Anomalous diffusion in non-Markovian walks having amnestically induced persistence

We report numerically and analytically estimated values for the Hurst exponent for a recently proposed non-Markovian walk characterized by amnestically induced persistence. These results are consistent with earlier studies showing that log-periodic oscillations arise only for large memory losses of the recent past. We also report numerical estimates of the Hurst exponent for non-Markovian walks with diluted memory. Finally, we study walks with a fractal memory of the past for a Thue-Morse and Fibonacci memory patterns. These results are interpreted and discussed in the context of the necessary and sufficient conditions for the central limit theorem to hold.

Spontaneous symmetry breaking in amnestically induced persistence

We investigate a recently proposed non-Markovian random walk model characterized by loss of memories of the recent past and amnestically induced persistence. We report numerical and analytical results showing the complete phase diagram, consisting of four phases, for this system: (i) classical nonpersistence, (ii) classical persistence, (iii) log-periodic nonpersistence, and (iv) log-periodic persistence driven by negative feedback. The first two phases possess continuous scale invariance symmetry, however, log-periodicity breaks this symmetry. Instead, log-periodic motion satisfies discrete scale invariance symmetry, with complex rather than real fractal dimensions. We find for log-periodic persistence evidence not only of statistical but also of geometric self-similarity.

Chaotic model and memory in single calcium-activated potassium channel kinetics

Ion channels are pores formed by proteins and responsible for carrying ion fluxes through cellular membranes. The ion channels can assume conformational states thereby controlling ion flow. Physically, the conformational transitions from one state to another are associated with energy barriers between them and are dependent on stimulus, such as, electrical field, ligands, second messengers, etc. Several models have been proposed to describe the kinetics of ion channels. The classical Markovian model assumes that a future transition is independent of the time that the ion channel stayed in a previous state. Others models as the fractal and the chaotic assume that the rate of transitions between the states depend on the time that the ionic channel stayed in a previous state. For the calcium activated potassium channels of Leydig cells the R/S Hurst analysis has indicated that the channels are long-term correlated with a Hurst coefficient H around 0.7, showing a persistent memory in this kinetic. Here, we applied the R/S analysis to the opening and closing dwell time series obtained from simulated data from a chaotic model proposed by L. Liebovitch and T. Toth [J. Theor. Biol. 148, 243 (1991)] and we show that this chaotic model or any model that treats the set of channel openings and closings as independent events is inadequate to describe the long-term correlation (memory) already described for the experimental data. (C) 2008 American Institute of Physics.

Multifractal regime transition in a modified minority game model

The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual minority game (MG) models do not exhibit multifractality, we study here one of its variants that does. We show that the nonsynchronous MG models in the nonergodic phase is multifractal and in this sense, together with other stylized facts, constitute a better modeling tool. Using the structure function (SF) approach we detected the stationary and the scaling range of the time series generated by the MG model and, from the linear (non-linear) behavior of the SF we identified the fractal (multifractal) regimes. Finally, using the wavelet transform modulus maxima (WTMM) technique we obtained its multifractal spectrum width for different dynamical regimes. (C) 2009 Elsevier Ltd. All rights reserved.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

Stretching and folding mechanism in foams

We have described the stretching and folding of foams in a vertical Hele-Shaw cell containing air and a surfactant solution, from a sequence of upside-down flips. Besides the firactal dimension of the foam, we have observed the logistic growth for the soap film length. The stretching and folding mechanism is present during the foam formation, and this mechanism is observed even after the foam has reached its respective maximum fractal dimension. Observing the motion of bubbles inside the foam, large bubbles present power spectrum associated with random walk motion in both directions, while the small bubbles are scattered like balls in a Galton board. (C) 2008 Published by Elsevier B.V.

Complexity of human postural control in young and older adults during prolonged standing

Aging is known to have a degrading influence on many structures and functions of the human sensorimotor system. The present work assessed aging-related changes in postural sway using fractal and complexity measures of the center of pressure (COP) dynamics with the hypothesis that complexity and fractality decreases in the older individuals. Older subjects (68 +/- 4 years) and young adult subjects (28 +/- 7 years) performed a quiet stance task (60 s) and a prolonged standing task (30 min) where subjects were allowed to move freely. Long-range correlations (fractality) of the data were estimated by the detrended fluctuation analysis (DFA); changes in entropy were estimated by the multi-scale entropy (MSE) measure. The DFA results showed that the fractal dimension was lower for the older subjects in comparison to the young adults but the fractal dimensions of both groups were not different from a 1/f noise, for time intervals between 10 and 600 s. The MSE analysis performed with the typically applied adjustment to the criterion distance showed a higher degree of complexity in the older subjects, which is inconsistent with the hypothesis that complexity in the human physiological system decreases with aging. The same MSE analysis performed without adjustment showed no differences between the groups. Taken all results together, the decrease in total postural sway and long-range correlations in older individuals are signs of an adaptation process reflecting the diminishing ability to generate adequate responses on a longer time scale.

