Synthetic generation of amyloid PET images by non-linear dimensionality reduction inversion

Privacy issues and data scarcity in PET field call for efficient methods to expand datasets via synthetic generation of new data that cannot be traced back to real patients and that are also realistic. In this thesis, machine learning techniques were applied to 1001 amyloid-beta PET images, which had undergone a diagnosis of Alzheimer’s disease: the evaluations were 540 positive, 457 negative and 4 unknown. Isomap algorithm was used as a manifold learning method to reduce the dimensions of the PET dataset; a numerical scale-free interpolation method was applied to invert the dimensionality reduction map. The interpolant was tested on the PET images via LOOCV, where the removed images were compared with the reconstructed ones with the mean SSIM index (MSSIM = 0.76 ± 0.06). The effectiveness of this measure is questioned, since it indicated slightly higher performance for a method of comparison using PCA (MSSIM = 0.79 ± 0.06), which gave clearly poor quality reconstructed images with respect to those recovered by the numerical inverse mapping. Ten synthetic PET images were generated and, after having been mixed with ten originals, were sent to a team of clinicians for the visual assessment of their realism; no significant agreements were found either between clinicians and the true image labels or among the clinicians, meaning that original and synthetic images were indistinguishable. The future perspective of this thesis points to the improvement of the amyloid-beta PET research field by increasing available data, overcoming the constraints of data acquisition and privacy issues. Potential improvements can be achieved via refinements of the manifold learning and the inverse mapping stages during the PET image analysis, by exploring different combinations in the choice of algorithm parameters and by applying other non-linear dimensionality reduction algorithms. A final prospect of this work is the search for new methods to assess image reconstruction quality.

Comparison of some theoretical models for fittings of the temperature dependence of the fundamental energy gap in GaAs

In this work we report on a comparison of some theoretical models usually used to fit the dependence on temperature of the fundamental energy gap of semiconductor materials. We used in our investigations the theoretical models of Viña, Pässler-p and Pässler-ρ to fit several sets of experimental data, available in the literature for the energy gap of GaAs in the temperature range from 12 to 974 K. Performing several fittings for different values of the upper limit of the analyzed temperature range (Tmax), we were able to follow in a systematic way the evolution of the fitting parameters up to the limit of high temperatures and make a comparison between the zero-point values obtained from the different models by extrapolating the linear dependence of the gaps at high T to T = 0 K and that determined by the dependence of the gap on isotope mass. Using experimental data measured by absorption spectroscopy, we observed the non-linear behavior of Eg(T) of GaAs for T > ΘD.

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.

Mechanical characterization of aortas using 2D ultrasound elastography

Rupture of aortic aneurysms (AA) is a major cause of death in the Western world. Currently, clinical decision upon surgical intervention is based on the diameter of the aneurysm. However, this method is not fully adequate. Noninvasive assessment of the elastic properties of the arterial wall can be a better predictor for AA growth and rupture risk. The purpose of this study is to estimate mechanical properties of the aortic wall using in vitro inflation testing and 2D ultrasound (US) elastography, and investigate the performance of the proposed methodology for physiological conditions. Two different inflation experiments were performed on twelve porcine aortas: 1) a static experiment for a large pressure range (0 – 140 mmHg); 2) a dynamic experiment closely mimicking the in vivo hemodynamics at physiological pressures (70 – 130 mmHg). 2D raw radiofrequency (RF) US datasets were acquired for one longitudinal and two cross-sectional imaging planes, for both experiments. The RF-data were manually segmented and a 2D vessel wall displacement tracking algorithm was applied to obtain the aortic diameter–time behavior. The shear modulus G was estimated assuming a Neo-Hookean material model. In addition, an incremental study based on the static data was performed to: 1) investigate the changes in G for increasing mean arterial pressure (MAP), for a certain pressure difference (30, 40, 50 and 60 mmHg); 2) compare the results with those from the dynamic experiment, for the same pressure range. The resulting shear modulus G was 94 ± 16 kPa for the static experiment, which is in agreement with literature. A linear dependency on MAP was found for G, yet the effect of the pressure difference was negligible. The dynamic data revealed a G of 250 ± 20 kPa. For the same pressure range, the incremental shear modulus (Ginc) was 240 ± 39 kPa, which is in agreement with the former. In general, for all experiments, no significant differences in the values of G were found between different image planes. This study shows that 2D US elastography of aortas during inflation testing is feasible under controlled and physiological circumstances. In future studies, the in vivo, dynamic experiment should be repeated for a range of MAPs and pathological vessels should be examined. Furthermore, the use of more complex material models needs to be considered to describe the non-linear behavior of the vascular tissue.

