Integrated valorization of Anona Cherimola Mill. seeds

Agricultural and agro-industrial residues are often considered both an environmental and an economical problem. Therefore, a paradigm shift is needed, assuming residues as biorefinery feedstocks. In this work cherimoya (Annona cherimola Mill.) seeds, which are lipid-rich (ca. 30%) and have a significant lignocellulosic fraction, were used as an example of a residue without any current valorization. Firstly, the lipid fraction was obtained by solvent extraction. Extraction yield varied from 13% to 28%, according to the extraction method and time, and solvent purity. This oil was converted into biodiesel (by base-catalyzed transesterification), yielding 76 g FAME/100 g oil. The obtained biodiesel is likely to be incorporated in the commercial chain, according to the EN14214 standard. The remaining lignocellulosic fraction was subjected to two alternative fractionation processes for the selective recovery of hemicellulose, aiming different products. Empirical mathematical models were developed for both processes, aiming future scale-up. Autohydrolysis rendered essentially oligosaccharides (10 gL-1) with properties indicating potential food/feed/pharmacological applications. The remaining solid was enzymatically saccharified, reaching a saccharification yield of 83%. The hydrolyzate obtained by dilute acid hydrolysis contained mostly monosaccharides, mainly xylose (26 gL-1), glucose (10 gL-1) and arabinose (3 gL-1), and had low content of microbial growth inhibitors. This hydrolyzate has proven to be appropriate to be used as culture media for exopolisaccharide production, using bacteria or microbial consortia. The maximum conversion of monosaccharides into xanthan gum was 0.87 g/g and kefiran maximum productivity was 0.07 g.(Lh)-1. This work shows the technical feasibility of using cherimoya seeds, and materials as such, as potential feedstocks, opening new perspectives for upgrading them in the biorefinery framework.

Estudo da organização funcional do sistema circadiano por meio de ferramentas computacionais e matemáticas

Circadian rhythms are variations in physiological processes that help living beings to adapt to environmental cycles. These rhythms are generated and are synchronized to the dark light cycle through the suprachiasmatic nucleus. The integrity of circadian rhythmicity has great implication on human health. Currently it is known that disturbances in circadian rhythms are related to some problems of today such as obesity, propensity for certain types of cancer and mental disorders for example. The circadian rhythmicity can be studied through experiments with animal models and in humans directly. In this work we use computational models to gather experimental results from the literature and explain the results of our laboratory. Another focus of this study was to analyze data rhythms of activity and rest obtained experimentally. Here we made a review on the use of variables used to analyze these data and finally propose an update on how to calculate these variables. Our models were able to reproduce the main experimental results in the literature and provided explanations for the results of experiments performed in our laboratory. The new variables used to analyze the rhythm of activity and rest in humans were more efficient to describe the fragmentation and synchronization of this rhythm. Therefore, the work contributed improving existing tools for the study of circadian rhythms in mammals

Applied models to biodegradation kinetics of lubricant and vegetable oils in wastewater

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Non-linear growth models for bullfrog tadpoles

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

STOCHASTIC QUANTIZATION OF FERMIONIC THEORIES - RENORMALIZATION OF THE MASSIVE THIRRING MODEL

Using the Langevin approach for stochastic processes, we study the renormalizability of the massive Thirring model. At finite fictitious time, we prove the absence of induced quadrilinear counterterms by verifying the cancellation of the divergencies of graphs with four external lines. This implies that the vanishing of the renormalization group beta function already occurs at finite times.

Evaluation and identification of lightning models by artificial neural networks

This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.

Quantum tunneling fragmentation model

A nonthermal quantum mechanical statistical fragmentation model based on tunneling of particles through potential barriers is studied in compact two- and three-dimensional systems. It is shown that this fragmentation dynamics gives origin to several static and dynamic scaling relations. The critical exponents are found and compared with those obtained in classical statistical models of fragmentation of general interest, in particular with thermal fragmentation involving classical processes over potential barriers. Besides its general theoretical interest, the fragmentation dynamics discussed here is complementary to classical fragmentation dynamics of interest in chemical kinetics and can be useful in the study of a number of other dynamic processes such as nuclear fragmentation. ©2000 The American Physical Society.

Fractal approach to ac impedance spectroscopy studies of ceramic materials

A novel fractal model for grain boundary regions of ceramic materials was developed. The model considers laterally inhomogeneous distribution of charge carriers in the vicinity of grain boundaries as the main cause of the non-Debye behaviour and distribution of relaxation times in ceramic materials. Considering the equivalent circuit the impedance of the grain boundary region was expressed. It was shown that the impedance of the grain boundary region has the form of the Davidson-Cole equation. The fractal dimension of the inhomogeneous distribution of charge carriers in the region close to the grain boundaries could be calculated based on the relation ds = 1 + β, where β is the constant from the Davidson-Cole equation.

