractal exponent, α2, from detrended fluctuation analysis, the ratio of low- to high-frequency power, the number of premature ventricular contractions per hour, and the heart rate turbulence slope are all statistically significant for predicting the occurrences of SCD (P < .001) and survival (log-rank, P < .01). The most powerful multivariate predictor tool using the Cox proportional hazards regression model was α2 with a hazard ratio of 0.0465 (95% confidence interval 0.00528-0.409; P < .01).Conclusion: Predictor variables extracted from R-R intervals correlate to the occurrences of SCD and distinguish survival functions among patients with ICDs in SCD-HeFT. We believe that SCD prediction models should incorporate Holter-based R-R interval analysis to refine ICD patient selection, especially to exclude patients who are unlikely to benefit from ICD therapy. [ABSTRACT FROM AUTHOR]

This paper introduces a methodology for the characterization of time-scale-dependent variability in wind patterns. Successive windows of wind speed time series are first analyzed using detrended fluctuation analysis. Isopersistence diagrams are then constructed to reflect the scale-by-scale variability of wind speed over time. Next, wind velocity vectors are projected on a plane that is rotated step by step, and a time-scale-sensitive analysis of the resulting projections is performed for each orientation of the plane, leading to an image of orientation–time-scale–persistence patterns. This methodology is designed to enhance the effectiveness of studies on site-dependent wind variability. [ABSTRACT FROM AUTHOR]

The nonlinearity and non-stationarity are two kinds of characteristics of gear fault vibration signals. The detrended fluctuation analysis (DFA) is introduced to extract the characteristics of vibration signals. With this method, the gear vibration signals acquired from experimental bench are analyzed. The logarithm scale-fluctuation function maps of DFA show that the signals are double-scaling which mean that there are different power-law correlated between scale and fluctuation amplitude in different time scale. The reason of double-scaling was discussed and a feature vector of gear vibration signal which consisted of the small scale exponent and the intercept was suggested. With proposed feature vector, 100 groups of training signals corresponding to different fault conditions are described by Gaussian mixture model and 50 groups of test signals are classified by maximum Bayes classification. The results verify that higher failure recognition rate can be got by proposed feature extraction method. [ABSTRACT FROM AUTHOR]

Using the ten day sunshine duration data of 107 meteorological stations in Henan Province from 1961 to 2012, spatial temporal variation characteristics of ten day sunshine duration were analyzed, and the scale invariance analysis of ten day sunshine duration was studied by using the method of detrended fluctuation analysis. The results showed that the means of ten day sunshine duration and its standardized error among stations were 57.90 and 9.18 h, respectively, and their probability distributions were not subject to normal distribution. The cumulative abnormal of sun shine duration had a distinct linear increasing trend, however, its square deviation among the stations was of phase characteristics. The scale index of ten-day sunshine of each station was above 0.5, indicated that time series of scale index was of permanence. Variation of scale index among stations was small, which obeyed the normal distribution. [ABSTRACT FROM AUTHOR]

• The novel indicator α 1 ratio from multi-site PAT by DFA is robust to posture change. • The sensitivity in detecting PAD was improved from 78.6% to 92.9% by combing ABI with α 1 ratio. • Multi-site PAT provides superior indicators for PAD detection than R-R interval. The ankle-brachial index (ABI) test is a common tool used for screening peripheral arterial disease (PAD), but its accuracy has been doubted especially in patients with incompressible arteries attributed to calcification. Advanced wearable sensing technologies have potential to offer novel solutions for PAD assessment. This study investigated several novel indicators using the Detrended Fluctuation Analysis (DFA) on beat-to-beat RR interval (RRI) and pulse arrival time (PAT) from the four limbs of 7 young healthy and 7 elderly PAD subjects in supine and sitting postures. The auxiliary value of these indicators in addition to ABI for PAD assessment was also studied using a binary logistic regression model. The results showed that the short-scale DFA coefficients (α 1) of RRI, α 1 of PATs of fingers and α 1 _ratio of PAT (the ratio of α 1 of PAT between the ipsilateral finger and toe) in supine posture, were significantly different between the PAD and healthy groups (1.26 ± 0.24 vs 0.76 ± 0.21, 1.03 ± 0.30 vs 0.68 ± 0.19, and 0.84 ± 0.20 vs 1.42 ± 0.47, respectively, p < 0.05), and the α 1 of RRI and α 1 _ratio of PAT were not significantly influenced by postural change. Moreover, using ABI together with the supine α 1 _ratio of PAT was more sensitive in detecting PAD (sensitivity = 92.9%) than ABI alone (78.6%) with the same specificity of 100%. The short-scale DFA coefficients of multi-site PAT in supine posture, which can be measured by wearable devices, is an auxiliary to ABI for detecting PAD. [ABSTRACT FROM AUTHOR]

