Changes of density, thermal conductivity, thermal diffusivity, and specific heat of plums during drying

The thermal properties of plums (Prunus domestica) and prunes were investigated in the moisture content of 14.2-80.4% (wet basis) near room temperature (approximately 28 degrees C). The apparent density of the fruits increased from 1042.9 to 1460.0 kg/m(3), and the bulk density increased from 706.6 to 897.5 kg/m(3) as the plums were dried, following classical empirical models as a function of moisture content. It was found that specific heat, effective thermal diffusivity, and effective thermal conductivity of the prunes increased with the moisture content of the samples, which can be represented by using different empirical models.

Density, heat capacity and thermal conductivity of liquid egg products

Density, heat capacity and thermal conductivity of liquid egg products, such as egg white, egg yolk, whole egg and various white and yolk blends, were determined as affected by temperature and water content ranging from 273 to 311 K and 51.8 to 88.2% (mass), respectively. Polynomial models fitted the experimental data very well, showing a linear relationship both for temperature and water content. (c) 2005 Published by Elsevier Ltd.

Tin(II)-EDTA complex: kinetic of thermal decomposition by non-isothermal procedures

Tin on the oxide form, alone or doped with others metals, has been extensively used as gas sensor, thus, this work reports on the preparation and kinetic parameters regarding the thermal decomposition of Sn(II)-ethylenediaminetetraacetate as precursor to SnO2. Thus, the acquaintance with the kinetic model regarding the thermal decomposition of the tin complex may leave the door open to foresee, whether it is possible to get thin film of SnO2 using Sn(II)-EDTA as precursor besides the influence of dopants added.The Sn(II)-EDTA soluble complex was prepared in aqueous medium by adding of tin(II) chloride acid solution to equimolar amount of ammonium salt from EDTA under N-2 atmosphere and temperature of 50degreesC arising the pH similar to 4. The compound was crystallized in ethanol at low-temperature and filtered to eliminate the chloride ions, obtaining the heptacoordinated chelate with the composition H2SnH2O(CH2N(CH2COO)(2))(2).0.5H(2)O.Results from TG, DTG and DSC curves under inert and oxidizing atmospheres indicate the presence of water coordinated to the metal and that the ethylenediamine fraction is thermally more stable than carboxylate groups. The final residue from thermal decomposition was the SnO2 characterized by X-ray as a tetragonal rutile phase.Applying the isoconversional Wall-Flynn-Ozawa method on the DSC curves, average activation energy: E-a = 183.7 +/- 12.7 and 218.9 +/- 2.1 kJ mol(-1), and pre-exponential factor: log A = 18.85 +/- 0.27 and 19.10 +/- 0.27 min(-1), at 95% confidence level, could be obtained, regarding the loss of coordinated water and thermal decomposition of the carboxylate groups, respectively. The E-a and logA also could be obtained applying isoconventional Wall-Flynn method on the TG curves.From E-a and log A values, Dollimore and Malek procedures could be applied suggesting R3 (contracting volume) and SB (two-parameter model) as the kinetic model to the loss of coordinated water (177-244degreesC) and thermal decomposition of the carboxylate groups (283-315degreesC), respectively. Simulated and experimental normalized DTG and DSC curves besides analysis of residuals check these kinetic models. (C) 2003 Elsevier B.V. All rights reserved.

Plant derived alkaloid (-)-cassine induces anti-inflammatory and anti-hyperalgesics effects in both acute and chronic inflammatory and neuropathic pain models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.

Adaptive control charts for attributes

We develop a general model for adaptive c, np, u and p control charts in which one, two or three design parameters (sample size, sampling interval and control limit width) switch between two values, according to the most recent process information. For a given in-control average sampling rate and a given false alarm rate, the adaptive chart detects changes in the process much faster than a chart with fixed parameters. Moreover, this study also offers general guidance on how to choose an effective design.

Thermal properties of passion fruit juice as affected by temperature and water content

The specific heat, thermal conductivity and density of passion fruit juice were experimentally determined from 0.506 to 0.902 (wet basis) water content and temperatures from 0.4 to 68.8C. The experimental results were compared with existing and widely used models for the thermal properties. In addition, based on empiric equations from literature, new simple models were parameterized with a subset of the total experimental data. The specific heat and thermal conductivity showed linear dependency on water content and temperature, while the density was nonlinearly related to water content. The generalized predictive models were considerably good for this product but the empiric, product-specific models developed in the present work yield better predictions. Even though the existing models showed a moderate accuracy, the new simple ones would be preferred, because they constitute an easier and direct way of evaluating the thermal properties of passion fruit juice, requiring no information about the chemical composition of the product, and a reduced time of the estimation procedure, as the new empiric models are described in terms of only two physical parameters, the water content and the temperature. © Copyright 2005, Blackwell Publishing All Rights Reserved.

