932 resultados para Simulation and Modeling
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The field of bioelectronics involves the use of electrodes to exchange electrical signals with biological systems for diagnostic and therapeutic purposes in biomedical devices and healthcare applications. However, the mechanical compatibility of implantable devices with the human body has been a challenge, particularly with long-term implantation into target organs. Current rigid bioelectronics can trigger inflammatory responses and cause unstable device functions due to the mechanical mismatch with the surrounding soft tissue. Recent advances in flexible and stretchable electronics have shown promise in making bioelectronic interfaces more biocompatible. To fully achieve this goal, material science and engineering of soft electronic devices must be combined with quantitative characterization and modeling tools to understand the mechanical issues at the interface between electronic technology and biological tissue. Local mechanical characterization is crucial to understand the activation of failure mechanisms and optimizing the devices. Experimental techniques for testing mechanical properties at the nanoscale are emerging, and the Atomic Force Microscope (AFM) is a good candidate for in situ local mechanical characterization of soft bioelectronic interfaces. In this work, in situ experimental techniques with solely AFM supported by interpretive models for the characterization of planar and three-dimensional devices suitable for in vivo and in vitro biomedical experimentations are reported. The combination of the proposed models and experimental techniques provides access to the local mechanical properties of soft bioelectronic interfaces. The study investigates the nanomechanics of hard thin gold films on soft polymeric substrates (Poly(dimethylsiloxane) PDMS) and 3D inkjet-printed micropillars under different deformation states. The proposed characterization methods provide a rapid and precise determination of mechanical properties, thus giving the possibility to parametrize the microfabrication steps and investigate their impact on the final device.
Development of processes for the valorization of lignocellulosic biomass based on renewable energies
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The world grapples with climate change from fossil fuel reliance, prompting Europe to pivot to renewable energy. Among renewables, biomass is a bioenergy and bio-carbon source, used to create high-value biomolecules, replacing fossil-based products. Alkyl levulinates, derived from biomass, hold promise as bio-additives and biofuels, especially via acid solvolysis of hexose sugars, necessitating further exploration. Alkyl levulinate's potential extends to converting into γ-valerolactone (GVL), a bio-solvent produced via hydrogenation with molecular-hydrogen. Hydrogen, a key reagent and energy carrier, aids renewable energy integration. This thesis delves into a biorefinery system study, aligning with sustainability goals, integrating biomass valorization, energy production, and hydrogen generation. It investigates optimizing technologies for butyl levulinate production and subsequent GVL hydrogenation. Sustainability remains pivotal, reflecting the global shift towards renewable and carbon bio-resources. The research initially focuses on experimenting with the optimal technology for producing butyl levulinate from biomass-derived hexose fructose. It examines the solvolysis process, investigating optimal conditions, kinetic modeling, and the impact of solvents on fructose conversion. The subsequent part concentrates on the technological aspect of hydrogenating butyl levulinate into GVL. It includes conceptual design, simulation, and optimization of the fructose-to-GVL process scheme based on process intensification. In the final part, the study applies the process to a real case study in Normandy, France, adapting it to local biomass availability and wind energy. It defines a methodology for designing and integrating the energy-supply system, evaluating different scenarios. Sustainability assessment using economic, environmental, and social indicators culminates in an overall sustainability index, indicating scenarios integrating the GVL biorefinery system with wind power and hydrogen energy storage as promising due to high profitability and reduced environmental impact. Sensitivity analyses validate the methodology's reliability, potentially extending to other technological systems.
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Nowadays the urgency to address climate change and global warming is growing rapidly: the industry and the energy sector must be decarbonized. Hydrogen can play a key role in the energy transition: it is expected to progressively replace fossil fuels, penetrating economies and gaining interest from the public. However, this new possible energy scenario requires further investigation on safety aspects, which currently represent a challenge. The present study aims at making a little contribution to this field. The focus is on the analysis and modeling of hazardous scenarios concerning liquid hydrogen. The investigation of BLEVEs (Boiling Liquid Expanding Vapor Explosion) consequences lies at the core of this research: among various consequences (overpressure, radiation), the interest is on the generation and projection of fragments. The goal is to investigate whether the models developed for conventional fuels and tanks give good predictions also when handling hydrogen. The experimental data from the SH2IFT - Safe Hydrogen Fuel Handling and Use for Efficient Implementation project are used to validate those models. This project’s objective was to increase competence within safety of hydrogen technology, especially focusing on consequences of handling large amounts of this substance.