Nonlinear methods have been applied to the analysis of biological signals. Complexity analysis of glucose time series may be a useful tool for the study of the initial phases of glucoregulatory dysfunction. This observational, cross-sectional study was performed in patients with essential hypertension. Glucose complexity was measured with detrended fluctuation analysis (DFA), and glucose variability was measured by the mean amplitudes of glycemic excursion (MAGE). We included 91 patients with a mean age of 59 ± 10 years. We found significant correlations for the number of metabolic syndrome (MS)-defining criteria with DFA ( r = 0.233, P = .026) and MAGE ( r = 0.396, P < .0001). DFA differed significantly between patients who complied with MS and those who did not (1.44 vs. 1.39, P = .018). The MAGE ( f = 5.3, P = .006), diastolic blood pressures ( f = 4.1, P = .018), and homeostasis model assessment indices ( f = 4.2, P = .018) differed between the DFA tertiles. Multivariate analysis revealed that the only independent determinants of the DFA values were MAGE (β coefficient = 0.002, 95% confidence interval: 0.001–0.004, P = .001) and abdominal circumference (β coefficient = 0.002, 95% confidence interval: 0.000015–0.004, P = .048). In our population, DFA was associated with MS and a number of MS criteria. Complexity analysis seemed to be capable of detecting differences in variables that are arguably related to the risk of the development of type 2 diabetes. [ABSTRACT FROM AUTHOR]

Background: Fraction of exhaled nitric oxide (Feno), a marker of airway inflammation, has been proposed to be useful for asthma management, but conclusions are inconsistent. This might be due to the failure of mean statistics to characterize individual variability in Feno values, which is possibly a better indicator of asthma control than single measurements. Objective: We characterized fractal fluctuations in daily Feno values over time and the relationship between Feno values and symptom scores. We investigated whether these are associated with asthma severity, control, and exacerbation risk. Methods: Daily Feno values and symptom scores over 192 days in 41 atopic asthmatic children from the Childhood Asthma Respiratory Inflammatory Status Monitoring study were analyzed. Two methods of time-series analysis were used: detrended fluctuation analysis to quantify fractal patterns in fluctuations in daily Feno values (α value) and cross-correlation to quantify the strength of the relationship between daily Feno values and symptom scores. The associations of α values and cross-correlation with markers of asthma severity and control were assessed by means of regression analysis. Results: Daily fluctuations in Feno values exhibited fractal-type long-range correlations. Those subjects receiving higher doses of inhaled corticosteroids at study entry had a significantly lower α value, corresponding to more random fluctuations in Feno values in those with greater inhaled corticosteroid need. The cross-correlation between Feno values and symptom scores was significantly higher in those subjects who had exacerbations. Conclusions: Fluctuation in Feno values and their cross-correlation to symptom scores contains information on asthma severity and control. Methods that quantify the complexity of asthma over time might assist in identifying asthmatic subjects with concordance between eosinophilic inflammation and symptoms and thus increased exacerbation risk. [ABSTRACT FROM AUTHOR]

We focus on finite sample properties of two mostly used methods of Hurst exponent H estimation-rescaled range analysis (R/S) and detrended fluctuation analysis (DFA). Even though both methods have been widely applied on different types of financial assets, only several papers have dealt with the finite sample properties which are crucial as the properties differ significantly from the asymptotic ones. Recently, R/S analysis has been shown to overestimate H when compared to DFA. However, we show that even though the estimates of R/S are truly significantly higher than an asymptotic limit of 0.5, for random time series with lengths from 29 to 217, they remain very close to the estimates proposed by Anis & Lloyd and the estimated standard deviations are lower than the ones of DFA. On the other hand, DFA estimates are very close to 0.5. The results propose that R/S still remains useful and robust method even when compared to newer method of DFA which is usually preferred in recent literature. [ABSTRACT FROM AUTHOR]

Optic Flow (OF) plays an important role in human locomotion and manipulation of OF characteristics can cause changes in locomotion patterns. The purpose of the study was to investigate the effect of the velocity of optic flow on the amount and structure of gait variability. Each subject underwent four conditions of treadmill walking at their self-selected pace. In three conditions the subjects walked in an endless virtual corridor, while a fourth control condition was also included. The three virtual conditions differed in the speed of the optic flow displayed as follows - same speed (OFn), faster (OFf), and slower (OFs) than that of the treadmill. Gait kinematics were tracked with an optical motion capture system. Gait variability measures of the hip, knee and ankle range of motion and stride interval were analyzed. Amount of variability was evaluated with linear measures of variability - coefficient of variation, while structure of variability i.e., its organization over time, were measured with nonlinear measures - approximate entropy and detrended fluctuation analysis. The linear measures of variability, CV, did not show significant differences between Non-VR and VR conditions while nonlinear measures of variability identified significant differences at the hip, ankle, and in stride interval. In response to manipulation of the optic flow, significant differences were observed between the three virtual conditions in the following order: OFn> OFf > OFs. Measures of structure of variability are more sensitive to changes in gait due to manipulation of visual cues, whereas measures of the amount of variability may be concealed by adaptive mechanisms. Visual cues increase the complexity of gait variability and may increase the degrees of freedom available to the subject. Further exploration of the effects of optic flow manipulation on locomotion may provide us with an effective tool for rehabilitation of subjects with sensorimotor issues. [ABSTRACT FROM AUTHOR]