Thermal evaporation: Representation of rise in boiling point of grapefruit juice

The rise in boiling point of grapefruit juice was experimentally measured at soluble solids concentrations in the range of 9.3-60.6 °Brix and pressures between °6.0 × 103 and 9.0 × 104 Pa. Different approaches to represent experimental data, including the Dhring's rule, the Antoine equation and empirical models proposed in the literature were tested. In the range of 9.3-29.0 °Brix, the rise in boiling point was nearly independent of pressure, varying only with juice concentration. Considerable deviations of this behavior began to occur at concentrations higher than 29.0 °Brix. Experimental data could be best predicted by adjusting an empirical model, which consisted of a single equation that takes into account the dependence of rise in boiling point on pressure and concentration. © SAGE Publications 2007.

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.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

Blood parameters of chicks from eggs injected with ascorbic acid and subjected to thermal stress

This study was aimed to verify if chicks from eggs injected with ascorbic acid and subjected to thermal stress would have higher immunity than chicks from incubation at thermoneutrality without injection of ascorbic acid. The parameters evaluated were temperature on oxygen saturation in hemoglobin, glucose, number of erythrocytes, hematocrit rate and number of hemoglobins of newly hatched male chicks, hatched from eggs injected with ascorbic acid (AA) and subjected to thermal stress during incubation. The experimental design was completely randomized in factorial scheme 5 (application levels of ascorbic acid) x 2 (incubation temperatures). The data were subjected to analysis of variance using the General Linear Model procedure (GLM) of SAS ®. For the parameters (number of erythrocytes, rate of hematrocit and values of hemoglobin), there was significant interaction (p <0.05) between treatments in egg and incubation temperatures. Analyzing the interactions for these parameters, it was observed that the application of 0% ascorbic acid in egg minimized the effect of heat stress when compared with treatment without injection. The application of ascorbic acid levels in eggs incubated under heat stress failed to maximize the immunity of newly hatched chicks. It is assumed that the increased liquid in the amniotic fluid, in those embryos injected with water, favored the lower heat conductance for these embryos, thus helping in their development in relation to immunity. Considering that hemoglobin is related to the transport of gases, these data suggest that increasing the concentration of AA solution inoculated may influence the respiratory rates of eggs.

Balance of pH of chicks from eggs injected with ascorbic acid and subjected to thermal stress

This study aimed to verify that chicks from eggs injected with ascorbic acid and subjected to heat stress would have changes in acid-base balance, compared to chicks incubated at thermoneutral without injection of ascorbic acid. The parameters evaluated were blood pressure of carbon dioxide and oxygen, base excess, total carbon dioxide, concentration of sodium, potassium, ionized calcium, bicarbonate and pH of newly hatched male chicks, hatched from eggs injected with acid ascorbic acid (AA) and subjected to heat stress during incubation. The experimental design was completely randomized in factorial scheme 5 (application levels of ascorbic acid) x 2 (incubation temperatures). The data were subjected to analysis of variance using the General Linear Model procedure (GLM) of SAS ®. For the blood pH was observed significant interaction (p <0.05) between treatments with application in eggs and incubation temperatures. For the other parameters were not significant effects (p< 0.05) of AA level and neither temperature of incubation. Analyzing the unfolding of the interaction to pH was observed that chicks from eggs injected with 6% ascorbic acid and subjected to heat stress during incubation had a higher pH value compared with the thermoneutral temperature incubated (p <0.05). Therefore, it is suggested that the incubation of eggs in high temperature (39°C) can alter the metabolic rate of these embryos.

Extrapolation of zircon fission-track annealing models

One of the purposes of this study is to give further constraints on the temperature range of the zircon partial annealing zone over a geological time scale using data from borehole zircon samples, which have experienced stable temperatures for ∼1 Ma. In this way, the extrapolation problem is explicitly addressed by fitting the zircon annealing models with geological timescale data. Several empirical model formulations have been proposed to perform these calibrations and have been compared in this work. The basic form proposed for annealing models is the Arrhenius-type model. There are other annealing models, that are based on the same general formulation. These empirical model equations have been preferred due to the great number of phenomena from track formation to chemical etching that are not well understood. However, there are two other models, which try to establish a direct correlation between their parameters and the related phenomena. To compare the response of the different annealing models, thermal indexes, such as closure temperature, total annealing temperature and the partial annealing zone, have been calculated and compared with field evidence. After comparing the different models, it was concluded that the fanning curvilinear models yield the best agreement between predicted index temperatures and field evidence. © 2012 Elsevier Ltd. All rights reserved.