Three-dimensional analysis of fracture, corrosion and wear surfaces

A brief look at the history of fractography has shown a recent trend in the quantification of topographic parameters through the use of three-dimensional reconstruction techniques, which associate SEM stereoscopy and stereophotogrammetry software, allowing the calculation of the elevation measurement at numerous points of the topography due to the parallax that takes place during the tilting of the sample along the microscope eucentric plane. Several investigators have used reconstruction techniques to correlate some fractographic parameters, such as fractal dimension and fractured to projected area ratio, to the mechanical properties of materials, such as fracture toughness and tensile strength. So far, the search for a clear relationship between the fracture topography and mechanical properties has provided ambiguous results. The present work applied a surface metrology software to reconstruct three-dimensionally fracture surfaces (transgranular cleavage, intergranular and dimple fracture), corrosion pits and tribo-surfaces in order to explore the potential of this stereophotogrammetry technique. The existence of a variation in the calculated topographic parameters with the conditions of SEM image acquisition reinforces the importance of both good image acquisition and accurate calibration methods in order to validate this 3D reconstruction technique in metrological terms. Preliminary results did not indicate the existence of a clear relationship between either the true to project area ratio and CVN absorbed energy or the fractal dimension and CVN absorbed energy. It is likely that each fracture mechanism presents a proper relationship between the fractographic parameters and mechanical properties. (C) 2009 Elsevier Ltd. All rights reserved.

A Nonstationary Model of Newborn EEG

The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

The relationship between interimplant distances and vascularization of the interimplant bone

Background Long-term success of the implant restorations is based upon the biology and vasculature of the bone surrounding the implants, especially for the bone between two implants. Purpose The aim of this study was to evaluate how loaded implants placed 2 or 3 mm apart influence bone vessel organization. Material and methods Six mongrel dogs were used for the study. The four mandibular premolars were extracted and 3 months later, four 4.5 x 10 mm implants were placed on each side of the mandible. The implants were placed so that two adjacent implants were 2 mm (group 1) or 3 mm (group 2) distant from each other. After 12 weeks, the implants were loaded with provisional prostheses, then metallic crowns were placed 4 weeks later. Both temporary and metallic restorations were made so that the distance between the contact point and the bone crest was 5 mm. The animals were sacrificed after 8 weeks. The hemi-mandibles were removed and prepared for analysis. The interimplant bone vasculature of the two groups was studied using scanning electron microscopic images fractal analysis. The fractal dimension (D(f)) was calculated using the box-counting method. Results The values of the D(f) for the blood vessels were significantly higher (P <.05) in the specimens of the group 2 (1.969 +/- 0.169) than the group 1 (1.556 +/- 0.246). Conclusion The presence of more blood vessels in the group 2 is another indication that 3 mm is a preferable distance for contiguous implants than the 2 mm distance. To cite this article:Traini T, Novaes AB, Piattelli A, Papalexiou V, Muglia VA. The relationship between interimplant distances and vascularization of the interimplant bone.Clin. Oral Impl. Res. 21, 2010; 822-829.doi: 10.1111/j.1600-0501.2010.01926.x.

Dendritic branching patterns of pyramidal cells in the visual cortex of the new world marmoset monkey, with comparative notes on the old world macaque monkey

The basal dendritic arbors of 442 supragranular pyramidal cells in visual cortex of the marmoset monkey were compared by fractal analyses. As detailed in a previous study,(1) individual cells were injected with Lucifer Yellow and processed for a DAB reaction product. The basal dendritic arbors were drawn, in the tangential plane, and the fractal dimension (D) determined by the dilation method. The fractal dimensions were compared between cells in ten cortical areas containing cells involved in visual processing, including the primary visual area (Vi), the second visual area (V2), the dorsoanterior area (DA), the dorsomedial area (DM), the dorsolateral. area (DL), the middle temporal area (MT), the posterior parietal area (PP), the fundus of the superior temporal area (FST) and the caudal and rostral subdivisions of inferotemporal cortex (ITc and ITr, respectively). Of 45 pairwise interareal comparisons of the fractal dimension of neurones, 20 were significantly different. Moreover, comparison of data according to previously published visual processing pathways revealed a trend for cells with greater fractal dimensions in higher cortical areas. Comparison of the present results with those in homologous cortical areas in the macaque monkey(2) revealed some similarities between the two species. The similarity in the trends of D values of cells in both species may reflect developmental features which, result in different functional attributes.