Summary: There is increasing interest in the study of fractals in medicine. In this review, we provide an overview of fractals, of techniques available to describe fractals in physiological data, and we propose some reasons why a physician might benefit from an understanding of fractals and fractal analysis, with an emphasis on paediatric respiratory medicine where possible. Among these reasons are the ubiquity of fractal organisation in nature and in the body, and how changes in this organisation over the lifespan provide insight into development and senescence. Fractal properties have also been shown to be altered in disease and even to predict the risk of worsening of disease. Finally, implications of a fractal organisation include robustness to errors during development, ability to adapt to surroundings, and the restoration of such organisation as targets for intervention and treatment. [Copyright &y& Elsevier]

Upright sitting is one of the first motor skills an infant learns, and thus sitting postural control provides an early window into the infant motor development. Early identification of infants with motor developmental delay, such as infants with cerebral palsy, allows for early therapeutic intervention by physical therapists. Early intervention is thought to produce better outcomes, due to greater neural plasticity in younger infants. Postural sway, as measured by a force plate, can be used to objectively and quantitatively characterize infant motor control during sitting. Pathology, such as cerebral palsy, may alter the fractal properties of motor function. Often physiologic time series data, including infant sitting postural sway data, is mathematically non-stationary. Detrended Fluctuation Analysis (DFA) is useful to characterize the fractal nature of time series data because it is does not assume stationarily of the data. In this study we found that suitable selection of the order of the detrending function improves the performance of the DFA algorithm, with a higher order polynomial detrending better able to distinguish infant silting posture time series data from Brown noise (random walk), and first order detrending better able to distinguish infants with motor delay (cerebral palsy) from infants with typical development. [ABSTRACT FROM AUTHOR]

The cold pressor test (CPT) triggers in healthy subjects a vascular sympathetic activation and an increase in blood pressure. The heart rate (HR) response to this test is less well defined, with a high inter-individual variability. We used traditional spectral analysis together with the non-linear detrended fluctuation analysis to study the autonomic control of HR during a 3-min CPT. 39 healthy young subjects (23.7±3.2 years, height 180.4±4.7 cm and weight 73.3±6.4 kg) were divided into two groups according to their HR responses to CPT. Twenty subjects have a sustained increase in HR throughout the test with reciprocal autonomic interaction, i.e. increase in sympathetic activity and decrease vagal outflow. In the 19 remainders, HR decreased after an initial increase, with indication of involvement of both sympathetic and vagal outflow. Baseline evaluation of the subjects revealed no difference between the two groups. Nevertheless, a higher sympathetic activity at the skin level during CPT was present in the group with decreased HR. Further studies are needed to explain why healthy subjects react differently to the CPT and if this has potential clinical implications. [ABSTRACT FROM AUTHOR]

The article explores the structure of variability of gait in humans, such as walking and running. It was found that the variability of walking or running is dependent on speed of gait. Also, the preferred speed of gait is said to provide the potential for adaptability in stride and step. The researchers suggest that models in gait dynamics can be developed with the help of findings on speed of locomotion.

Abstract: Multi-temporal series of satellite SPOT-VEGETATION normalized difference of vegetation index (NDVI) and normalized difference infrared index (NDII) data from 1998 to 2003 were exploited for studying persistence in mediterranean ecosystems of the Sardinia region (southern Italy). Three different vegetation covers (shrub-land, transitional and forest) were analysed. The NDVI and NDII provide information on the vegetation status and water content, respectively. The detrended fluctuation analysis (DFA), which permits the detection of persistent properties in nonstationary signal fluctuations, was applied to the NDVI and NDII time series for the three vegetation covers. Our findings point out that the investigated ecosystems are characterized by persistent behaviour of NDVI and NDII, which means that they are governed by positive feedback mechanisms, which tend to destabilize the systems under external forces. The NDII exhibits a more persistent behaviour than NDVI, and the shrub-land shows a more persistent feature than the other two cover types. [Copyright &y& Elsevier]