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The physical model was based on the method of Newton-Euler. The model was developed by using the scientific computer program Mathematica®. Several simulations where tried varying the progress speeds (0.69; 1.12; 1.48; 1.82 and 2.12 m s-1); soil profiles (sinoidal, ascending and descending ramp) and height of the profile (0.025 and 0.05 m) to obtain the normal force of soil reaction. After the initial simulations, the mechanism was optimized using the scientific computer program Matlab® having as criterion (function-objective) the minimization of the normal force of reaction of the profile (FN). The project variables were the lengths of the bars (L1y, L2, l3 and L4), height of the operation (L7), the initial length of the spring (Lmo) and the elastic constant of the spring (k t). The lack of robustness of the mechanism in relation to the variable height of the operation was outlined by using a spring with low rigidity and large length. The results demonstrated that the mechanism optimized showed better flotation performance in relation to the initial mechanism.
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In this paper we present a study of reading comprehension based on a contrastive argumentative-discursive approach. We examine the relationship between linguistic materiality and discursive processes, observing the connection between reading in a foreign language, writing production and textual memories in the mother tongue. In addition to an interest in practical language teaching and learning processes (in this case of Spanish and Portuguese), we investigate the question of politeness and the theoretical relationship between subjectivity, language, and textuality. The latter, being understood as the result of discourse regularities, is unique for each and every production, yet is also conditioned by plural discursive memories resulting from contradictory social relationships in a specific historical context (Foucault, 1986; Pêcheux, 1990). In the experiment presented here, we follow some of the procedures of the methodology applied in the European Galatea Project developed for the study of reading strategies in the inter-comprehension between Romance languages (Dabène, 1996). We use the procedure of simulation and the subjective projection of participants as well as the notion of discursive resonance in the analysis. The results, having to do with directness and indirectness in speech and the question of politeness in two typologically close languages, lead to the conclusion that the concept of politeness goes beyond a pragmatic strategy used to avoid conflicts to be approached as a marker of cultural identity constitution. The relevance of discursive awareness and its theoretical and practical consequences are then emphasized.
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Objective: The purpose of this study was to evaluate the effect of 830-nm laser in blocking the action of nicotine on the viability of skin flap. Background data: The authors have analyzed the deleterious effect of cigarette smoke or nicotine on the skin flap alone with evidence of increased skin necrosis in the flap. Materials and methods: Twenty-four Wistar-albino rats were divided into three groups of eight animals each: Group 1 (control), subjected to a surgical technique to obtain a flap for cranial base, laser irradiation simulation, and a subcutaneous injection of saline; Group 2, similar to Group 1, with subcutaneous injection of nicotine (2mg/kg/day) for a period of 1 week before and 1 week after surgery; and Group 3, similar to Group 2, with skin flaps subjected to a lambda 830-nm laser irradiation. The laser parameters used were: power 30 mW, beam area 0.07cm(2), irradiance 429 mW/cm(2), irradiation time 84 sec, total energy 2.52J, and energy density 36J/cm(2). The laser was used immediately after surgery and for 4 consecutive days, in one point at 2.5 cm of the flap cranial base. The areas of necrosis were examined by two macroscopic analyses: paper template and Mini-Mop (R). The pervious blood vessels were also counted. Results: The results were statistically analyzed by ANOVA and post-test contrast orthogonal method (multiple comparisons), showing that the laser decreased the area of necrosis in flaps subjected to nicotine, and consequently, increased the number of blood vessels (p < 0.05). Conclusions: The laser proved to be an effective way to decrease the area of necrosis in rats subjected to nicotine, making them similar to the control group.
