Fluxo de fluído através de um meio poroso fractal desordenado. Análise das tensões de cisalhamento e efeito de escala na estimativa das forças viscosas

In this work we have investigated some aspects of the two-dimensional flow of a viscous Newtonian fluid through a disordered porous medium modeled by a random fractal system similar to the Sierpinski carpet. This fractal is formed by obstacles of various sizes, whose distribution function follows a power law. They are randomly disposed in a rectangular channel. The velocity field and other details of fluid dynamics are obtained by solving numerically of the Navier-Stokes and continuity equations at the pore level, where occurs actually the flow of fluids in porous media. The results of numerical simulations allowed us to analyze the distribution of shear stresses developed in the solid-fluid interfaces, and find algebraic relations between the viscous forces or of friction with the geometric parameters of the model, including its fractal dimension. Based on the numerical results, we proposed scaling relations involving the relevant parameters of the phenomenon, allowing quantifying the fractions of these forces with respect to size classes of obstacles. Finally, it was also possible to make inferences about the fluctuations in the form of the distribution of viscous stresses developed on the surface of obstacles.

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Análise não linear de séries temporais e aplicações à Psicologia

Nesta dissertação estudámos as séries temporais que representam a complexa dinâmica do comportamento. Demos especial atenção às técnicas de dinâmica não linear. As técnicas fornecem-nos uma quantidade de índices quantitativos que servem para descrever as propriedades dinâmicas do sistema. Estes índices têm sido intensivamente usados nos últimos anos em aplicações práticas em Psicologia. Estudámos alguns conceitos básicos de dinâmica não linear, as características dos sistemas caóticos e algumas grandezas que caracterizam os sistemas dinâmicos, que incluem a dimensão fractal, que indica a complexidade de informação contida na série temporal, os expoentes de Lyapunov, que indicam a taxa com que pontos arbitrariamente próximos no espaço de fases da representação do espaço dinâmico, divergem ao longo do tempo, ou a entropia aproximada, que mede o grau de imprevisibilidade de uma série temporal. Esta informação pode então ser usada para compreender, e possivelmente prever, o comportamento. ABSTRACT: ln this thesis we studied the time series that represent the complex dynamic behavior. We focused on techniques of nonlinear dynamics. The techniques provide us a number of quantitative indices used to describe the dynamic properties of the system. These indices have been extensively used in recent years in practical applications in psychology. We studied some basic concepts of nonlinear dynamics, the characteristics of chaotic systems and some quantities that characterize the dynamic systems, including fractal dimension, indicating the complexity of information in the series, the Lyapunov exponents, which indicate the rate at that arbitrarily dose points in phase space representation of a dynamic, vary over time, or the approximate entropy, which measures the degree of unpredictability of a series. This information can then be used to understand and possibly predict the behavior.

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.

A comprehensive insight into floc characteristics and their impact on compressibility and settleability of activated sludge

This paper presents a comprehensive study of sludge floc characteristics and their impact on compressibility and settleability of activated sludge in full scale wastewater treatment processes. The sludge flocs were characterised by morphological (floc size distribution, fractal dimension, filament index), physical (flocculating ability, viscosity, hydrophobicity and surface charge) and chemical (polymeric constituents and metal content) parameters. Compressibility and settleability were defined in terms of the sludge volume index (SVI) and zone settling velocity (ZSV). The floc morphological and physical properties had important influence on the sludge compressibility and settleability. Sludges containing large flocs and high quantities of filaments, corresponding to lower values of fractal dimension (D-f), demonstrated poor compressibility and settleability. Sludge flocs with high flocculating ability had lower SVI and higher ZSV, whereas high values of hydrophobicity, negative surface charge and viscosity of the sludge flocs correlated to high SVI and low ZSV. The quantity of the polymeric compounds protein. humic substances and carbohydrate in the sludge and the extracted extracellular polymeric substances (EPS) had significant positive correlations with SVI. The ZSV was quantitatively independent of the polymeric constituents. High concentrations of the extracted EPS were related to poor compressibility and settleability. The cationic ions Ca, Mg, Al and Fe in the sludge improved significantly the sludge compressibility and settleability. (C) 2003 Elsevier Science B.V. All rights reserved.

Impacts of structural characteristics on activated sludge floc stability

Activated sludge samples from seven full-scale plants were investigated in order to determine the relationship between floc structure and floc stability. Floc stability was determined by shear sensitivity and floc strength. Floc structure was considered in terms of two size scales, the micro- and macrostructure. The microstructure refers to the organization of the floc components, such as the individual microorganisms. The macrostructure refers to the overall floc. The floc macrostructure was characterized by filament index, sludge volume index, size, and fractal dimension. It had a significant impact on floc stability. Large and open floes with low fractal dimensions containing large number of filaments were more shear sensitive and had lower floc strength compared to small and dense floes. Fluorescent in situ hybridization analysis indicated that the organization of the bacterial cells might also have an effect on the floc stability. (C) 2003 Elsevier Ltd. All rights reserved.

Quantifying chaos for ecological stoichiometry

The theory of ecological stoichiometry considers ecological interactions among species with different chemical compositions. Both experimental and theoretical investigations have shown the importance of species composition in the outcome of the population dynamics. A recent study of a theoretical three-species food chain model considering stoichiometry [B. Deng and I. Loladze, Chaos 17, 033108 (2007)] shows that coexistence between two consumers predating on the same prey is possible via chaos. In this work we study the topological and dynamical measures of the chaotic attractors found in such a model under ecological relevant parameters. By using the theory of symbolic dynamics, we first compute the topological entropy associated with unimodal Poincareacute return maps obtained by Deng and Loladze from a dimension reduction. With this measure we numerically prove chaotic competitive coexistence, which is characterized by positive topological entropy and positive Lyapunov exponents, achieved when the first predator reduces its maximum growth rate, as happens at increasing delta(1). However, for higher values of delta(1) the dynamics become again stable due to an asymmetric bubble-like bifurcation scenario. We also show that a decrease in the efficiency of the predator sensitive to prey's quality (increasing parameter zeta) stabilizes the dynamics. Finally, we estimate the fractal dimension of the chaotic attractors for the stoichiometric ecological model.