Modelling the exothermic heat and the demand of cooling in paper and pulp industry biological wastewater treatment

This master thesis presents a study on the requisite cooling of an activated sludge process in paper and pulp industry. The energy consumption of paper and pulp industry and it’s wastewater treatment plant in particular is relatively high. It is therefore useful to understand the wastewater treatment process of such industries. The activated sludge process is a biological mechanism which degrades carbonaceous compounds that are present in waste. The modified activated sludge model constructed here aims to imitate the bio-kinetics of an activated sludge process. However, due to the complicated non-linear behavior of the biological process, modelling this system is laborious and intriguing. We attempt to find a system solution first using steady-state modelling of Activated Sludge Model number 1 (ASM1), approached by Euler’s method and an ordinary differential equation solver. Furthermore, an enthalpy study of paper and pulp industry’s vital pollutants was carried out and applied to revise the temperature shift over a period of time to formulate the operation of cooling water. This finding will lead to a forecast of the plant process execution in a cost-effective manner and management of effluent efficiency. The final stage of the thesis was achieved by optimizing the steady state of ASM1.

Speech Analysis using Modern Techniques of Nonlinear Dynamics

Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.

Calibration of structure in a distributed forecasting model for a semiarid flash flood: dynamic surface storage and channel roughness

Flash floods pose a significant danger for life and property. Unfortunately, in arid and semiarid environment the runoff generation shows a complex non-linear behavior with a strong spatial and temporal non-uniformity. As a result, the predictions made by physically-based simulations in semiarid areas are subject to great uncertainty, and a failure in the predictive behavior of existing models is common. Thus better descriptions of physical processes at the watershed scale need to be incorporated into the hydrological model structures. For example, terrain relief has been systematically considered static in flood modelling at the watershed scale. Here, we show that the integrated effect of small distributed relief variations originated through concurrent hydrological processes within a storm event was significant on the watershed scale hydrograph. We model these observations by introducing dynamic formulations of two relief-related parameters at diverse scales: maximum depression storage, and roughness coefficient in channels. In the final (a posteriori) model structure these parameters are allowed to be both time-constant or time-varying. The case under study is a convective storm in a semiarid Mediterranean watershed with ephemeral channels and high agricultural pressures (the Rambla del Albujón watershed; 556 km 2 ), which showed a complex multi-peak response. First, to obtain quasi-sensible simulations in the (a priori) model with time-constant relief-related parameters, a spatially distributed parameterization was strictly required. Second, a generalized likelihood uncertainty estimation (GLUE) inference applied to the improved model structure, and conditioned to observed nested hydrographs, showed that accounting for dynamic relief-related parameters led to improved simulations. The discussion is finally broadened by considering the use of the calibrated model both to analyze the sensitivity of the watershed to storm motion and to attempt the flood forecasting of a stratiform event with highly different behavior.

Identificação em tempo real de modelo dinâmico de robô móvel com acionamento diferencial e zona morta

Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters

Two-dimensional modeling of material failure in reinforced concrete by means of a continuum strong discontinuity approach

The paper presents a new methodology to model material failure, in two-dimensional reinforced concrete members, using the Continuum Strong Discontinuity Approach (CSDA). The mixture theory is used as the methodological approach to model reinforced concrete as a composite material, constituted by a plain concrete matrix reinforced with two embedded orthogonal long fiber bundles (rebars). Matrix failure is modeled on the basis of a continuum damage model, equipped with strain softening, whereas the rebars effects are modeled by means of phenomenological constitutive models devised to reproduce the axial non-linear behavior, as well as the bondslip and dowel effects. The proposed methodology extends the fundamental ingredients of the standard Strong Discontinuity Approach, and the embedded discontinuity finite element formulations, in homogeneous materials, to matrix/fiber composite materials, as reinforced concrete. The specific aspects of the material failure modeling for those composites are also addressed. A number of available experimental tests are reproduced in order to illustrate the feasibility of the proposed methodology. (c) 2007 Elsevier B.V. All rights reserved.

A mixture theory based method for three-dimensional modeling of reinforce concrete members with embedded crack finite elements

The paper presents a methodology to model three-dimensional reinforced concrete members by means of embedded discontinuity elements based on the Continuum Strong Discontinuous Approach (CSDA). Mixture theory concepts are used to model reinforced concrete as a 31) composite material constituted of concrete with long fibers (rebars) bundles oriented in different directions embedded in it. The effects of the rebars are modeled by phenomenological constitutive models devised to reproduce the axial non-linear behavior, as well as the bond-slip and dowel action. The paper presents the constitutive models assumed for the components and the compatibility conditions chosen to constitute the composite. Numerical analyses of existing experimental reinforced concrete members are presented, illustrating the applicability of the proposed methodology.