Precision of yule-walker methods for the arma spectral model

In this work a new method is proposed of separated estimation for the ARMA spectral model based on the modified Yule-Walker equations and on the least squares method. The proposal of the new method consists of performing an AR filtering in the random process generated obtaining a new random estimate, which will reestimate the ARMA model parameters, given a better spectrum estimate. Some numerical examples will be presented in order to ilustrate the performance of the method proposed, which is evaluated by the relative error and the average variation coefficient.

Characterization of cure of carbon/epoxy prepreg used in aerospace field

Carbon/epoxy 8552 prepreg is a thermoplastic toughened high-performance epoxy being used in the manufacture of advanced army material. Understanding the cure behavior of a thermosetting system is essential in the development and optimization of composite fabrication processes. The cure kinetics and rheological behavior were evaluated using a differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA) and a rheometer. Values of the kinetic parameters were obtained from dynamic DSC scans using an nth order reaction model. Rheological measurements as a function of temperature and time were made for the prepreg system. The manufacturer's recommended cure cycle was evaluated and considered adequate to consolidated the studied system.

Remarks on orthotropic elastic models applied to wood

Wood is generally considered an anisotropic material. In terms of engineering elastic models, wood is usually treated as an orthotropic material. This paper presents an analysis of two principal anisotropic elastic models that are usually applied to wood. The first one, the linear orthotropic model, where the material axes L (Longitudinal), R(radial) and T(tangential) are coincident with the Cartesian axes (x, y, z), is more accepted as wood elastic model. The other one, the cylindrical orthotropic model is more adequate of the growth caracteristics of wood but more mathematically complex to be adopted in practical terms. Specifically due to its importance in wood elastic parameters, this paper deals with the fiber orientation influence in these models through adequate transformation of coordinates. As a final result, some examples of the linear model, which show the variation of elastic moduli, i.e., Young's modulus and shear modulus, with fiber orientation are presented.

Usage of enterprise modeling processes and information systems design to forecast demand

Managing the great complexity of enterprise system, due to entities numbers, decision and process varieties involved to be controlled results in a very hard task because deals with the integration of its operations and its information systems. Moreover, the enterprises find themselves in a constant changing process, reacting in a dynamic and competitive environment where their business processes are constantly altered. The transformation of business processes into models allows to analyze and redefine them. Through computing tools usage it is possible to minimize the cost and risks of an enterprise integration design. This article claims for the necessity of modeling the processes in order to define more precisely the enterprise business requirements and the adequate usage of the modeling methodologies. Following these patterns, the paper concerns the process modeling relative to the domain of demand forecasting as a practical example. The domain of demand forecasting was built based on a theoretical review. The resulting models considered as reference model are transformed into information systems and have the aim to introduce a generic solution and be start point of better practical forecasting. The proposal is to promote the adequacy of the information system to the real needs of an enterprise in order to enable it to obtain and accompany better results, minimizing design errors, time, money and effort. The enterprise processes modeling are obtained with the usage of CIMOSA language and to the support information system it was used the UML language.

Mitigating systematic errors for single frequency GPS receivers employing a penalized least squares methodology

Among the positioning systems that compose GNSS (Global Navigation Satellite System), GPS has the capability of providing low, medium and high precision positioning data. However, GPS observables may be subject to many different types of errors. These systematic errors can degrade the accuracy of the positioning provided by GPS. These errors are mainly related to GPS satellite orbits, multipath, and atmospheric effects. In order to mitigate these errors, a semiparametric model and the penalized least squares technique were employed in this study. This is similar to changing the stochastical model, in which error functions are incorporated and the results are similar to those in which the functional model is changed instead. Using this method, it was shown that ambiguities and the estimation of station coordinates were more reliable and accurate than when employing a conventional least squares methodology.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Generating VHDL-AMS models of digital-to-analogue converters from MATLAB®/SIMULINK®

Today, the trend within the electronics industry is for the use of rapid and advanced simulation methodologies in association with synthesis toolsets. This paper presents an approach developed to support mixed-signal circuit design and analysis. The methodology proposed shows a novel approach to the problem of developing behvioural model descriptions of mixed-signal circuit topologies, by construction of a set of subsystems, that supports the automated mapping of MATLAB®/SIMULINK® models to structural VHDL-AMS descriptions. The tool developed, named MS 2SV, reads a SIMULINK® model file and translates it to a structural VHDL-AMS code. It also creates the file structure required to simulate the translated model in the System Vision™. To validate the methodology and the developed program, the DAC08, AD7524 and AD5450 data converters were studied and initially modelled in MATLAB®/ SIMULINK®. The VHDL-AMS code generated automatically by MS 2SV, (MATLAB®/SIMULINK® to System Vision™), was then simulated in the System Vision™. The simulation results show that the proposed approach, which is based on VHDL-AMS descriptions of the original model library elements, allows for the behavioural level simulation of complex mixed-signal circuits.