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Through long-range transport of dust, the North-African desert supplies essential minerals to the Amazon rain forest. Since North African dust reaches South America mostly during the Northern Hemisphere winter, the dust sources active during winter are the main contributors to the forest. Given that the Bod,l, depression area in southwestern Chad is the main winter dust source, a close link is expected between the Bod,l, emission patterns and volumes and the mineral supply flux to the Amazon. Until now, the particular link between the Bod,l, and the Amazon forest was based on sparse satellite measurements and modeling studies. In this study, we combine a detailed analysis of space-borne and ground data with reanalysis model data and surface measurements taken in the central Amazon during the Amazonian Aerosol Characterization Experiment (AMAZE-08) in order to explore the validity and the nature of the proposed link between the Bod,l, depression and the Amazon forest. This case study follows the dust events of 11-16 and 18-27 February 2008, from the emission in the Bod,l, over West Africa (most likely with contribution from other dust sources in the region) the crossing of the Atlantic Ocean, to the observed effects above the Amazon canopy about 10 days after the emission. The dust was lifted by surface winds stronger than 14 m s(-1), usually starting early in the morning. The lofted dust, mixed with biomass burning aerosols over Nigeria, was transported over the Atlantic Ocean, and arrived over the South American continent. The top of the aerosol layer reached above 3 km, and the bottom merged with the boundary layer. The arrival of the dusty air parcel over the Amazon forest increased the average concentration of aerosol crustal elements by an order of magnitude.
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Shallow subsurface layers of gold nanoclusters were formed in polymethylmethacrylate (PMMA) polymer by very low energy (49 eV) gold ion implantation. The ion implantation process was modeled by computer simulation and accurately predicted the layer depth and width. Transmission electron microscopy (TEM) was used to image the buried layer and individual nanoclusters; the layer width was similar to 6-8 nm and the cluster diameter was similar to 5-6 nm. Surface plasmon resonance (SPR) absorption effects were observed by UV-visible spectroscopy. The TEM and SPR results were related to prior measurements of electrical conductivity of Au-doped PMMA, and excellent consistency was found with a model of electrical conductivity in which either at low implantation dose the individual nanoclusters are separated and do not physically touch each other, or at higher implantation dose the nanoclusters touch each other to form a random resistor network (percolation model). (C) 2009 American Vacuum Society. [DOI: 10.1116/1.3231449]
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Electron paramagnetic resonance measurements of NiCl(2)-4SC(NH(2))(2) reveal the low-energy spin dispersion, including a magnetic-field interval in which the two-magnon continuum is within k(B)T of the ground state, allowing a continuum of excitations over a range of k states, rather than only the k=0 single-magnon excitations. This produces a novel Y shape in the frequency-field EPR spectrum measured at T >= 1.5 K. Since the interchain coupling J(perpendicular to)< k(B)T, this shape can be reproduced by a single S=1 antiferromagnetic Heisenberg chain with a strong easy-plane single-ion anisotropy. Importantly, the combination of experiment and modeling we report herein demonstrates a powerful approach to probing spin dispersion in a wide range of interacting magnetic systems without the stringent sample requirements and complications associated with inelastic scattering experiments.
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In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.
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The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.
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We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.
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Recently, we have built a classification model that is capable of assigning a given sesquiterpene lactone (STL) into exactly one tribe of the plant family Asteraceae from which the STL has been isolated. Although many plant species are able to biosynthesize a set of peculiar compounds, the occurrence of the same secondary metabolites in more than one tribe of Asteraceae is frequent. Building on our previous work, in this paper, we explore the possibility of assigning an STL to more than one tribe (class) simultaneously. When an object may belong to more than one class simultaneously, it is called multilabeled. In this work, we present a general overview of the techniques available to examine multilabeled data. The problem of evaluating the performance of a multilabeled classifier is discussed. Two particular multilabeled classification methods-cross-training with support vector machines (ct-SVM) and multilabeled k-nearest neighbors (M-L-kNN)were applied to the classification of the STLs into seven tribes from the plant family Asteraceae. The results are compared to a single-label classification and are analyzed from a chemotaxonomic point of view. The multilabeled approach allowed us to (1) model the reality as closely as possible, (2) improve our understanding of the relationship between the secondary metabolite profiles of different Asteraceae tribes, and (3) significantly decrease the number of plant sources to be considered for finding a certain STL. The presented classification models are useful for the targeted collection of plants with the objective of finding plant sources of natural compounds that are biologically active or possess other specific properties of interest.