Multifractal regime transition in a modified minority game model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Poole-Frenkel effect in Er doped SnO2 thin films deposited by sol-gel-dip-coating

Electrical properties of Er-doped SnO2 thin films obtained by sol-gel-dip-coating technique were measured. When compared to undoped tin dioxide, rare-earth doped films present much higher resistivity, indicating that Er3+ presents an acceptor-like character into the matrix, which leads to a high degree of electric charge compensation. Current-voltage characteristics, measured above room temperature for Er-doped films, lead to non-linear behavior and two conduction regimes. In the lower electric field range the conduction is dominated by Schottky emission over the grain boundary potential barrier, which presents an average value of 0.85 eV. Increasing the applied bias, a second regime of conduction is observed, since the Poole-Frenkel coulombic barrier lowering becomes a significant effect. The obtained activation energy for ionization is 0.67 eV. (C) 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dependência estrutural da capacidade de rotação plástic em vigas de concreto armado

Summary In this work the structural dependence of plastic rotation capacity in RC beams is evaluated using the Finite Element Method. The objective is to achieve a better understanding of the non-linear behavior of reinforced concrete members and perform extensive parameter studies, using a rational model developed by Bigaj [1] to analyze the phenomenon of plastic rotation capacity in reinforced concrete members. It is assumed that only bending failure is relevant due to sufficient member resistance against shear and torsion. The paper begins with the physical and theoretical background of the phenomenon of plastic hinge development in RC structures. Special emphasis is laid on the issue of structural dependence of deformation capacity of plastic hinges in RC members. Member size dependence and influence of properties of construction materials were emphasized as well. The essential components of the Bigajs model for calculating the plastic rotation capacity are discussed. The behaviour of the plastic hinge is analysed taking into account the strain localisation in the damage zones of the hinge region. The Fictitious Crack Model (FCM) and the Compressive Damage Zone Model (CDZ) are adopted in a Fracture Mechanics approach to model the behaviour of concrete in tension and compression, respectively. The approach is implemented in FEMOOP, a FEM in-house solver under development, and applied to evaluate ductility in 2D beams. The models were generated with GiD, a pre-processor and post-processor developed by CIMNE, and analyzed with the capabilities implemented in FEMOOP. © Universitat Politècnica de Catalunya, Barcelona, España 2010.

Fuzzy control embedded in microcontroller and applied to an experimental apparatus using magnetorheological fluid damper

This work focuses on applying fuzzy control embedded in microcontrollers in an experimental apparatus using magnetorheological fluid damper. The non-linear behavior of the magnetorheological dampers associated with the parametric variations on vehicle suspension models corroborate the use of the fuzzy controllers. The fundamental formulation of this controller is discussed and its performance is shown through numeric simulations. An experimental apparatus representing a two degree of freedom system containing a magnetorheological damper is used to identify the main parameters and to evaluate the performance of the closed-loop system with the embedded low-cost microcontroller-based fuzzy controller. © 2013 Brazilian Society for Automatics - SBA.

A finite element approach for predicting the ultimate rotation capacity of RC beams

This paper presents a numerical approach to model the complex failure mechanisms that define the ultimate rotational capacity of reinforced concrete beams. The behavior in tension and compression is described by a constitutive damage model derived from a combination of two specific damage models [1]. The nonlinear behavior of the compressed region is treated by the compressive damage model based on the Drucker-Prager criterion written in terms of the effective stresses. The tensile damage model employs a failure criterion based on the strain energy associated with the positive part the effective stress tensor. This model is used to describe the behavior of very thin bands of strain localization, which are embedded in finite elements to represent multiple cracks that occur in the tensioned region [2]. The softening law establishes dissipation energy compatible with the fracture energy of the concrete. The reinforcing steel bars are modeled by truss elements with elastic-perfect plastic behavior. It is shown that the resulting approach is able to predict the different stages of the collapse mechanism of beams with distinct sizes and reinforcement ratios. The tensile damage model and the finite element embedded crack approach are able to describe the stiffness reduction due to concrete cracking in the tensile zone. The truss elements are able to reproduce the effects of steel yielding and, finally, the compressive damage model is able to describe the non-linear behavior of the compressive zone until the complete collapse of the beam due to crushing of concrete. The proposed approach is able to predict well the plastic rotation capacity of tested beams [3], including size-scale effects.