Pyramidal neurones in macaque visual cortex: Interareal phenotypic variation of dendritic branching patterns

The basal dendritic arbors of over 500-layer III pyramidal neurones of the macaque cortex were compared by fractal analyses, which provides a measure of the space filling (or branching pattern) of dendritic arbors. Fractal values (D) of individual cells were compared between the cytochrome oxidase (CO)-rich blobs and CO-poor interblobs, of middle and upper layer III, and between sublaminae, in the primary visual area (Vi). These data were compared with those in the CO compartments in the second visual area (V2), and seven other extrastriate cortical areas. (V4, MT, LIP, 7a, TEO, TE and STP). There were significant differences in the fractal dimensions, and therefore the dendritic branching patterns, of cells in striate and extrastriate areas. Of the 55 possible pairwise comparisons of fractal dimension of neurones in different cortical areas (or CO compartments), 39 proved to be significantly different. The markedly different morphologies of pyramidal cells in the different cortical areas may be one of the features that determine the functional signatures of these cells by influencing the number of inputs received by, and propagation of potentials through, their dendritic arbors.

Characterisation of pore structure of carbon adsorbents using regularisation procedure

The constrained regularisation procedure was applied to compute the pore size distributions (PSDs, f(x)) for a variety of activated carbons using overall adsorption equation based on the combination of the Kelvin equation and the statistical adsorbed film thickness. The impact of the boundary values of relative nitrogen pressure p/p(0) was analysed on the basis of the corresponding alterations in the PSDs. Changes in microporosity and mesoporosity of activated carbons can be described adequately only when the range of p/p(0) is as wide as possible, as at a high initial p/p(0) value, the f(x) curves can be broadened with shifted maxima especially for micropores and narrow mesopores. Comparative analysis of the PSDs and the adsorption potential, adsorption energy and fractal dimension distributions gives useful information on the complete description of the adsorbent characteristics. (C) 2001 Elsevier Science B.V. All rights reserved.

Novel molecular sieve silica (MSS) membranes: characterisation and permeation of single-step and two-step sol-gel membranes

High quality MSS membranes were synthesised by a single-step and two-step catalysed hydrolyses employing tetraethylorthosilicate (TEOS), absolute ethanol (EtOH), I M nitric acid (HNO3) and distilled water (H2O). The Si-29 NMR results showed that the two-step xerogels consistently had more contribution of silanol groups (Q(3) and Q(2)) than the single-step xerogel. According to the fractal theory, high contribution of Q(2) and Q(3) species are responsible for the formation of weakly branched systems leading to low pore volume of microporous dimension. The transport of diffusing gases in these membranes is shown to be activated as the permeance increased with temperature. Albeit the permeance of He for both single-step and two-step membranes are very similar, the two-step membranes permselectivity (ideal separation factor) for He/CO2 (69-319) and He/CH4 (585-958) are one to two orders of magnitude higher than the single-step membranes results of 2-7 and 69, respectively. The two-step membranes have high activation energy for He and H-2 permeance, in excess of 16 kJ mol(-1). The mobility energy for He permeance is three to six-fold higher for the two-step than the single-step membranes. As the mobility energy is higher for small pores than large pores and coupled with the permselectivity results, the two-step catalysed hydrolysis sol-gel process resulted in the formation of pore sizes in the region of 3 Angstrom while the single-step process tended to produce slightly larger pores. (C) 2002 Elsevier Science B.V. All rights reserved.

Learning the dynamics of embedded clauses

Recent work by Siegelmann has shown that the computational power of recurrent neural networks matches that of Turing Machines. One important implication is that complex language classes (infinite languages with embedded clauses) can be represented in neural networks. Proofs are based on a fractal encoding of states to simulate the memory and operations of stacks. In the present work, it is shown that similar stack-like dynamics can be learned in recurrent neural networks from simple sequence prediction tasks. Two main types of network solutions are found and described qualitatively as dynamical systems: damped oscillation and entangled spiraling around fixed points. The potential and limitations of each solution type are established in terms of generalization on two different context-free languages. Both solution types constitute novel stack implementations - generally in line with Siegelmann's theoretical work - which supply insights into how embedded structures of languages can be handled in analog hardware.